2024-08-27 23:30:48,745 - mmdet - INFO - Environment info:
------------------------------------------------------------
sys.platform: linux
Python: 3.9.19 (main, May  6 2024, 19:43:03) [GCC 11.2.0]
CUDA available: True
GPU 0,1,2,3,4,5,6,7: NVIDIA A100-SXM4-80GB
CUDA_HOME: /mnt/petrelfs/share_data/liqingyun/cuda-11.7/
NVCC: Cuda compilation tools, release 11.7, V11.7.64
GCC: gcc (GCC) 9.4.0
PyTorch: 1.12.0+cu113
PyTorch compiling details: PyTorch built with:
  - GCC 9.3
  - C++ Version: 201402
  - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications
  - Intel(R) MKL-DNN v2.6.0 (Git Hash 52b5f107dd9cf10910aaa19cb47f3abf9b349815)
  - OpenMP 201511 (a.k.a. OpenMP 4.5)
  - LAPACK is enabled (usually provided by MKL)
  - NNPACK is enabled
  - CPU capability usage: AVX2
  - CUDA Runtime 11.3
  - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86
  - CuDNN 8.9.7  (built against CUDA 11.8)
    - Built with CuDNN 8.3.2
  - Magma 2.5.2
  - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.3.2, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.12.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, 

TorchVision: 0.13.0+cu113
OpenCV: 4.9.0
MMCV: 1.7.0
MMCV Compiler: GCC 7.3
MMCV CUDA Compiler: 11.7
MMDetection: 2.25.3+a9214dc
------------------------------------------------------------

2024-08-27 23:30:50,298 - mmdet - INFO - Distributed training: True
2024-08-27 23:30:51,834 - mmdet - INFO - Config:
model = dict(
    type='MaskRCNN',
    backbone=dict(
        type='PIIPThreeBranch',
        n_points=4,
        deform_num_heads=16,
        cffn_ratio=0.25,
        deform_ratio=0.5,
        with_cffn=True,
        interact_attn_type='deform',
        interaction_drop_path_rate=0.4,
        with_simple_fpn=False,
        regular_fpn_type='merge',
        out_interaction_indexes=[0, 1, 10],
        branch1=dict(
            real_size=448,
            interaction_indexes=[[0, 2], [3, 6], [7, 10], [11, 13], [14, 16],
                                 [17, 19], [20, 22], [23, 25], [26, 28],
                                 [29, 31], [32, 34], [35, 38]],
            downsample_ratios=[
                4, 4, 4, 8, 8, 8, 8, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16,
                16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16,
                16, 16, 32, 32, 32, 32
            ],
            pretrained='facebook/convnext-base-224',
            drop_path_rate=0.4),
        branch2=dict(
            real_size=672,
            interaction_indexes=[[0, 2], [3, 6], [7, 10], [11, 13], [14, 16],
                                 [17, 19], [20, 22], [23, 25], [26, 28],
                                 [29, 31], [32, 34], [35, 38]],
            downsample_ratios=[
                4, 4, 4, 8, 8, 8, 8, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16,
                16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16,
                16, 16, 32, 32, 32, 32
            ],
            pretrained='facebook/convnext-small-224',
            drop_path_rate=0.3),
        branch3=dict(
            real_size=1024,
            interaction_indexes=[[0, 2], [3, 6], [7, 8], [9, 9], [10, 10],
                                 [11, 11], [12, 12], [13, 13], [14, 14],
                                 [15, 15], [16, 16], [17, 20]],
            downsample_ratios=[
                4, 4, 4, 8, 8, 8, 8, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16,
                32, 32, 32, 32
            ],
            pretrained='facebook/convnext-tiny-224',
            drop_path_rate=0.3)),
    neck=dict(
        type='FPN',
        in_channels=[128, 256, 512, 1024],
        out_channels=256,
        num_outs=5),
    rpn_head=dict(
        type='RPNHead',
        in_channels=256,
        feat_channels=256,
        anchor_generator=dict(
            type='AnchorGenerator',
            scales=[8],
            ratios=[0.5, 1.0, 2.0],
            strides=[4, 8, 16, 32, 64]),
        bbox_coder=dict(
            type='DeltaXYWHBBoxCoder',
            target_means=[0.0, 0.0, 0.0, 0.0],
            target_stds=[1.0, 1.0, 1.0, 1.0]),
        loss_cls=dict(
            type='CrossEntropyLoss', use_sigmoid=True, loss_weight=1.0),
        loss_bbox=dict(type='L1Loss', loss_weight=1.0)),
    roi_head=dict(
        type='StandardRoIHead',
        bbox_roi_extractor=dict(
            type='SingleRoIExtractor',
            roi_layer=dict(type='RoIAlign', output_size=7, sampling_ratio=0),
            out_channels=256,
            featmap_strides=[4, 8, 16, 32]),
        bbox_head=dict(
            type='Shared2FCBBoxHead',
            in_channels=256,
            fc_out_channels=1024,
            roi_feat_size=7,
            num_classes=80,
            bbox_coder=dict(
                type='DeltaXYWHBBoxCoder',
                target_means=[0.0, 0.0, 0.0, 0.0],
                target_stds=[0.1, 0.1, 0.2, 0.2]),
            reg_class_agnostic=False,
            loss_cls=dict(
                type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0),
            loss_bbox=dict(type='L1Loss', loss_weight=1.0)),
        mask_roi_extractor=dict(
            type='SingleRoIExtractor',
            roi_layer=dict(type='RoIAlign', output_size=14, sampling_ratio=0),
            out_channels=256,
            featmap_strides=[4, 8, 16, 32]),
        mask_head=dict(
            type='FCNMaskHead',
            num_convs=4,
            in_channels=256,
            conv_out_channels=256,
            num_classes=80,
            loss_mask=dict(
                type='CrossEntropyLoss', use_mask=True, loss_weight=1.0))),
    train_cfg=dict(
        rpn=dict(
            assigner=dict(
                type='MaxIoUAssigner',
                pos_iou_thr=0.7,
                neg_iou_thr=0.3,
                min_pos_iou=0.3,
                match_low_quality=True,
                ignore_iof_thr=-1),
            sampler=dict(
                type='RandomSampler',
                num=256,
                pos_fraction=0.5,
                neg_pos_ub=-1,
                add_gt_as_proposals=False),
            allowed_border=-1,
            pos_weight=-1,
            debug=False),
        rpn_proposal=dict(
            nms_pre=2000,
            max_per_img=1000,
            nms=dict(type='nms', iou_threshold=0.7),
            min_bbox_size=0),
        rcnn=dict(
            assigner=dict(
                type='MaxIoUAssigner',
                pos_iou_thr=0.5,
                neg_iou_thr=0.5,
                min_pos_iou=0.5,
                match_low_quality=True,
                ignore_iof_thr=-1),
            sampler=dict(
                type='RandomSampler',
                num=512,
                pos_fraction=0.25,
                neg_pos_ub=-1,
                add_gt_as_proposals=True),
            mask_size=28,
            pos_weight=-1,
            debug=False)),
    test_cfg=dict(
        rpn=dict(
            nms_pre=1000,
            max_per_img=1000,
            nms=dict(type='nms', iou_threshold=0.7),
            min_bbox_size=0),
        rcnn=dict(
            score_thr=0.05,
            nms=dict(type='nms', iou_threshold=0.5),
            max_per_img=100,
            mask_thr_binary=0.5)))
dataset_type = 'CocoDataset'
data_root = 'data/coco/'
img_norm_cfg = dict(
    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
train_pipeline = [
    dict(type='LoadImageFromFile'),
    dict(type='LoadAnnotations', with_bbox=True, with_mask=True),
    dict(type='Resize', img_scale=(1333, 800), keep_ratio=True),
    dict(type='RandomFlip', flip_ratio=0.5),
    dict(
        type='Normalize',
        mean=[123.675, 116.28, 103.53],
        std=[58.395, 57.12, 57.375],
        to_rgb=True),
    dict(type='Pad', size_divisor=32),
    dict(type='DefaultFormatBundle'),
    dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels', 'gt_masks'])
]
test_pipeline = [
    dict(type='LoadImageFromFile'),
    dict(
        type='MultiScaleFlipAug',
        img_scale=(1333, 800),
        flip=False,
        transforms=[
            dict(type='Resize', keep_ratio=True),
            dict(type='RandomFlip'),
            dict(
                type='Normalize',
                mean=[123.675, 116.28, 103.53],
                std=[58.395, 57.12, 57.375],
                to_rgb=True),
            dict(type='Pad', size_divisor=32),
            dict(type='ImageToTensor', keys=['img']),
            dict(type='Collect', keys=['img'])
        ])
]
data = dict(
    samples_per_gpu=2,
    workers_per_gpu=2,
    train=dict(
        type='CocoDataset',
        ann_file='data/coco/annotations/instances_train2017.json',
        img_prefix='data/coco/train2017/',
        pipeline=[
            dict(type='LoadImageFromFile'),
            dict(type='LoadAnnotations', with_bbox=True, with_mask=True),
            dict(type='Resize', img_scale=(1333, 800), keep_ratio=True),
            dict(type='RandomFlip', flip_ratio=0.5),
            dict(
                type='Normalize',
                mean=[123.675, 116.28, 103.53],
                std=[58.395, 57.12, 57.375],
                to_rgb=True),
            dict(type='Pad', size_divisor=32),
            dict(type='DefaultFormatBundle'),
            dict(
                type='Collect',
                keys=['img', 'gt_bboxes', 'gt_labels', 'gt_masks'])
        ]),
    val=dict(
        type='CocoDataset',
        ann_file='data/coco/annotations/instances_val2017.json',
        img_prefix='data/coco/val2017/',
        pipeline=[
            dict(type='LoadImageFromFile'),
            dict(
                type='MultiScaleFlipAug',
                img_scale=(1333, 800),
                flip=False,
                transforms=[
                    dict(type='Resize', keep_ratio=True),
                    dict(type='RandomFlip'),
                    dict(
                        type='Normalize',
                        mean=[123.675, 116.28, 103.53],
                        std=[58.395, 57.12, 57.375],
                        to_rgb=True),
                    dict(type='Pad', size_divisor=32),
                    dict(type='ImageToTensor', keys=['img']),
                    dict(type='Collect', keys=['img'])
                ])
        ]),
    test=dict(
        type='CocoDataset',
        ann_file='data/coco/annotations/instances_val2017.json',
        img_prefix='data/coco/val2017/',
        pipeline=[
            dict(type='LoadImageFromFile'),
            dict(
                type='MultiScaleFlipAug',
                img_scale=(1333, 800),
                flip=False,
                transforms=[
                    dict(type='Resize', keep_ratio=True),
                    dict(type='RandomFlip'),
                    dict(
                        type='Normalize',
                        mean=[123.675, 116.28, 103.53],
                        std=[58.395, 57.12, 57.375],
                        to_rgb=True),
                    dict(type='Pad', size_divisor=32),
                    dict(type='ImageToTensor', keys=['img']),
                    dict(type='Collect', keys=['img'])
                ])
        ]))
evaluation = dict(metric=['bbox', 'segm'], interval=1, save_best=None)
optimizer = dict(
    type='AdamW',
    lr=0.0002,
    betas=(0.9, 0.999),
    weight_decay=0.05,
    constructor='CustomLayerDecayOptimizerConstructorMMDet',
    paramwise_cfg=dict(
        num_layers=12, layer_decay_rate=0.8, skip_stride=[1, 3]))
optimizer_config = dict(grad_clip=None)
lr_config = dict(
    policy='step',
    warmup='linear',
    warmup_iters=500,
    warmup_ratio=0.001,
    step=[8, 11])
runner = dict(type='EpochBasedRunner', max_epochs=12)
checkpoint_config = dict(interval=1, deepspeed=True, max_keep_ckpts=1)
log_config = dict(
    interval=50,
    hooks=[
        dict(
            type='MMDetWandbHook',
            init_kwargs=dict(
                project='piip_detseg_0821',
                name=
                '0827_4j_mask_rcnn_convnext-tsb_1024_672_448_regular-fpn-merge_cz',
                tags=[],
                entity='hao-lab'),
            interval=50,
            log_checkpoint=False,
            log_checkpoint_metadata=False,
            num_eval_images=0)
    ])
custom_hooks = [dict(type='ToBFloat16HookMMDet', priority=49)]
dist_params = dict(backend='nccl')
log_level = 'INFO'
load_from = None
resume_from = None
workflow = [('train', 1)]
opencv_num_threads = 0
mp_start_method = 'fork'
auto_scale_lr = dict(enable=False, base_batch_size=16)
deepspeed = True
deepspeed_config = 'zero_configs/adam_zero1_bf16.json'
custom_imports = dict(
    imports=['mmdet.mmcv_custom'], allow_failed_imports=False)
work_dir = './work_dirs/0827_4j_mask_rcnn_convnext-tsb_1024_672_448_regular-fpn-merge_cz'
auto_resume = False
gpu_ids = range(0, 8)

2024-08-27 23:30:55,572 - mmdet - INFO - Set random seed to 1895709125, deterministic: False
2024-08-27 23:32:15,321 - mmdet - INFO - initialize FPN with init_cfg {'type': 'Xavier', 'layer': 'Conv2d', 'distribution': 'uniform'}
2024-08-27 23:32:15,894 - mmdet - INFO - initialize RPNHead with init_cfg {'type': 'Normal', 'layer': 'Conv2d', 'std': 0.01}
2024-08-27 23:32:15,967 - mmdet - INFO - initialize Shared2FCBBoxHead with init_cfg [{'type': 'Normal', 'std': 0.01, 'override': {'name': 'fc_cls'}}, {'type': 'Normal', 'std': 0.001, 'override': {'name': 'fc_reg'}}, {'type': 'Xavier', 'distribution': 'uniform', 'override': [{'name': 'shared_fcs'}, {'name': 'cls_fcs'}, {'name': 'reg_fcs'}]}]
Name of parameter - Initialization information

backbone.w1 - torch.Size([]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.w2 - torch.Size([]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.w3 - torch.Size([]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_0_w1 - torch.Size([]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_0_w2 - torch.Size([]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_0_w3 - torch.Size([]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_1_w1 - torch.Size([]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_1_w2 - torch.Size([]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_1_w3 - torch.Size([]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_10_w1 - torch.Size([]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_10_w2 - torch.Size([]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_10_w3 - torch.Size([]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.embeddings.patch_embeddings.weight - torch.Size([128, 3, 4, 4]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.embeddings.patch_embeddings.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.embeddings.layernorm.weight - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.embeddings.layernorm.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.0.layer_scale_parameter - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.0.dwconv.weight - torch.Size([128, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.0.dwconv.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.0.layernorm.weight - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.0.layernorm.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.0.pwconv1.weight - torch.Size([512, 128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.0.pwconv1.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.0.pwconv2.weight - torch.Size([128, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.0.pwconv2.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.1.layer_scale_parameter - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.1.dwconv.weight - torch.Size([128, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.1.dwconv.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.1.layernorm.weight - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.1.layernorm.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.1.pwconv1.weight - torch.Size([512, 128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.1.pwconv1.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.1.pwconv2.weight - torch.Size([128, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.1.pwconv2.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.2.layer_scale_parameter - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.2.dwconv.weight - torch.Size([128, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.2.dwconv.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.2.layernorm.weight - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.2.layernorm.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.2.pwconv1.weight - torch.Size([512, 128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.2.pwconv1.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.2.pwconv2.weight - torch.Size([128, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.0.layers.2.pwconv2.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.downsampling_layer.0.weight - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.downsampling_layer.0.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.downsampling_layer.1.weight - torch.Size([256, 128, 2, 2]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.downsampling_layer.1.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.0.layer_scale_parameter - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.0.dwconv.weight - torch.Size([256, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.0.dwconv.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.0.layernorm.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.0.layernorm.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.0.pwconv1.weight - torch.Size([1024, 256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.0.pwconv1.bias - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.0.pwconv2.weight - torch.Size([256, 1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.0.pwconv2.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.1.layer_scale_parameter - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.1.dwconv.weight - torch.Size([256, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.1.dwconv.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.1.layernorm.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.1.layernorm.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.1.pwconv1.weight - torch.Size([1024, 256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.1.pwconv1.bias - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.1.pwconv2.weight - torch.Size([256, 1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.1.pwconv2.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.2.layer_scale_parameter - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.2.dwconv.weight - torch.Size([256, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.2.dwconv.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.2.layernorm.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.2.layernorm.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.2.pwconv1.weight - torch.Size([1024, 256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.2.pwconv1.bias - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.2.pwconv2.weight - torch.Size([256, 1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.1.layers.2.pwconv2.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.downsampling_layer.0.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.downsampling_layer.0.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.downsampling_layer.1.weight - torch.Size([512, 256, 2, 2]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.downsampling_layer.1.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.0.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.0.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.0.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.0.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.0.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.0.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.0.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.0.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.0.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.1.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.1.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.1.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.1.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.1.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.1.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.1.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.1.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.1.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.2.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.2.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.2.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.2.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.2.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.2.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.2.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.2.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.2.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.3.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.3.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.3.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.3.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.3.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.3.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.3.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.3.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.3.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.4.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.4.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.4.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.4.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.4.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.4.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.4.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.4.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.4.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.5.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.5.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.5.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.5.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.5.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.5.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.5.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.5.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.5.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.6.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.6.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.6.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.6.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.6.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.6.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.6.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.6.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.6.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.7.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.7.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.7.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.7.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.7.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.7.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.7.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.7.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.7.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.8.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.8.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.8.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.8.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.8.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.8.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.8.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.8.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.8.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.9.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.9.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.9.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.9.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.9.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.9.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.9.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.9.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.9.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.10.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.10.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.10.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.10.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.10.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.10.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.10.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.10.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.10.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.11.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.11.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.11.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.11.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.11.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.11.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.11.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.11.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.11.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.12.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.12.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.12.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.12.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.12.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.12.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.12.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.12.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.12.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.13.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.13.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.13.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.13.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.13.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.13.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.13.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.13.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.13.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.14.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.14.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.14.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.14.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.14.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.14.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.14.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.14.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.14.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.15.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.15.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.15.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.15.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.15.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.15.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.15.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.15.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.15.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.16.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.16.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.16.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.16.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.16.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.16.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.16.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.16.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.16.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.17.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.17.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.17.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.17.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.17.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.17.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.17.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.17.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.17.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.18.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.18.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.18.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.18.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.18.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.18.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.18.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.18.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.18.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.19.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.19.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.19.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.19.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.19.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.19.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.19.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.19.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.19.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.20.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.20.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.20.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.20.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.20.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.20.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.20.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.20.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.20.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.21.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.21.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.21.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.21.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.21.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.21.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.21.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.21.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.21.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.22.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.22.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.22.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.22.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.22.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.22.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.22.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.22.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.22.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.23.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.23.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.23.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.23.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.23.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.23.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.23.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.23.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.23.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.24.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.24.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.24.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.24.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.24.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.24.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.24.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.24.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.24.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.25.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.25.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.25.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.25.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.25.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.25.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.25.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.25.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.25.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.26.layer_scale_parameter - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.26.dwconv.weight - torch.Size([512, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.26.dwconv.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.26.layernorm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.26.layernorm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.26.pwconv1.weight - torch.Size([2048, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.26.pwconv1.bias - torch.Size([2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.26.pwconv2.weight - torch.Size([512, 2048]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.2.layers.26.pwconv2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.downsampling_layer.0.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.downsampling_layer.0.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.downsampling_layer.1.weight - torch.Size([1024, 512, 2, 2]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.downsampling_layer.1.bias - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.0.layer_scale_parameter - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.0.dwconv.weight - torch.Size([1024, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.0.dwconv.bias - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.0.layernorm.weight - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.0.layernorm.bias - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.0.pwconv1.weight - torch.Size([4096, 1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.0.pwconv1.bias - torch.Size([4096]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.0.pwconv2.weight - torch.Size([1024, 4096]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.0.pwconv2.bias - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.1.layer_scale_parameter - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.1.dwconv.weight - torch.Size([1024, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.1.dwconv.bias - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.1.layernorm.weight - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.1.layernorm.bias - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.1.pwconv1.weight - torch.Size([4096, 1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.1.pwconv1.bias - torch.Size([4096]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.1.pwconv2.weight - torch.Size([1024, 4096]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.1.pwconv2.bias - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.2.layer_scale_parameter - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.2.dwconv.weight - torch.Size([1024, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.2.dwconv.bias - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.2.layernorm.weight - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.2.layernorm.bias - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.2.pwconv1.weight - torch.Size([4096, 1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.2.pwconv1.bias - torch.Size([4096]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.2.pwconv2.weight - torch.Size([1024, 4096]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.encoder.stages.3.layers.2.pwconv2.bias - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.layernorm.weight - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch1.convnext_model.layernorm.bias - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.embeddings.patch_embeddings.weight - torch.Size([96, 3, 4, 4]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.embeddings.patch_embeddings.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.embeddings.layernorm.weight - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.embeddings.layernorm.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.0.layer_scale_parameter - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.0.dwconv.weight - torch.Size([96, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.0.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.0.layernorm.weight - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.0.layernorm.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.0.pwconv1.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.0.pwconv1.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.0.pwconv2.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.0.pwconv2.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.1.layer_scale_parameter - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.1.dwconv.weight - torch.Size([96, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.1.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.1.layernorm.weight - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.1.layernorm.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.1.pwconv1.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.1.pwconv1.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.1.pwconv2.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.1.pwconv2.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.2.layer_scale_parameter - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.2.dwconv.weight - torch.Size([96, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.2.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.2.layernorm.weight - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.2.layernorm.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.2.pwconv1.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.2.pwconv1.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.2.pwconv2.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.0.layers.2.pwconv2.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.downsampling_layer.0.weight - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.downsampling_layer.0.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.downsampling_layer.1.weight - torch.Size([192, 96, 2, 2]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.downsampling_layer.1.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.0.layer_scale_parameter - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.0.dwconv.weight - torch.Size([192, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.0.dwconv.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.0.layernorm.weight - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.0.layernorm.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.0.pwconv1.weight - torch.Size([768, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.0.pwconv1.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.0.pwconv2.weight - torch.Size([192, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.0.pwconv2.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.1.layer_scale_parameter - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.1.dwconv.weight - torch.Size([192, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.1.dwconv.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.1.layernorm.weight - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.1.layernorm.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.1.pwconv1.weight - torch.Size([768, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.1.pwconv1.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.1.pwconv2.weight - torch.Size([192, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.1.pwconv2.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.2.layer_scale_parameter - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.2.dwconv.weight - torch.Size([192, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.2.dwconv.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.2.layernorm.weight - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.2.layernorm.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.2.pwconv1.weight - torch.Size([768, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.2.pwconv1.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.2.pwconv2.weight - torch.Size([192, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.1.layers.2.pwconv2.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.downsampling_layer.0.weight - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.downsampling_layer.0.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.downsampling_layer.1.weight - torch.Size([384, 192, 2, 2]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.downsampling_layer.1.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.0.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.0.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.0.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.0.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.0.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.0.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.0.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.0.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.0.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.1.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.1.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.1.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.1.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.1.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.1.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.1.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.1.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.1.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.2.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.2.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.2.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.2.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.2.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.2.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.2.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.2.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.2.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.3.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.3.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.3.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.3.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.3.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.3.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.3.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.3.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.3.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.4.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.4.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.4.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.4.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.4.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.4.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.4.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.4.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.4.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.5.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.5.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.5.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.5.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.5.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.5.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.5.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.5.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.5.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.6.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.6.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.6.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.6.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.6.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.6.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.6.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.6.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.6.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.7.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.7.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.7.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.7.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.7.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.7.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.7.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.7.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.7.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.8.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.8.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.8.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.8.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.8.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.8.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.8.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.8.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.8.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.9.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.9.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.9.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.9.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.9.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.9.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.9.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.9.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.9.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.10.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.10.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.10.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.10.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.10.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.10.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.10.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.10.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.10.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.11.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.11.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.11.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.11.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.11.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.11.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.11.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.11.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.11.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.12.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.12.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.12.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.12.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.12.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.12.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.12.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.12.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.12.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.13.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.13.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.13.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.13.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.13.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.13.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.13.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.13.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.13.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.14.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.14.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.14.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.14.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.14.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.14.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.14.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.14.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.14.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.15.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.15.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.15.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.15.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.15.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.15.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.15.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.15.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.15.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.16.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.16.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.16.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.16.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.16.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.16.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.16.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.16.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.16.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.17.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.17.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.17.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.17.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.17.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.17.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.17.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.17.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.17.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.18.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.18.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.18.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.18.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.18.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.18.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.18.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.18.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.18.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.19.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.19.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.19.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.19.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.19.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.19.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.19.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.19.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.19.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.20.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.20.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.20.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.20.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.20.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.20.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.20.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.20.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.20.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.21.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.21.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.21.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.21.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.21.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.21.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.21.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.21.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.21.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.22.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.22.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.22.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.22.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.22.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.22.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.22.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.22.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.22.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.23.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.23.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.23.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.23.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.23.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.23.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.23.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.23.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.23.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.24.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.24.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.24.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.24.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.24.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.24.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.24.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.24.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.24.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.25.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.25.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.25.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.25.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.25.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.25.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.25.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.25.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.25.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.26.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.26.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.26.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.26.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.26.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.26.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.26.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.26.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.2.layers.26.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.downsampling_layer.0.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.downsampling_layer.0.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.downsampling_layer.1.weight - torch.Size([768, 384, 2, 2]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.downsampling_layer.1.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.0.layer_scale_parameter - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.0.dwconv.weight - torch.Size([768, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.0.dwconv.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.0.layernorm.weight - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.0.layernorm.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.0.pwconv1.weight - torch.Size([3072, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.0.pwconv1.bias - torch.Size([3072]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.0.pwconv2.weight - torch.Size([768, 3072]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.0.pwconv2.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.1.layer_scale_parameter - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.1.dwconv.weight - torch.Size([768, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.1.dwconv.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.1.layernorm.weight - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.1.layernorm.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.1.pwconv1.weight - torch.Size([3072, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.1.pwconv1.bias - torch.Size([3072]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.1.pwconv2.weight - torch.Size([768, 3072]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.1.pwconv2.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.2.layer_scale_parameter - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.2.dwconv.weight - torch.Size([768, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.2.dwconv.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.2.layernorm.weight - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.2.layernorm.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.2.pwconv1.weight - torch.Size([3072, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.2.pwconv1.bias - torch.Size([3072]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.2.pwconv2.weight - torch.Size([768, 3072]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.encoder.stages.3.layers.2.pwconv2.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.layernorm.weight - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch2.convnext_model.layernorm.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.embeddings.patch_embeddings.weight - torch.Size([96, 3, 4, 4]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.embeddings.patch_embeddings.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.embeddings.layernorm.weight - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.embeddings.layernorm.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.0.layer_scale_parameter - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.0.dwconv.weight - torch.Size([96, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.0.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.0.layernorm.weight - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.0.layernorm.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.0.pwconv1.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.0.pwconv1.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.0.pwconv2.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.0.pwconv2.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.1.layer_scale_parameter - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.1.dwconv.weight - torch.Size([96, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.1.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.1.layernorm.weight - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.1.layernorm.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.1.pwconv1.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.1.pwconv1.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.1.pwconv2.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.1.pwconv2.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.2.layer_scale_parameter - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.2.dwconv.weight - torch.Size([96, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.2.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.2.layernorm.weight - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.2.layernorm.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.2.pwconv1.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.2.pwconv1.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.2.pwconv2.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.0.layers.2.pwconv2.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.downsampling_layer.0.weight - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.downsampling_layer.0.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.downsampling_layer.1.weight - torch.Size([192, 96, 2, 2]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.downsampling_layer.1.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.0.layer_scale_parameter - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.0.dwconv.weight - torch.Size([192, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.0.dwconv.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.0.layernorm.weight - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.0.layernorm.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.0.pwconv1.weight - torch.Size([768, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.0.pwconv1.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.0.pwconv2.weight - torch.Size([192, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.0.pwconv2.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.1.layer_scale_parameter - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.1.dwconv.weight - torch.Size([192, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.1.dwconv.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.1.layernorm.weight - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.1.layernorm.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.1.pwconv1.weight - torch.Size([768, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.1.pwconv1.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.1.pwconv2.weight - torch.Size([192, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.1.pwconv2.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.2.layer_scale_parameter - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.2.dwconv.weight - torch.Size([192, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.2.dwconv.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.2.layernorm.weight - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.2.layernorm.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.2.pwconv1.weight - torch.Size([768, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.2.pwconv1.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.2.pwconv2.weight - torch.Size([192, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.1.layers.2.pwconv2.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.downsampling_layer.0.weight - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.downsampling_layer.0.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.downsampling_layer.1.weight - torch.Size([384, 192, 2, 2]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.downsampling_layer.1.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.0.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.0.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.0.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.0.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.0.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.0.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.0.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.0.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.0.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.1.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.1.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.1.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.1.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.1.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.1.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.1.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.1.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.1.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.2.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.2.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.2.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.2.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.2.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.2.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.2.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.2.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.2.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.3.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.3.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.3.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.3.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.3.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.3.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.3.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.3.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.3.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.4.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.4.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.4.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.4.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.4.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.4.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.4.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.4.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.4.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.5.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.5.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.5.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.5.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.5.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.5.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.5.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.5.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.5.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.6.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.6.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.6.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.6.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.6.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.6.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.6.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.6.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.6.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.7.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.7.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.7.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.7.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.7.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.7.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.7.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.7.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.7.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.8.layer_scale_parameter - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.8.dwconv.weight - torch.Size([384, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.8.dwconv.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.8.layernorm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.8.layernorm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.8.pwconv1.weight - torch.Size([1536, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.8.pwconv1.bias - torch.Size([1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.8.pwconv2.weight - torch.Size([384, 1536]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.2.layers.8.pwconv2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.downsampling_layer.0.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.downsampling_layer.0.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.downsampling_layer.1.weight - torch.Size([768, 384, 2, 2]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.downsampling_layer.1.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.0.layer_scale_parameter - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.0.dwconv.weight - torch.Size([768, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.0.dwconv.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.0.layernorm.weight - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.0.layernorm.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.0.pwconv1.weight - torch.Size([3072, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.0.pwconv1.bias - torch.Size([3072]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.0.pwconv2.weight - torch.Size([768, 3072]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.0.pwconv2.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.1.layer_scale_parameter - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.1.dwconv.weight - torch.Size([768, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.1.dwconv.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.1.layernorm.weight - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.1.layernorm.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.1.pwconv1.weight - torch.Size([3072, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.1.pwconv1.bias - torch.Size([3072]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.1.pwconv2.weight - torch.Size([768, 3072]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.1.pwconv2.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.2.layer_scale_parameter - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.2.dwconv.weight - torch.Size([768, 1, 7, 7]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.2.dwconv.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.2.layernorm.weight - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.2.layernorm.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.2.pwconv1.weight - torch.Size([3072, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.2.pwconv1.bias - torch.Size([3072]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.2.pwconv2.weight - torch.Size([768, 3072]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.encoder.stages.3.layers.2.pwconv2.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.layernorm.weight - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.branch3.convnext_model.layernorm.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch2to1_proj.weight - torch.Size([128, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch2to1_proj.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch1to2_proj.weight - torch.Size([96, 128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch1to2_proj.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch2to1_injector.ca_gamma - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch2to1_injector.cffn_gamma - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch2to1_injector.query_norm.weight - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch2to1_injector.query_norm.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch2to1_injector.feat_norm.weight - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch2to1_injector.feat_norm.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch2to1_injector.attn.output_proj.weight - torch.Size([128, 64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch2to1_injector.attn.output_proj.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch2to1_injector.attn.value_proj.weight - torch.Size([64, 128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch2to1_injector.attn.value_proj.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch2to1_injector.ffn.fc1.weight - torch.Size([32, 128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch2to1_injector.ffn.fc1.bias - torch.Size([32]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([32, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([32]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch2to1_injector.ffn.fc2.weight - torch.Size([128, 32]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch2to1_injector.ffn.fc2.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch2to1_injector.ffn_norm.weight - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch2to1_injector.ffn_norm.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch1to2_injector.ca_gamma - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch1to2_injector.cffn_gamma - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch1to2_injector.query_norm.weight - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch1to2_injector.query_norm.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch1to2_injector.feat_norm.weight - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch1to2_injector.feat_norm.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch1to2_injector.attn.output_proj.weight - torch.Size([96, 48]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch1to2_injector.attn.output_proj.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch1to2_injector.attn.value_proj.weight - torch.Size([48, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch1to2_injector.attn.value_proj.bias - torch.Size([48]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch1to2_injector.ffn.fc1.weight - torch.Size([24, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch1to2_injector.ffn.fc1.bias - torch.Size([24]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([24, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([24]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch1to2_injector.ffn.fc2.weight - torch.Size([96, 24]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch1to2_injector.ffn.fc2.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch1to2_injector.ffn_norm.weight - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_12.branch1to2_injector.ffn_norm.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch2to1_proj.weight - torch.Size([96, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch2to1_proj.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch1to2_proj.weight - torch.Size([96, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch1to2_proj.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch2to1_injector.ca_gamma - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch2to1_injector.cffn_gamma - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch2to1_injector.query_norm.weight - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch2to1_injector.query_norm.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch2to1_injector.feat_norm.weight - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch2to1_injector.feat_norm.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch2to1_injector.attn.output_proj.weight - torch.Size([96, 48]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch2to1_injector.attn.output_proj.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch2to1_injector.attn.value_proj.weight - torch.Size([48, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch2to1_injector.attn.value_proj.bias - torch.Size([48]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch2to1_injector.ffn.fc1.weight - torch.Size([24, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch2to1_injector.ffn.fc1.bias - torch.Size([24]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([24, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([24]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch2to1_injector.ffn.fc2.weight - torch.Size([96, 24]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch2to1_injector.ffn.fc2.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch2to1_injector.ffn_norm.weight - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch2to1_injector.ffn_norm.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch1to2_injector.ca_gamma - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch1to2_injector.cffn_gamma - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch1to2_injector.query_norm.weight - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch1to2_injector.query_norm.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch1to2_injector.feat_norm.weight - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch1to2_injector.feat_norm.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch1to2_injector.attn.output_proj.weight - torch.Size([96, 48]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch1to2_injector.attn.output_proj.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch1to2_injector.attn.value_proj.weight - torch.Size([48, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch1to2_injector.attn.value_proj.bias - torch.Size([48]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch1to2_injector.ffn.fc1.weight - torch.Size([24, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch1to2_injector.ffn.fc1.bias - torch.Size([24]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([24, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([24]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch1to2_injector.ffn.fc2.weight - torch.Size([96, 24]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch1to2_injector.ffn.fc2.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch1to2_injector.ffn_norm.weight - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.0.interaction_units_23.branch1to2_injector.ffn_norm.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch2to1_proj.weight - torch.Size([256, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch2to1_proj.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch1to2_proj.weight - torch.Size([192, 256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch1to2_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch2to1_injector.ca_gamma - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch2to1_injector.cffn_gamma - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch2to1_injector.query_norm.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch2to1_injector.query_norm.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch2to1_injector.feat_norm.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch2to1_injector.feat_norm.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch2to1_injector.attn.output_proj.weight - torch.Size([256, 128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch2to1_injector.attn.output_proj.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch2to1_injector.attn.value_proj.weight - torch.Size([128, 256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch2to1_injector.attn.value_proj.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch2to1_injector.ffn.fc1.weight - torch.Size([64, 256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch2to1_injector.ffn.fc1.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([64, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch2to1_injector.ffn.fc2.weight - torch.Size([256, 64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch2to1_injector.ffn.fc2.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch2to1_injector.ffn_norm.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch2to1_injector.ffn_norm.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch1to2_injector.ca_gamma - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch1to2_injector.cffn_gamma - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch1to2_injector.query_norm.weight - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch1to2_injector.query_norm.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch1to2_injector.feat_norm.weight - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch1to2_injector.feat_norm.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch1to2_injector.attn.output_proj.weight - torch.Size([192, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch1to2_injector.attn.output_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch1to2_injector.attn.value_proj.weight - torch.Size([96, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch1to2_injector.attn.value_proj.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch1to2_injector.ffn.fc1.weight - torch.Size([48, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch1to2_injector.ffn.fc1.bias - torch.Size([48]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([48, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([48]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch1to2_injector.ffn.fc2.weight - torch.Size([192, 48]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch1to2_injector.ffn.fc2.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch1to2_injector.ffn_norm.weight - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_12.branch1to2_injector.ffn_norm.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch2to1_proj.weight - torch.Size([192, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch2to1_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch1to2_proj.weight - torch.Size([192, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch1to2_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch2to1_injector.ca_gamma - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch2to1_injector.cffn_gamma - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch2to1_injector.query_norm.weight - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch2to1_injector.query_norm.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch2to1_injector.feat_norm.weight - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch2to1_injector.feat_norm.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch2to1_injector.attn.output_proj.weight - torch.Size([192, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch2to1_injector.attn.output_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch2to1_injector.attn.value_proj.weight - torch.Size([96, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch2to1_injector.attn.value_proj.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch2to1_injector.ffn.fc1.weight - torch.Size([48, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch2to1_injector.ffn.fc1.bias - torch.Size([48]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([48, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([48]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch2to1_injector.ffn.fc2.weight - torch.Size([192, 48]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch2to1_injector.ffn.fc2.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch2to1_injector.ffn_norm.weight - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch2to1_injector.ffn_norm.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch1to2_injector.ca_gamma - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch1to2_injector.cffn_gamma - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch1to2_injector.query_norm.weight - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch1to2_injector.query_norm.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch1to2_injector.feat_norm.weight - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch1to2_injector.feat_norm.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch1to2_injector.attn.output_proj.weight - torch.Size([192, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch1to2_injector.attn.output_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch1to2_injector.attn.value_proj.weight - torch.Size([96, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch1to2_injector.attn.value_proj.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch1to2_injector.ffn.fc1.weight - torch.Size([48, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch1to2_injector.ffn.fc1.bias - torch.Size([48]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([48, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([48]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch1to2_injector.ffn.fc2.weight - torch.Size([192, 48]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch1to2_injector.ffn.fc2.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch1to2_injector.ffn_norm.weight - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.1.interaction_units_23.branch1to2_injector.ffn_norm.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch2to1_proj.weight - torch.Size([512, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch2to1_proj.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch1to2_proj.weight - torch.Size([384, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch1to2_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch2to1_injector.ca_gamma - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch2to1_injector.cffn_gamma - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch2to1_injector.query_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch2to1_injector.query_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch2to1_injector.feat_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch2to1_injector.feat_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch2to1_injector.attn.output_proj.weight - torch.Size([512, 256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch2to1_injector.attn.output_proj.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch2to1_injector.attn.value_proj.weight - torch.Size([256, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch2to1_injector.attn.value_proj.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch2to1_injector.ffn.fc1.weight - torch.Size([128, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch2to1_injector.ffn.fc1.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([128, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch2to1_injector.ffn.fc2.weight - torch.Size([512, 128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch2to1_injector.ffn.fc2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch2to1_injector.ffn_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch2to1_injector.ffn_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch1to2_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch1to2_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch1to2_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch1to2_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch1to2_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch1to2_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch1to2_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_12.branch1to2_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch2to1_proj.weight - torch.Size([384, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch2to1_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch1to2_proj.weight - torch.Size([384, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch1to2_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch2to1_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch2to1_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch2to1_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch2to1_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch2to1_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch2to1_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch2to1_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch2to1_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch2to1_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch2to1_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch2to1_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch2to1_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch2to1_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch2to1_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch2to1_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch2to1_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch1to2_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch1to2_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch1to2_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch1to2_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch1to2_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch1to2_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch1to2_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.2.interaction_units_23.branch1to2_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch2to1_proj.weight - torch.Size([512, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch2to1_proj.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch1to2_proj.weight - torch.Size([384, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch1to2_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch2to1_injector.ca_gamma - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch2to1_injector.cffn_gamma - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch2to1_injector.query_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch2to1_injector.query_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch2to1_injector.feat_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch2to1_injector.feat_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch2to1_injector.attn.output_proj.weight - torch.Size([512, 256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch2to1_injector.attn.output_proj.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch2to1_injector.attn.value_proj.weight - torch.Size([256, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch2to1_injector.attn.value_proj.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch2to1_injector.ffn.fc1.weight - torch.Size([128, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch2to1_injector.ffn.fc1.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([128, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch2to1_injector.ffn.fc2.weight - torch.Size([512, 128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch2to1_injector.ffn.fc2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch2to1_injector.ffn_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch2to1_injector.ffn_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch1to2_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch1to2_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch1to2_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch1to2_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch1to2_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch1to2_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch1to2_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_12.branch1to2_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch2to1_proj.weight - torch.Size([384, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch2to1_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch1to2_proj.weight - torch.Size([384, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch1to2_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch2to1_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch2to1_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch2to1_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch2to1_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch2to1_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch2to1_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch2to1_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch2to1_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch2to1_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch2to1_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch2to1_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch2to1_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch2to1_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch2to1_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch2to1_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch2to1_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch1to2_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch1to2_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch1to2_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch1to2_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch1to2_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch1to2_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch1to2_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.3.interaction_units_23.branch1to2_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch2to1_proj.weight - torch.Size([512, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch2to1_proj.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch1to2_proj.weight - torch.Size([384, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch1to2_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch2to1_injector.ca_gamma - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch2to1_injector.cffn_gamma - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch2to1_injector.query_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch2to1_injector.query_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch2to1_injector.feat_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch2to1_injector.feat_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch2to1_injector.attn.output_proj.weight - torch.Size([512, 256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch2to1_injector.attn.output_proj.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch2to1_injector.attn.value_proj.weight - torch.Size([256, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch2to1_injector.attn.value_proj.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch2to1_injector.ffn.fc1.weight - torch.Size([128, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch2to1_injector.ffn.fc1.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([128, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch2to1_injector.ffn.fc2.weight - torch.Size([512, 128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch2to1_injector.ffn.fc2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch2to1_injector.ffn_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch2to1_injector.ffn_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch1to2_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch1to2_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch1to2_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch1to2_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch1to2_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch1to2_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch1to2_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_12.branch1to2_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch2to1_proj.weight - torch.Size([384, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch2to1_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch1to2_proj.weight - torch.Size([384, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch1to2_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch2to1_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch2to1_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch2to1_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch2to1_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch2to1_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch2to1_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch2to1_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch2to1_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch2to1_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch2to1_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch2to1_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch2to1_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch2to1_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch2to1_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch2to1_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch2to1_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch1to2_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch1to2_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch1to2_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch1to2_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch1to2_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch1to2_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch1to2_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.4.interaction_units_23.branch1to2_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch2to1_proj.weight - torch.Size([512, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch2to1_proj.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch1to2_proj.weight - torch.Size([384, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch1to2_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch2to1_injector.ca_gamma - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch2to1_injector.cffn_gamma - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch2to1_injector.query_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch2to1_injector.query_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch2to1_injector.feat_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch2to1_injector.feat_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch2to1_injector.attn.output_proj.weight - torch.Size([512, 256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch2to1_injector.attn.output_proj.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch2to1_injector.attn.value_proj.weight - torch.Size([256, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch2to1_injector.attn.value_proj.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch2to1_injector.ffn.fc1.weight - torch.Size([128, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch2to1_injector.ffn.fc1.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([128, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch2to1_injector.ffn.fc2.weight - torch.Size([512, 128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch2to1_injector.ffn.fc2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch2to1_injector.ffn_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch2to1_injector.ffn_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch1to2_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch1to2_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch1to2_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch1to2_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch1to2_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch1to2_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch1to2_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_12.branch1to2_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch2to1_proj.weight - torch.Size([384, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch2to1_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch1to2_proj.weight - torch.Size([384, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch1to2_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch2to1_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch2to1_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch2to1_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch2to1_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch2to1_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch2to1_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch2to1_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch2to1_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch2to1_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch2to1_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch2to1_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch2to1_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch2to1_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch2to1_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch2to1_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch2to1_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch1to2_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch1to2_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch1to2_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch1to2_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch1to2_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch1to2_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch1to2_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.5.interaction_units_23.branch1to2_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch2to1_proj.weight - torch.Size([512, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch2to1_proj.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch1to2_proj.weight - torch.Size([384, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch1to2_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch2to1_injector.ca_gamma - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch2to1_injector.cffn_gamma - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch2to1_injector.query_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch2to1_injector.query_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch2to1_injector.feat_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch2to1_injector.feat_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch2to1_injector.attn.output_proj.weight - torch.Size([512, 256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch2to1_injector.attn.output_proj.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch2to1_injector.attn.value_proj.weight - torch.Size([256, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch2to1_injector.attn.value_proj.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch2to1_injector.ffn.fc1.weight - torch.Size([128, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch2to1_injector.ffn.fc1.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([128, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch2to1_injector.ffn.fc2.weight - torch.Size([512, 128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch2to1_injector.ffn.fc2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch2to1_injector.ffn_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch2to1_injector.ffn_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch1to2_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch1to2_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch1to2_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch1to2_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch1to2_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch1to2_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch1to2_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_12.branch1to2_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch2to1_proj.weight - torch.Size([384, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch2to1_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch1to2_proj.weight - torch.Size([384, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch1to2_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch2to1_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch2to1_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch2to1_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch2to1_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch2to1_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch2to1_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch2to1_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch2to1_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch2to1_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch2to1_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch2to1_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch2to1_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch2to1_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch2to1_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch2to1_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch2to1_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch1to2_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch1to2_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch1to2_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch1to2_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch1to2_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch1to2_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch1to2_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.6.interaction_units_23.branch1to2_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch2to1_proj.weight - torch.Size([512, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch2to1_proj.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch1to2_proj.weight - torch.Size([384, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch1to2_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch2to1_injector.ca_gamma - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch2to1_injector.cffn_gamma - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch2to1_injector.query_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch2to1_injector.query_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch2to1_injector.feat_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch2to1_injector.feat_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch2to1_injector.attn.output_proj.weight - torch.Size([512, 256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch2to1_injector.attn.output_proj.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch2to1_injector.attn.value_proj.weight - torch.Size([256, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch2to1_injector.attn.value_proj.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch2to1_injector.ffn.fc1.weight - torch.Size([128, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch2to1_injector.ffn.fc1.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([128, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch2to1_injector.ffn.fc2.weight - torch.Size([512, 128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch2to1_injector.ffn.fc2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch2to1_injector.ffn_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch2to1_injector.ffn_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch1to2_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch1to2_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch1to2_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch1to2_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch1to2_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch1to2_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch1to2_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_12.branch1to2_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch2to1_proj.weight - torch.Size([384, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch2to1_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch1to2_proj.weight - torch.Size([384, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch1to2_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch2to1_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch2to1_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch2to1_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch2to1_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch2to1_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch2to1_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch2to1_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch2to1_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch2to1_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch2to1_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch2to1_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch2to1_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch2to1_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch2to1_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch2to1_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch2to1_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch1to2_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch1to2_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch1to2_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch1to2_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch1to2_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch1to2_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch1to2_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.7.interaction_units_23.branch1to2_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch2to1_proj.weight - torch.Size([512, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch2to1_proj.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch1to2_proj.weight - torch.Size([384, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch1to2_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch2to1_injector.ca_gamma - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch2to1_injector.cffn_gamma - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch2to1_injector.query_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch2to1_injector.query_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch2to1_injector.feat_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch2to1_injector.feat_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch2to1_injector.attn.output_proj.weight - torch.Size([512, 256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch2to1_injector.attn.output_proj.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch2to1_injector.attn.value_proj.weight - torch.Size([256, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch2to1_injector.attn.value_proj.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch2to1_injector.ffn.fc1.weight - torch.Size([128, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch2to1_injector.ffn.fc1.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([128, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch2to1_injector.ffn.fc2.weight - torch.Size([512, 128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch2to1_injector.ffn.fc2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch2to1_injector.ffn_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch2to1_injector.ffn_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch1to2_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch1to2_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch1to2_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch1to2_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch1to2_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch1to2_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch1to2_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_12.branch1to2_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch2to1_proj.weight - torch.Size([384, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch2to1_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch1to2_proj.weight - torch.Size([384, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch1to2_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch2to1_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch2to1_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch2to1_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch2to1_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch2to1_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch2to1_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch2to1_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch2to1_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch2to1_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch2to1_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch2to1_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch2to1_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch2to1_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch2to1_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch2to1_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch2to1_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch1to2_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch1to2_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch1to2_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch1to2_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch1to2_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch1to2_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch1to2_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.8.interaction_units_23.branch1to2_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch2to1_proj.weight - torch.Size([512, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch2to1_proj.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch1to2_proj.weight - torch.Size([384, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch1to2_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch2to1_injector.ca_gamma - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch2to1_injector.cffn_gamma - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch2to1_injector.query_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch2to1_injector.query_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch2to1_injector.feat_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch2to1_injector.feat_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch2to1_injector.attn.output_proj.weight - torch.Size([512, 256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch2to1_injector.attn.output_proj.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch2to1_injector.attn.value_proj.weight - torch.Size([256, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch2to1_injector.attn.value_proj.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch2to1_injector.ffn.fc1.weight - torch.Size([128, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch2to1_injector.ffn.fc1.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([128, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch2to1_injector.ffn.fc2.weight - torch.Size([512, 128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch2to1_injector.ffn.fc2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch2to1_injector.ffn_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch2to1_injector.ffn_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch1to2_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch1to2_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch1to2_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch1to2_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch1to2_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch1to2_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch1to2_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_12.branch1to2_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch2to1_proj.weight - torch.Size([384, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch2to1_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch1to2_proj.weight - torch.Size([384, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch1to2_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch2to1_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch2to1_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch2to1_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch2to1_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch2to1_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch2to1_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch2to1_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch2to1_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch2to1_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch2to1_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch2to1_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch2to1_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch2to1_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch2to1_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch2to1_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch2to1_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch1to2_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch1to2_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch1to2_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch1to2_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch1to2_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch1to2_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch1to2_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.9.interaction_units_23.branch1to2_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch2to1_proj.weight - torch.Size([512, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch2to1_proj.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch1to2_proj.weight - torch.Size([384, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch1to2_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch2to1_injector.ca_gamma - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch2to1_injector.cffn_gamma - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch2to1_injector.query_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch2to1_injector.query_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch2to1_injector.feat_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch2to1_injector.feat_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch2to1_injector.attn.output_proj.weight - torch.Size([512, 256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch2to1_injector.attn.output_proj.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch2to1_injector.attn.value_proj.weight - torch.Size([256, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch2to1_injector.attn.value_proj.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch2to1_injector.ffn.fc1.weight - torch.Size([128, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch2to1_injector.ffn.fc1.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([128, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch2to1_injector.ffn.fc2.weight - torch.Size([512, 128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch2to1_injector.ffn.fc2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch2to1_injector.ffn_norm.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch2to1_injector.ffn_norm.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch1to2_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch1to2_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch1to2_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch1to2_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch1to2_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch1to2_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch1to2_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_12.branch1to2_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch2to1_proj.weight - torch.Size([384, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch2to1_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch1to2_proj.weight - torch.Size([384, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch1to2_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch2to1_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch2to1_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch2to1_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch2to1_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch2to1_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch2to1_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch2to1_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch2to1_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch2to1_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch2to1_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch2to1_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch2to1_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch2to1_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch2to1_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch2to1_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch2to1_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch1to2_injector.ca_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch1to2_injector.cffn_gamma - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch1to2_injector.query_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch1to2_injector.query_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch1to2_injector.feat_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch1to2_injector.feat_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch1to2_injector.ffn_norm.weight - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.10.interaction_units_23.branch1to2_injector.ffn_norm.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch2to1_proj.weight - torch.Size([1024, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch2to1_proj.bias - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch1to2_proj.weight - torch.Size([768, 1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch1to2_proj.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch2to1_injector.ca_gamma - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch2to1_injector.cffn_gamma - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch2to1_injector.query_norm.weight - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch2to1_injector.query_norm.bias - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch2to1_injector.feat_norm.weight - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch2to1_injector.feat_norm.bias - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch2to1_injector.attn.output_proj.weight - torch.Size([1024, 512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch2to1_injector.attn.output_proj.bias - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch2to1_injector.attn.value_proj.weight - torch.Size([512, 1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch2to1_injector.attn.value_proj.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch2to1_injector.ffn.fc1.weight - torch.Size([256, 1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch2to1_injector.ffn.fc1.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([256, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch2to1_injector.ffn.fc2.weight - torch.Size([1024, 256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch2to1_injector.ffn.fc2.bias - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch2to1_injector.ffn_norm.weight - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch2to1_injector.ffn_norm.bias - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch1to2_injector.ca_gamma - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch1to2_injector.cffn_gamma - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch1to2_injector.query_norm.weight - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch1to2_injector.query_norm.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch1to2_injector.feat_norm.weight - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch1to2_injector.feat_norm.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch1to2_injector.attn.output_proj.weight - torch.Size([768, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch1to2_injector.attn.output_proj.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch1to2_injector.attn.value_proj.weight - torch.Size([384, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch1to2_injector.attn.value_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch1to2_injector.ffn.fc1.weight - torch.Size([192, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch1to2_injector.ffn.fc1.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch1to2_injector.ffn.fc2.weight - torch.Size([768, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch1to2_injector.ffn.fc2.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch1to2_injector.ffn_norm.weight - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_12.branch1to2_injector.ffn_norm.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch2to1_proj.weight - torch.Size([768, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch2to1_proj.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch1to2_proj.weight - torch.Size([768, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch1to2_proj.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch2to1_injector.ca_gamma - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch2to1_injector.cffn_gamma - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch2to1_injector.query_norm.weight - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch2to1_injector.query_norm.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch2to1_injector.feat_norm.weight - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch2to1_injector.feat_norm.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch2to1_injector.attn.output_proj.weight - torch.Size([768, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch2to1_injector.attn.output_proj.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch2to1_injector.attn.value_proj.weight - torch.Size([384, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch2to1_injector.attn.value_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch2to1_injector.ffn.fc1.weight - torch.Size([192, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch2to1_injector.ffn.fc1.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch2to1_injector.ffn.fc2.weight - torch.Size([768, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch2to1_injector.ffn.fc2.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch2to1_injector.ffn_norm.weight - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch2to1_injector.ffn_norm.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch1to2_injector.ca_gamma - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch1to2_injector.cffn_gamma - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch1to2_injector.query_norm.weight - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch1to2_injector.query_norm.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch1to2_injector.feat_norm.weight - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch1to2_injector.feat_norm.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch1to2_injector.attn.output_proj.weight - torch.Size([768, 384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch1to2_injector.attn.output_proj.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch1to2_injector.attn.value_proj.weight - torch.Size([384, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch1to2_injector.attn.value_proj.bias - torch.Size([384]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch1to2_injector.ffn.fc1.weight - torch.Size([192, 768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch1to2_injector.ffn.fc1.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch1to2_injector.ffn.fc2.weight - torch.Size([768, 192]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch1to2_injector.ffn.fc2.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch1to2_injector.ffn_norm.weight - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.interactions.11.interaction_units_23.branch1to2_injector.ffn_norm.bias - torch.Size([768]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_0_branch1.0.weight - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_0_branch1.0.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_0_branch2.0.weight - torch.Size([128, 96, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_0_branch2.1.weight - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_0_branch2.1.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_0_branch3.0.weight - torch.Size([128, 96, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_0_branch3.1.weight - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_0_branch3.1.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_1_branch1.0.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_1_branch1.0.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_1_branch2.0.weight - torch.Size([256, 192, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_1_branch2.1.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_1_branch2.1.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_1_branch3.0.weight - torch.Size([256, 192, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_1_branch3.1.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_1_branch3.1.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_10_branch1.0.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_10_branch1.0.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_10_branch2.0.weight - torch.Size([512, 384, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_10_branch2.1.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_10_branch2.1.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_10_branch3.0.weight - torch.Size([512, 384, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_10_branch3.1.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.intermediate_merging_10_branch3.1.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.merge_branch1.0.weight - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.merge_branch1.0.bias - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.merge_branch2.0.weight - torch.Size([1024, 768, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.merge_branch2.1.weight - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.merge_branch2.1.bias - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.merge_branch3.0.weight - torch.Size([1024, 768, 3, 3]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.merge_branch3.1.weight - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

backbone.merge_branch3.1.bias - torch.Size([1024]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

neck.lateral_convs.0.conv.weight - torch.Size([256, 128, 1, 1]): 
XavierInit: gain=1, distribution=uniform, bias=0 

neck.lateral_convs.0.conv.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

neck.lateral_convs.1.conv.weight - torch.Size([256, 256, 1, 1]): 
XavierInit: gain=1, distribution=uniform, bias=0 

neck.lateral_convs.1.conv.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

neck.lateral_convs.2.conv.weight - torch.Size([256, 512, 1, 1]): 
XavierInit: gain=1, distribution=uniform, bias=0 

neck.lateral_convs.2.conv.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

neck.lateral_convs.3.conv.weight - torch.Size([256, 1024, 1, 1]): 
XavierInit: gain=1, distribution=uniform, bias=0 

neck.lateral_convs.3.conv.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

neck.fpn_convs.0.conv.weight - torch.Size([256, 256, 3, 3]): 
XavierInit: gain=1, distribution=uniform, bias=0 

neck.fpn_convs.0.conv.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

neck.fpn_convs.1.conv.weight - torch.Size([256, 256, 3, 3]): 
XavierInit: gain=1, distribution=uniform, bias=0 

neck.fpn_convs.1.conv.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

neck.fpn_convs.2.conv.weight - torch.Size([256, 256, 3, 3]): 
XavierInit: gain=1, distribution=uniform, bias=0 

neck.fpn_convs.2.conv.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

neck.fpn_convs.3.conv.weight - torch.Size([256, 256, 3, 3]): 
XavierInit: gain=1, distribution=uniform, bias=0 

neck.fpn_convs.3.conv.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

rpn_head.rpn_conv.weight - torch.Size([256, 256, 3, 3]): 
NormalInit: mean=0, std=0.01, bias=0 

rpn_head.rpn_conv.bias - torch.Size([256]): 
NormalInit: mean=0, std=0.01, bias=0 

rpn_head.rpn_cls.weight - torch.Size([3, 256, 1, 1]): 
NormalInit: mean=0, std=0.01, bias=0 

rpn_head.rpn_cls.bias - torch.Size([3]): 
NormalInit: mean=0, std=0.01, bias=0 

rpn_head.rpn_reg.weight - torch.Size([12, 256, 1, 1]): 
NormalInit: mean=0, std=0.01, bias=0 

rpn_head.rpn_reg.bias - torch.Size([12]): 
NormalInit: mean=0, std=0.01, bias=0 

roi_head.bbox_head.fc_cls.weight - torch.Size([81, 1024]): 
NormalInit: mean=0, std=0.01, bias=0 

roi_head.bbox_head.fc_cls.bias - torch.Size([81]): 
NormalInit: mean=0, std=0.01, bias=0 

roi_head.bbox_head.fc_reg.weight - torch.Size([320, 1024]): 
NormalInit: mean=0, std=0.001, bias=0 

roi_head.bbox_head.fc_reg.bias - torch.Size([320]): 
NormalInit: mean=0, std=0.001, bias=0 

roi_head.bbox_head.shared_fcs.0.weight - torch.Size([1024, 12544]): 
XavierInit: gain=1, distribution=uniform, bias=0 

roi_head.bbox_head.shared_fcs.0.bias - torch.Size([1024]): 
XavierInit: gain=1, distribution=uniform, bias=0 

roi_head.bbox_head.shared_fcs.1.weight - torch.Size([1024, 1024]): 
XavierInit: gain=1, distribution=uniform, bias=0 

roi_head.bbox_head.shared_fcs.1.bias - torch.Size([1024]): 
XavierInit: gain=1, distribution=uniform, bias=0 

roi_head.mask_head.convs.0.conv.weight - torch.Size([256, 256, 3, 3]): 
Initialized by user-defined `init_weights` in ConvModule  

roi_head.mask_head.convs.0.conv.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

roi_head.mask_head.convs.1.conv.weight - torch.Size([256, 256, 3, 3]): 
Initialized by user-defined `init_weights` in ConvModule  

roi_head.mask_head.convs.1.conv.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

roi_head.mask_head.convs.2.conv.weight - torch.Size([256, 256, 3, 3]): 
Initialized by user-defined `init_weights` in ConvModule  

roi_head.mask_head.convs.2.conv.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

roi_head.mask_head.convs.3.conv.weight - torch.Size([256, 256, 3, 3]): 
Initialized by user-defined `init_weights` in ConvModule  

roi_head.mask_head.convs.3.conv.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of MaskRCNN  

roi_head.mask_head.upsample.weight - torch.Size([256, 256, 2, 2]): 
Initialized by user-defined `init_weights` in FCNMaskHead  

roi_head.mask_head.upsample.bias - torch.Size([256]): 
Initialized by user-defined `init_weights` in FCNMaskHead  

roi_head.mask_head.conv_logits.weight - torch.Size([80, 256, 1, 1]): 
Initialized by user-defined `init_weights` in FCNMaskHead  

roi_head.mask_head.conv_logits.bias - torch.Size([80]): 
Initialized by user-defined `init_weights` in FCNMaskHead  
2024-08-27 23:32:36,549 - mmdet - INFO - {'num_layers': 12, 'layer_decay_rate': 0.8, 'skip_stride': [1, 3]}
2024-08-27 23:32:36,549 - mmdet - INFO - Build LayerDecayOptimizerConstructor 0.800000 - 14
2024-08-27 23:32:36,564 - mmdet - INFO - Param groups = {
  "layer_13_decay": {
    "param_names": [
      "backbone.w1",
      "backbone.w2",
      "backbone.w3",
      "backbone.intermediate_merging_0_w1",
      "backbone.intermediate_merging_0_w2",
      "backbone.intermediate_merging_0_w3",
      "backbone.intermediate_merging_1_w1",
      "backbone.intermediate_merging_1_w2",
      "backbone.intermediate_merging_1_w3",
      "backbone.intermediate_merging_10_w1",
      "backbone.intermediate_merging_10_w2",
      "backbone.intermediate_merging_10_w3",
      "backbone.interactions.0.interaction_units_12.branch2to1_proj.weight",
      "backbone.interactions.0.interaction_units_12.branch1to2_proj.weight",
      "backbone.interactions.0.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight",
      "backbone.interactions.0.interaction_units_12.branch2to1_injector.attn.attention_weights.weight",
      "backbone.interactions.0.interaction_units_12.branch2to1_injector.attn.output_proj.weight",
      "backbone.interactions.0.interaction_units_12.branch2to1_injector.attn.value_proj.weight",
      "backbone.interactions.0.interaction_units_12.branch2to1_injector.ffn.fc1.weight",
      "backbone.interactions.0.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight",
      "backbone.interactions.0.interaction_units_12.branch2to1_injector.ffn.fc2.weight",
      "backbone.interactions.0.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight",
      "backbone.interactions.0.interaction_units_12.branch1to2_injector.attn.attention_weights.weight",
      "backbone.interactions.0.interaction_units_12.branch1to2_injector.attn.output_proj.weight",
      "backbone.interactions.0.interaction_units_12.branch1to2_injector.attn.value_proj.weight",
      "backbone.interactions.0.interaction_units_12.branch1to2_injector.ffn.fc1.weight",
      "backbone.interactions.0.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight",
      "backbone.interactions.0.interaction_units_12.branch1to2_injector.ffn.fc2.weight",
      "backbone.interactions.0.interaction_units_23.branch2to1_proj.weight",
      "backbone.interactions.0.interaction_units_23.branch1to2_proj.weight",
      "backbone.interactions.0.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight",
      "backbone.interactions.0.interaction_units_23.branch2to1_injector.attn.attention_weights.weight",
      "backbone.interactions.0.interaction_units_23.branch2to1_injector.attn.output_proj.weight",
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      "backbone.interactions.10.interaction_units_23.branch1to2_proj.bias",
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      "neck.lateral_convs.1.conv.bias",
      "neck.lateral_convs.2.conv.bias",
      "neck.lateral_convs.3.conv.bias",
      "neck.fpn_convs.0.conv.bias",
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      "neck.fpn_convs.2.conv.bias",
      "neck.fpn_convs.3.conv.bias",
      "rpn_head.rpn_conv.bias",
      "rpn_head.rpn_cls.bias",
      "rpn_head.rpn_reg.bias",
      "roi_head.bbox_head.fc_cls.bias",
      "roi_head.bbox_head.fc_reg.bias",
      "roi_head.bbox_head.shared_fcs.0.bias",
      "roi_head.bbox_head.shared_fcs.1.bias",
      "roi_head.mask_head.convs.0.conv.bias",
      "roi_head.mask_head.convs.1.conv.bias",
      "roi_head.mask_head.convs.2.conv.bias",
      "roi_head.mask_head.convs.3.conv.bias",
      "roi_head.mask_head.upsample.bias",
      "roi_head.mask_head.conv_logits.bias"
    ],
    "lr_scale": 1.0,
    "lr": 0.0002,
    "weight_decay": 0.0
  }
}
2024-08-27 23:33:05,333 - mmdet - INFO - Automatic scaling of learning rate (LR) has been disabled.
2024-08-27 23:33:05,740 - mmdet - INFO - Start running, host: liqingyun@SH-IDCA1404-10-140-54-59, work_dir: /mnt/petrelfs/liqingyun/yx/PIIP_detseg/mmdetection/work_dirs/0827_4j_mask_rcnn_convnext-tsb_1024_672_448_regular-fpn-merge_cz
2024-08-27 23:33:05,740 - mmdet - INFO - Hooks will be executed in the following order:
before_run:
(VERY_HIGH   ) StepLrUpdaterHook                  
(49          ) ToBFloat16HookMMDet                
(NORMAL      ) DeepspeedCheckpointHook            
(LOW         ) DeepspeedDistEvalHook              
(VERY_LOW    ) MMDetWandbHook                     
 -------------------- 
before_train_epoch:
(VERY_HIGH   ) StepLrUpdaterHook                  
(NORMAL      ) DistSamplerSeedHook                
(LOW         ) IterTimerHook                      
(LOW         ) DeepspeedDistEvalHook              
(VERY_LOW    ) MMDetWandbHook                     
 -------------------- 
before_train_iter:
(VERY_HIGH   ) StepLrUpdaterHook                  
(LOW         ) IterTimerHook                      
(LOW         ) DeepspeedDistEvalHook              
 -------------------- 
after_train_iter:
(ABOVE_NORMAL) OptimizerHook                      
(NORMAL      ) DeepspeedCheckpointHook            
(LOW         ) IterTimerHook                      
(LOW         ) DeepspeedDistEvalHook              
(VERY_LOW    ) MMDetWandbHook                     
 -------------------- 
after_train_epoch:
(NORMAL      ) DeepspeedCheckpointHook            
(LOW         ) DeepspeedDistEvalHook              
(VERY_LOW    ) MMDetWandbHook                     
 -------------------- 
before_val_epoch:
(NORMAL      ) DistSamplerSeedHook                
(LOW         ) IterTimerHook                      
(VERY_LOW    ) MMDetWandbHook                     
 -------------------- 
before_val_iter:
(LOW         ) IterTimerHook                      
 -------------------- 
after_val_iter:
(LOW         ) IterTimerHook                      
 -------------------- 
after_val_epoch:
(VERY_LOW    ) MMDetWandbHook                     
 -------------------- 
after_run:
(VERY_LOW    ) MMDetWandbHook                     
 -------------------- 
2024-08-27 23:33:05,740 - mmdet - INFO - workflow: [('train', 1)], max: 12 epochs
2024-08-27 23:33:05,752 - mmdet - INFO - Checkpoints will be saved to /mnt/petrelfs/liqingyun/yx/PIIP_detseg/mmdetection/work_dirs/0827_4j_mask_rcnn_convnext-tsb_1024_672_448_regular-fpn-merge_cz by HardDiskBackend.
2024-08-28 00:49:25,578 - mmdet - INFO - Saving checkpoint at 1 epochs
2024-08-28 00:51:05,352 - mmdet - INFO - Evaluating bbox...
2024-08-28 00:51:38,587 - mmdet - INFO - 
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.333
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=1000 ] = 0.571
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=1000 ] = 0.349
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.191
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.367
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.446
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.482
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=300 ] = 0.482
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=1000 ] = 0.482
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.304
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.519
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.619

2024-08-28 00:51:38,587 - mmdet - INFO - Evaluating segm...
2024-08-28 00:52:16,564 - mmdet - INFO - 
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.330
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=1000 ] = 0.548
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=1000 ] = 0.348
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.148
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.360
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.501
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.470
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=300 ] = 0.470
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=1000 ] = 0.470
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.278
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.510
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.634

2024-08-28 02:09:44,135 - mmdet - INFO - Saving checkpoint at 2 epochs
2024-08-28 02:11:18,828 - mmdet - INFO - Evaluating bbox...
2024-08-28 02:11:46,886 - mmdet - INFO - 
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.384
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=1000 ] = 0.620
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=1000 ] = 0.421
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.225
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.426
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.519
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.519
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=300 ] = 0.519
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=1000 ] = 0.519
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.328
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.561
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.672

2024-08-28 02:11:46,886 - mmdet - INFO - Evaluating segm...
2024-08-28 02:12:18,514 - mmdet - INFO - 
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.373
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=1000 ] = 0.597
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=1000 ] = 0.402
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.177
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.402
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.562
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.500
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=300 ] = 0.500
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=1000 ] = 0.500
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.300
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.544
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.675

2024-08-28 03:30:34,360 - mmdet - INFO - Saving checkpoint at 3 epochs
2024-08-28 03:32:07,201 - mmdet - INFO - Evaluating bbox...
2024-08-28 03:32:36,939 - mmdet - INFO - 
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.416
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=1000 ] = 0.647
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=1000 ] = 0.461
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.247
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.453
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.558
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.548
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=300 ] = 0.548
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=1000 ] = 0.548
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.352
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.588
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.697

2024-08-28 03:32:36,940 - mmdet - INFO - Evaluating segm...
2024-08-28 03:33:07,828 - mmdet - INFO - 
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.385
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=1000 ] = 0.616
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=1000 ] = 0.413
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.183
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.412
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.580
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.511
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=300 ] = 0.511
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=1000 ] = 0.511
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.312
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.550
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.681

2024-08-28 04:51:27,411 - mmdet - INFO - Saving checkpoint at 4 epochs
2024-08-28 04:53:00,069 - mmdet - INFO - Evaluating bbox...
2024-08-28 04:53:22,369 - mmdet - INFO - 
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.427
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=1000 ] = 0.653
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=1000 ] = 0.471
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.259
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.462
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.578
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.553
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=300 ] = 0.553
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=1000 ] = 0.553
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.365
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.596
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.699

2024-08-28 04:53:22,369 - mmdet - INFO - Evaluating segm...
2024-08-28 04:53:48,176 - mmdet - INFO - 
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.394
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=1000 ] = 0.624
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=1000 ] = 0.422
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.193
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.422
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.589
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.513
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=300 ] = 0.513
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=1000 ] = 0.513
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.320
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.550
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.682

2024-08-28 06:12:08,559 - mmdet - INFO - Saving checkpoint at 5 epochs
2024-08-28 06:13:44,027 - mmdet - INFO - Evaluating bbox...
2024-08-28 06:14:09,673 - mmdet - INFO - 
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.438
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=1000 ] = 0.663
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=1000 ] = 0.482
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.270
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.473
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.585
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.566
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=300 ] = 0.566
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=1000 ] = 0.566
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.390
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.602
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.720

2024-08-28 06:14:09,673 - mmdet - INFO - Evaluating segm...
2024-08-28 06:14:41,801 - mmdet - INFO - 
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.401
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=1000 ] = 0.633
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=1000 ] = 0.429
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.203
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.433
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.599
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.523
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=300 ] = 0.523
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=1000 ] = 0.523
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.341
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.564
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.694

2024-08-28 07:32:17,176 - mmdet - INFO - Saving checkpoint at 6 epochs
2024-08-28 07:33:45,225 - mmdet - INFO - Evaluating bbox...
2024-08-28 07:34:08,486 - mmdet - INFO - 
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.442
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=1000 ] = 0.662
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=1000 ] = 0.485
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.261
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.478
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.592
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.563
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=300 ] = 0.563
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=1000 ] = 0.563
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.362
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.605
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.714

2024-08-28 07:34:08,486 - mmdet - INFO - Evaluating segm...
2024-08-28 07:34:32,228 - mmdet - INFO - 
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.402
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=1000 ] = 0.633
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=1000 ] = 0.431
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.202
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.430
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.596
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.517
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=300 ] = 0.517
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=1000 ] = 0.517
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.318
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.556
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.686

2024-08-28 08:53:09,701 - mmdet - INFO - Saving checkpoint at 7 epochs
2024-08-28 08:54:36,015 - mmdet - INFO - Evaluating bbox...
2024-08-28 08:55:00,296 - mmdet - INFO - 
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.444
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=1000 ] = 0.662
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=1000 ] = 0.490
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.266
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.483
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.599
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.562
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=300 ] = 0.562
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=1000 ] = 0.562
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.368
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.600
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.721

2024-08-28 08:55:00,296 - mmdet - INFO - Evaluating segm...
2024-08-28 08:55:23,556 - mmdet - INFO - 
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.403
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=1000 ] = 0.634
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=1000 ] = 0.434
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.202
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.436
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.599
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.515
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=300 ] = 0.515
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=1000 ] = 0.515
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.321
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.553
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.684

2024-08-28 10:13:46,961 - mmdet - INFO - Saving checkpoint at 8 epochs
2024-08-28 10:15:14,936 - mmdet - INFO - Evaluating bbox...
2024-08-28 10:15:41,727 - mmdet - INFO - 
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.443
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=1000 ] = 0.662
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=1000 ] = 0.486
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.271
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.480
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.594
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.565
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=300 ] = 0.565
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=1000 ] = 0.565
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.375
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.605
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.724

2024-08-28 10:15:41,727 - mmdet - INFO - Evaluating segm...
2024-08-28 10:16:06,612 - mmdet - INFO - 
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.403
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=1000 ] = 0.633
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=1000 ] = 0.430
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.206
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.433
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.597
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.519
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=300 ] = 0.519
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=1000 ] = 0.519
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.330
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.556
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.687

2024-08-28 11:34:26,193 - mmdet - INFO - Saving checkpoint at 9 epochs
2024-08-28 11:35:54,394 - mmdet - INFO - Evaluating bbox...
2024-08-28 11:36:17,764 - mmdet - INFO - 
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.462
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=1000 ] = 0.675
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=1000 ] = 0.506
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.279
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.496
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.620
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.575
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=300 ] = 0.575
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=1000 ] = 0.575
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.378
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.612
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.741

2024-08-28 11:36:17,764 - mmdet - INFO - Evaluating segm...
2024-08-28 11:36:40,173 - mmdet - INFO - 
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.416
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=1000 ] = 0.646
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=1000 ] = 0.449
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.214
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.442
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.616
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.524
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=300 ] = 0.524
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=1000 ] = 0.524
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.333
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.557
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.698

2024-08-28 12:55:39,983 - mmdet - INFO - Saving checkpoint at 10 epochs
2024-08-28 12:57:06,754 - mmdet - INFO - Evaluating bbox...
2024-08-28 12:57:29,064 - mmdet - INFO - 
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.462
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=1000 ] = 0.676
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=1000 ] = 0.507
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.280
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.494
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.622
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.577
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=300 ] = 0.577
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=1000 ] = 0.577
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.385
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.613
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.740

2024-08-28 12:57:29,064 - mmdet - INFO - Evaluating segm...
2024-08-28 12:57:51,336 - mmdet - INFO - 
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.416
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=1000 ] = 0.646
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=1000 ] = 0.447
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.215
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.441
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.614
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.527
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=300 ] = 0.527
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=1000 ] = 0.527
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.338
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.559
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.696

2024-08-28 14:16:32,317 - mmdet - INFO - Saving checkpoint at 11 epochs
2024-08-28 14:17:58,142 - mmdet - INFO - Evaluating bbox...
2024-08-28 14:18:18,384 - mmdet - INFO - 
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.463
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=1000 ] = 0.675
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=1000 ] = 0.507
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.280
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.497
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.621
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.575
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=300 ] = 0.575
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=1000 ] = 0.575
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.380
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.612
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.735

2024-08-28 14:18:18,385 - mmdet - INFO - Evaluating segm...
2024-08-28 14:18:43,443 - mmdet - INFO - 
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.416
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=1000 ] = 0.645
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=1000 ] = 0.448
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.214
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.441
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.614
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.524
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=300 ] = 0.524
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=1000 ] = 0.524
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.335
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.556
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.692

2024-08-28 15:37:19,855 - mmdet - INFO - Saving checkpoint at 12 epochs
2024-08-28 15:38:45,273 - mmdet - INFO - Evaluating bbox...
2024-08-28 15:39:05,093 - mmdet - INFO - 
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.464
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=1000 ] = 0.676
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=1000 ] = 0.507
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.282
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.496
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.624
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.577
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=300 ] = 0.577
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=1000 ] = 0.577
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.383
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.612
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.742

2024-08-28 15:39:05,094 - mmdet - INFO - Evaluating segm...
2024-08-28 15:39:27,127 - mmdet - INFO - 
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.417
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=1000 ] = 0.647
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=1000 ] = 0.448
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.213
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.441
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.617
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.525
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=300 ] = 0.525
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=1000 ] = 0.525
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.335
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.558
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.697