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import fastai from neptune.new.integrations.fastai import NeptuneCallback from fastai.vision.all import * import neptune.new as neptune run = neptune.init( project="common/fastai-integration", api_token="<PASSWORD>", tags="basic" ) path = untar_data(URLs.MNIST_TINY) dls = ImageDataLoaders.from_csv(path) # Log al...
[ "neptune.new.integrations.fastai.NeptuneCallback", "neptune.new.init" ]
[((143, 234), 'neptune.new.init', 'neptune.init', ([], {'project': '"""common/fastai-integration"""', 'api_token': '"""<PASSWORD>"""', 'tags': '"""basic"""'}), "(project='common/fastai-integration', api_token='<PASSWORD>',\n tags='basic')\n", (155, 234), True, 'import neptune.new as neptune\n'), ((393, 446), 'neptun...
import neptune from tensorflow.keras.callbacks import BaseLogger class NeptuneMonitor(BaseLogger): def __init__(self, name, api_token, prj_name, params: tuple = None): assert api_token is not None assert prj_name is not None super(BaseLogger, self).__init__() self.my_name = name ...
[ "neptune.create_experiment", "neptune.init" ]
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'''Train DCENet with PyTorch''' # from __future__ import print_function import torch import torch.nn as nn import torch.optim as optim from torch.utils.data import DataLoader import os import json import neptune import argparse import numpy as np from loader import * from utils.plots import * from utils.utils impor...
[ "neptune.init", "neptune.log_metric", "neptune.create_experiment", "neptune.append_tag" ]
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import gym, torch, random, copy import torch.nn as nn import torch.optim as optim import numpy as np import torch.nn.functional as F import neptune.new as neptune # initialize policy & value network class PolicyNetwork(nn.Module): def __init__(self, beta): super().__init__() self.model = nn.Sequen...
[ "neptune.new.init" ]
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# # Copyright (c) 2020, Neptune Labs Sp. z o.o. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agr...
[ "neptune.new.exceptions.ProjectNotFound", "neptune.new.sync.get_project", "neptune.new.sync.sync_all_runs", "neptune.new.internal.utils.sync_offset_file.SyncOffsetFile", "neptune.new.sync.get_qualified_name", "neptune.new.sync.sync_selected_runs", "neptune.new.sync.synchronization_status" ]
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import neptune # The init() function called this way assumes that # NEPTUNE_API_TOKEN environment variable is defined. neptune.init('zackpashkin/sandbox') PARAMS = {'decay_factor' : 0.5, 'n_iterations' : 117} neptune.create_experiment(name='minimal_example',params=PARAMS) # log some metrics for i in ran...
[ "neptune.create_experiment", "neptune.init", "neptune.log_metric" ]
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import requests import pytest from neptune.neptune_api import NeptuneService from neptune.tests.conftest import get_server_addr @pytest.mark.fpgas(1) def test_coco(request): """ Check the coco service from Neptune with a known image Args: request (fixture): get the cmdline options """ ser...
[ "neptune.neptune_api.NeptuneService", "neptune.tests.conftest.get_server_addr" ]
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""" Script by <NAME>, November 2020 Used to finetune models trained on pathology images (pre-chunked) on External Images """ import numpy as np import tables import pickle import neptune from neptunecontrib.monitoring.keras import NeptuneMonitor import collections from sklearn.utils import class_weight import cv2 fr...
[ "neptune.init" ]
[((1446, 1542), 'neptune.init', 'neptune.init', ([], {'api_token': 'neptune_api_key', 'project_qualified_name': '"""yashaektefaie/benignmodel"""'}), "(api_token=neptune_api_key, project_qualified_name=\n 'yashaektefaie/benignmodel')\n", (1458, 1542), False, 'import neptune\n'), ((2046, 2083), 'tables.open_file', 'ta...
import warnings from typing import Callable, Sequence, Union import joblib import neptune.new as neptune import neptune.new.integrations.optuna as optuna_utils import optuna import pandas as pd from optuna.samplers import TPESampler from optuna.study import Study from optuna.trial import FrozenTrial, Trial from sklear...
[ "neptune.new.init", "neptune.new.integrations.optuna.NeptuneCallback" ]
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import neptune def _update_keys(d, prefix): keys = list(d.keys()) for k in keys: d['{}_{}'.format(prefix, k)] = d.pop(k) class NeptuneWriter: def __init__(self, proj_name): self.project = neptune.init(proj_name) self.has_started = False def start(self, args, **kwargs): ...
[ "neptune.init" ]
[((220, 243), 'neptune.init', 'neptune.init', (['proj_name'], {}), '(proj_name)\n', (232, 243), False, 'import neptune\n')]
import neptune.new as neptune import os import torch.nn as nn import torch import torch.nn.functional as F from torch.optim import SGD, Adam from torch.utils.data import DataLoader, random_split from torch.optim.lr_scheduler import CyclicLR import torch.multiprocessing as mp import numpy as np import random import math...
[ "neptune.new.init" ]
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# -*- coding: utf-8 -*- # # Copyright (c) 2017, deepsense.io # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicab...
[ "neptune.internal.cli.storage.upload_storage_utils.upload_to_storage", "neptune.internal.cli.commands.enqueue_utils.EnqueueUtils", "neptune.internal.common.config.neptune_config.load_global_config", "neptune.internal.cli.storage.populate_storage_utils.CopyProgressBar", "neptune.internal.common.NeptuneExcept...
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# # Copyright (c) 2020, Neptune Labs Sp. z o.o. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agr...
[ "neptune.new.exceptions.MetadataInconsistency", "neptune.new.internal.utils.paths.join_paths", "neptune.new.internal.utils.paths.parse_path" ]
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"""Implements Neptune Logger.""" from abc import ABC from typing import TYPE_CHECKING, List from torchflare.callbacks.callback import Callbacks from torchflare.callbacks.states import CallbackOrder from torchflare.utils.imports_check import module_available _AVAILABLE = module_available("neptune") if _AVAILABLE: ...
[ "neptune.new.init" ]
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#!/usr/bin/env python # The MIT License (MIT) # Copyright (c) 2020 <NAME> # Paper: "Self-Supervised Relational Reasoning for Representation Learning", <NAME> & <NAME>, NeurIPS 2020 # GitHub: https://github.com/mpatacchiola/self-supervised-relational-reasoning # # Implementation of a standard neural network (no self-su...
[ "neptune.send_metric", "neptune.create_experiment", "neptune.init" ]
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# -*- coding: utf-8 -*- # # Copyright (c) 2017, deepsense.io # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicab...
[ "neptune.internal.common.api.api_service_factory.create_services", "neptune.internal.common.threads.neptune_future.NeptuneFuture", "neptune.internal.common.NeptuneInternalException", "neptune.internal.common.NeptuneException" ]
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import neptune # The init() function called this way assumes that # NEPTUNE_API_TOKEN environment variable is defined. neptune.init('vanducng/sandbox') neptune.create_experiment(name='minimal_example') # log some metrics for i in range(100): neptune.log_metric('loss', 0.95**i) neptune.log_metric('AUC', 0.96)
[ "neptune.create_experiment", "neptune.init", "neptune.log_metric" ]
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import sys from dataclasses import asdict from pathlib import Path from pprint import pprint from typing import Optional import click import matplotlib.pyplot as plt import neptune import torch import torchaudio from click import Context from torch.nn.functional import mse_loss from tqdm import trange, tqdm from refo...
[ "neptune.init" ]
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import itertools import json import logging import os import tempfile from typing import List, Any, Dict, Tuple import gin import numpy as np import pandas as pd from experiments.src.gin import get_default_experiment_name, parse_gin_str from experiments.src.training.training_utils import get_metric_cls GridResultDic...
[ "neptune.init" ]
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# # Copyright (c) 2022, Neptune Labs Sp. z o.o. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agr...
[ "neptune.new.exceptions.ProjectNotFound", "neptune.new.sync.utils.get_project" ]
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