code stringlengths 1.14k 31.2k | apis list | extract_api stringlengths 187 38.3k |
|---|---|---|
import pathlib
from typing import Any, Dict, List, Tuple
from torchdata.datapipes.iter import IterDataPipe, Mapper, Filter
from torchvision.prototype.datasets.utils import Dataset, DatasetConfig, DatasetInfo, HttpResource, OnlineResource
from torchvision.prototype.datasets.utils._internal import path_comparator, hint_... | [
"torchdata.datapipes.iter.Mapper"
] | [((1862, 1880), 'torchvision.prototype.datasets.utils._internal.hint_shuffling', 'hint_shuffling', (['dp'], {}), '(dp)\n', (1876, 1880), False, 'from torchvision.prototype.datasets.utils._internal import path_comparator, hint_sharding, hint_shuffling\n'), ((1894, 1911), 'torchvision.prototype.datasets.utils._internal.h... |
import enum
import pdb
import functools
import pathlib
from typing import Any, Dict, List, Optional, Tuple, BinaryIO, cast, Union
from xml.etree import ElementTree
from torchdata.datapipes.iter import (
IterDataPipe,
Mapper,
Filter,
Demultiplexer,
IterKeyZipper,
LineReader,
)
from torchvision.d... | [
"torchdata.datapipes.iter.Mapper",
"torchdata.datapipes.iter.LineReader",
"torchdata.datapipes.iter.Demultiplexer",
"torchdata.datapipes.iter.Filter"
] | [((3711, 3818), 'Dataset4EO.datasets.utils.HttpResource', 'HttpResource', (['f"""http://host.robots.ox.ac.uk/pascal/VOC/voc{self._year}/{file_name}"""'], {'sha256': 'sha256'}), "(\n f'http://host.robots.ox.ac.uk/pascal/VOC/voc{self._year}/{file_name}',\n sha256=sha256)\n", (3723, 3818), False, 'from Dataset4EO.da... |
from torchtext._internal.module_utils import is_module_available
from typing import Union, Tuple
if is_module_available("torchdata"):
from torchdata.datapipes.iter import FileOpener, HttpReader, IterableWrapper
from torchtext.data.datasets_utils import (
_wrap_split_argument,
_add_docstring_header,
_c... | [
"torchdata.datapipes.iter.FileOpener",
"torchdata.datapipes.iter.IterableWrapper",
"torchdata.datapipes.iter.HttpReader"
] | [((101, 133), 'torchtext._internal.module_utils.is_module_available', 'is_module_available', (['"""torchdata"""'], {}), "('torchdata')\n", (120, 133), False, 'from torchtext._internal.module_utils import is_module_available\n'), ((775, 832), 'torchtext.data.datasets_utils._add_docstring_header', '_add_docstring_header'... |
import time
import torch
import torchdata
import torchfunc
from .datasets import ExampleDataset, ExampleIterable
from .utils import artificial_slowdown, enumerate_step, index_is_sample
def test_basic_iterable():
dataset = ExampleIterable(0, 100).map(lambda value: value + 12)
for index, item in enumerate(da... | [
"torchdata.maps.Flatten"
] | [((3190, 3254), 'torch.utils.data.DataLoader', 'torch.utils.data.DataLoader', (['dataset'], {'shuffle': '(True)', 'batch_size': '(3)'}), '(dataset, shuffle=True, batch_size=3)\n', (3217, 3254), False, 'import torch\n'), ((1419, 1436), 'torchfunc.Timer', 'torchfunc.Timer', ([], {}), '()\n', (1434, 1436), False, 'import ... |
from typing import (
Iterator,
Any,
Callable,
Dict,
Iterable,
List,
Optional,
)
import io
import torch
import torch.utils.data.datapipes as dp
from torchdata.datapipes.iter import S3FileLister, S3FileLoader
from torchdata.datapipes.utils import StreamWrapper
from torchrec.datasets.utils imp... | [
"torchdata.datapipes.iter.S3FileLoader",
"torchdata.datapipes.iter.S3FileLister"
] | [((520, 545), 'torchdata.datapipes.iter.S3FileLister', 'S3FileLister', (['s3_prefixes'], {}), '(s3_prefixes)\n', (532, 545), False, 'from torchdata.datapipes.iter import S3FileLister, S3FileLoader\n'), ((560, 584), 'torchdata.datapipes.iter.S3FileLoader', 'S3FileLoader', (['dp_s3_urls'], {}), '(dp_s3_urls)\n', (572, 58... |
import os
from functools import partial
from typing import Union, Tuple
from torchtext._internal.module_utils import is_module_available
from torchtext.data.datasets_utils import (
_wrap_split_argument,
_create_dataset_directory,
)
if is_module_available("torchdata"):
from torchdata.datapipes.iter import ... | [
"torchdata.datapipes.iter.IterableWrapper",
"torchdata.datapipes.iter.FileOpener"
] | [((245, 277), 'torchtext._internal.module_utils.is_module_available', 'is_module_available', (['"""torchdata"""'], {}), "('torchdata')\n", (264, 277), False, 'from torchtext._internal.module_utils import is_module_available\n'), ((866, 918), 'torchtext.data.datasets_utils._create_dataset_directory', '_create_dataset_di... |
import progressbar
import torch
from tele.meter import SumMeter
from torch.autograd import Variable
from torch.utils.data import DataLoader
from torchdata.mpii import MpiiData
from dsnt.data import MPIIDataset
from dsnt.util import timer, type_as_index, reverse_tensor
def generate_predictions(model, dataset, use_fli... | [
"torchdata.mpii.MpiiData"
] | [((537, 547), 'tele.meter.SumMeter', 'SumMeter', ([], {}), '()\n', (545, 547), False, 'from tele.meter import SumMeter\n'), ((597, 660), 'torch.utils.data.DataLoader', 'DataLoader', (['dataset', 'batch_size'], {'num_workers': '(4)', 'pin_memory': '(True)'}), '(dataset, batch_size, num_workers=4, pin_memory=True)\n', (6... |
import os
from typing import Union, Tuple
from torchtext._internal.module_utils import is_module_available
from torchtext.data.datasets_utils import (
_wrap_split_argument,
_create_dataset_directory,
)
if is_module_available("torchdata"):
from torchdata.datapipes.iter import FileOpener, HttpReader, Iterab... | [
"torchdata.datapipes.iter.IterableWrapper",
"torchdata.datapipes.iter.HttpReader",
"torchdata.datapipes.iter.FileOpener"
] | [((215, 247), 'torchtext._internal.module_utils.is_module_available', 'is_module_available', (['"""torchdata"""'], {}), "('torchdata')\n", (234, 247), False, 'from torchtext._internal.module_utils import is_module_available\n'), ((696, 748), 'torchtext.data.datasets_utils._create_dataset_directory', '_create_dataset_di... |
from torchtext._internal.module_utils import is_module_available
if is_module_available("torchdata"):
from torchdata.datapipes.iter import FileOpener, HttpReader, IterableWrapper
import os
from torchtext.data.datasets_utils import (
_wrap_split_argument,
_add_docstring_header,
_create_dataset_director... | [
"torchdata.datapipes.iter.IterableWrapper",
"torchdata.datapipes.iter.HttpReader",
"torchdata.datapipes.iter.FileOpener"
] | [((69, 101), 'torchtext._internal.module_utils.is_module_available', 'is_module_available', (['"""torchdata"""'], {}), "('torchdata')\n", (88, 101), False, 'from torchtext._internal.module_utils import is_module_available\n'), ((794, 836), 'torchtext.data.datasets_utils._add_docstring_header', '_add_docstring_header', ... |
import io
from collections import namedtuple
from typing import Any, Dict, List, Optional, Tuple, Iterator
from torchdata.datapipes.iter import IterDataPipe, Mapper, Zipper
from torchvision.prototype import features
from torchvision.prototype.datasets.utils import (
Dataset,
DatasetConfig,
DatasetInfo,
... | [
"torchdata.datapipes.iter.Mapper",
"torchdata.datapipes.iter.Zipper"
] | [((1123, 1184), 'collections.namedtuple', 'namedtuple', (['"""_Resource"""', "('file_name', 'gdrive_id', 'sha256')"], {}), "('_Resource', ('file_name', 'gdrive_id', 'sha256'))\n", (1133, 1184), False, 'from collections import namedtuple\n'), ((4149, 4178), 'torchdata.datapipes.iter.Zipper', 'Zipper', (['images_dp', 'ta... |
import os
from functools import partial
from torchtext._internal.module_utils import is_module_available
from torchtext.data.datasets_utils import _create_dataset_directory
if is_module_available("torchdata"):
from torchdata.datapipes.iter import FileOpener, IterableWrapper
from torchtext._download_hooks impo... | [
"torchdata.datapipes.iter.IterableWrapper",
"torchdata.datapipes.iter.FileOpener"
] | [((178, 210), 'torchtext._internal.module_utils.is_module_available', 'is_module_available', (['"""torchdata"""'], {}), "('torchdata')\n", (197, 210), False, 'from torchtext._internal.module_utils import is_module_available\n'), ((668, 720), 'torchtext.data.datasets_utils._create_dataset_directory', '_create_dataset_di... |
# Copyright (c) Facebook, Inc. and its affiliates.
import os
from torch.utils.data.dataset import IterableDataset
from torchtext._internal.module_utils import is_module_available
from torchtext.data.datasets_utils import (
_add_docstring_header,
_create_dataset_directory,
_wrap_split_argument,
)
if is_mod... | [
"torchdata.datapipes.iter.IterableWrapper",
"torchdata.datapipes.iter.FileLoader"
] | [((314, 346), 'torchtext._internal.module_utils.is_module_available', 'is_module_available', (['"""torchdata"""'], {}), "('torchdata')\n", (333, 346), False, 'from torchtext._internal.module_utils import is_module_available\n'), ((1378, 1435), 'torchtext.data.datasets_utils._add_docstring_header', '_add_docstring_heade... |
# Copyright (c) Facebook, Inc. and its affiliates.
import os
from torchdata.datapipes.iter import FileOpener, GDriveReader, IterableWrapper
from .utils import _add_docstring_header, _create_dataset_directory, _wrap_split_argument
URL = "https://drive.google.com/uc?export=download&id=0Bz8a_Dbh9QhbaW12WVVZS2drcnM"
M... | [
"torchdata.datapipes.iter.GDriveReader",
"torchdata.datapipes.iter.FileOpener",
"torchdata.datapipes.iter.IterableWrapper"
] | [((499, 554), 'os.path.join', 'os.path.join', (['"""amazon_review_polarity_csv"""', '"""train.csv"""'], {}), "('amazon_review_polarity_csv', 'train.csv')\n", (511, 554), False, 'import os\n'), ((568, 622), 'os.path.join', 'os.path.join', (['"""amazon_review_polarity_csv"""', '"""test.csv"""'], {}), "('amazon_review_pol... |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
from io import BytesIO
from typing import Iterator, Tuple
import torchdata
from torchdata.datapipes import fun... | [
"torchdata._torchdata.S3Handler",
"torchdata.datapipes.functional_datapipe"
] | [((442, 480), 'torchdata.datapipes.functional_datapipe', 'functional_datapipe', (['"""list_file_by_s3"""'], {}), "('list_file_by_s3')\n", (461, 480), False, 'from torchdata.datapipes import functional_datapipe\n'), ((3172, 3210), 'torchdata.datapipes.functional_datapipe', 'functional_datapipe', (['"""load_file_by_s3"""... |
import enum
import functools
import io
import pathlib
from typing import Any, Callable, Dict, List, Optional, Tuple
import torch
from torchdata.datapipes.iter import (
IterDataPipe,
Mapper,
Shuffler,
Filter,
IterKeyZipper,
Demultiplexer,
LineReader,
CSVParser,
)
from torchvision.prototy... | [
"torchdata.datapipes.iter.Filter",
"torchdata.datapipes.iter.Shuffler",
"torchdata.datapipes.iter.LineReader",
"torchdata.datapipes.iter.CSVParser",
"torchdata.datapipes.iter.Demultiplexer"
] | [((1203, 1397), 'torchvision.prototype.datasets.utils.HttpResource', 'HttpResource', (['"""https://www.robots.ox.ac.uk/~vgg/data/dtd/download/dtd-r1.0.1.tar.gz"""'], {'sha256': '"""e42855a52a4950a3b59612834602aa253914755c95b0cff9ead6d07395f8e205"""', 'decompress': '(True)'}), "(\n 'https://www.robots.ox.ac.uk/~vgg/d... |
import functools
import io
import os
import os.path
import pathlib
from typing import Callable, Optional, Collection
from typing import Union, Tuple, List, Dict, Any
import torch
from torchdata.datapipes.iter import IterDataPipe, FileLister, FileOpener, Mapper, Shuffler, Filter
from torchvision.prototype.datasets.deco... | [
"torchdata.datapipes.iter.Mapper",
"torchdata.datapipes.iter.Shuffler",
"torchdata.datapipes.iter.FileOpener"
] | [((1848, 1865), 'torchvision.prototype.datasets.utils._internal.hint_sharding', 'hint_sharding', (['dp'], {}), '(dp)\n', (1861, 1865), False, 'from torchvision.prototype.datasets.utils._internal import INFINITE_BUFFER_SIZE, hint_sharding\n'), ((1875, 1921), 'torchdata.datapipes.iter.Shuffler', 'Shuffler', (['dp'], {'bu... |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import os
import unittest
import warnings
from functools import partial
import expecttest
import numpy as np
i... | [
"torchdata.datapipes.iter.TFRecordLoader",
"torchdata.datapipes.iter.IterableWrapper",
"torchdata.datapipes.iter.FileOpener"
] | [((1515, 1530), 'torch.no_grad', 'torch.no_grad', ([], {}), '()\n', (1528, 1530), False, 'import torch\n'), ((6173, 6188), 'torch.no_grad', 'torch.no_grad', ([], {}), '()\n', (6186, 6188), False, 'import torch\n'), ((12867, 12882), 'unittest.main', 'unittest.main', ([], {}), '()\n', (12880, 12882), False, 'import unitt... |
import functools
import io
import pathlib
from typing import Any, Callable, Dict, List, Optional, Tuple
import torch
from torchdata.datapipes.iter import IterDataPipe, Mapper, Filter, IterKeyZipper, Demultiplexer, JsonParser, UnBatcher
from torchvision.prototype.datasets.utils import (
Dataset,
DatasetConfig,
... | [
"torchdata.datapipes.iter.JsonParser",
"torchdata.datapipes.iter.Mapper",
"torchdata.datapipes.iter.Demultiplexer",
"torchdata.datapipes.iter.UnBatcher"
] | [((1009, 1156), 'torchvision.prototype.datasets.utils.HttpResource', 'HttpResource', (['"""https://dl.fbaipublicfiles.com/clevr/CLEVR_v1.0.zip"""'], {'sha256': '"""5cd61cf1096ed20944df93c9adb31e74d189b8459a94f54ba00090e5c59936d1"""'}), "('https://dl.fbaipublicfiles.com/clevr/CLEVR_v1.0.zip', sha256=\n '5cd61cf1096ed... |
# Copyright (c) Facebook, Inc. and its affiliates.
import hashlib
import itertools
import lzma
import os
import subprocess
import tarfile
import unittest
import warnings
import zipfile
from json.decoder import JSONDecodeError
import expecttest
from _utils._common_utils_for_test import create_temp_dir, create_temp_fi... | [
"torchdata.datapipes.iter.IoPathFileOpener",
"torchdata.datapipes.iter.Decompressor",
"torchdata.datapipes.iter.TarArchiveLoader",
"torchdata.datapipes.iter.FileOpener",
"torchdata.datapipes.iter.RarArchiveLoader",
"torchdata.datapipes.iter.FileLister",
"torchdata.datapipes.iter.Saver",
"torchdata.dat... | [((802, 846), 'unittest.skipIf', 'unittest.skipIf', (['(not HAS_IOPATH)', '"""no iopath"""'], {}), "(not HAS_IOPATH, 'no iopath')\n", (817, 846), False, 'import unittest\n'), ((1177, 1227), 'unittest.skipIf', 'unittest.skipIf', (['(not HAS_RAR_TOOLS)', '"""no rar tools"""'], {}), "(not HAS_RAR_TOOLS, 'no rar tools')\n"... |
#!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torcharrow as ta
import torcharrow.dtypes as dt
import torcharrow.py... | [
"torchdata.datapipes.iter.FileLister"
] | [((1570, 1618), 'torchdata.datapipes.iter.FileLister', 'FileLister', (['parquet_directory'], {'masks': '"""*.parquet"""'}), "(parquet_directory, masks='*.parquet')\n", (1580, 1618), False, 'from torchdata.datapipes.iter import FileLister\n'), ((3608, 3715), 'torch.utils.data.DataLoader', 'DataLoader', (['parquet_df_dp'... |
# Copyright (c) Facebook, Inc. and its affiliates.
from typing import Callable, Iterator, List, Tuple, TypeVar
from torchdata.datapipes import functional_datapipe
from torchdata.datapipes.iter import IterDataPipe
T_co = TypeVar("T_co", covariant=True)
def _default_line_join(lines: List[str]) -> str:
return "\n... | [
"torchdata.datapipes.functional_datapipe"
] | [((223, 254), 'typing.TypeVar', 'TypeVar', (['"""T_co"""'], {'covariant': '(True)'}), "('T_co', covariant=True)\n", (230, 254), False, 'from typing import Callable, Iterator, List, Tuple, TypeVar\n'), ((337, 379), 'torchdata.datapipes.functional_datapipe', 'functional_datapipe', (['"""lines_to_paragraphs"""'], {}), "('... |
# Copyright (c) Facebook, Inc. and its affiliates.
import os
from torchdata.datapipes import functional_datapipe
from torchdata.datapipes.iter import IterDataPipe
from torchdata.datapipes.utils import StreamWrapper
from typing import Iterator, Tuple
class IoPathFileListerIterDataPipe(IterDataPipe[str]):
r""":cla... | [
"torchdata.datapipes.utils.StreamWrapper",
"torchdata.datapipes.functional_datapipe"
] | [((1325, 1367), 'torchdata.datapipes.functional_datapipe', 'functional_datapipe', (['"""load_file_by_iopath"""'], {}), "('load_file_by_iopath')\n", (1344, 1367), False, 'from torchdata.datapipes import functional_datapipe\n'), ((1287, 1321), 'os.path.join', 'os.path.join', (['self.root', 'file_name'], {}), '(self.root,... |
import functools
import io
from typing import Any, Callable, Dict, List, Optional, Tuple
import numpy as np
import torch
from torchdata.datapipes.iter import (
IterDataPipe,
Mapper,
UnBatcher,
)
from torchvision.prototype.datasets.decoder import raw
from torchvision.prototype.datasets.utils import (
Da... | [
"torchdata.datapipes.iter.Mapper",
"torchdata.datapipes.iter.UnBatcher"
] | [((1339, 1462), 'torchvision.prototype.datasets.utils.HttpResource', 'HttpResource', (['f"""http://ufldl.stanford.edu/housenumbers/{config.split}_32x32.mat"""'], {'sha256': 'self._CHECKSUMS[config.split]'}), "(f'http://ufldl.stanford.edu/housenumbers/{config.split}_32x32.mat'\n , sha256=self._CHECKSUMS[config.split]... |
import enum
import functools
import pathlib
import re
from typing import Any, Dict, List, Optional, Tuple, BinaryIO, Match, cast, Union
from torchdata.datapipes.iter import (
IterDataPipe,
LineReader,
IterKeyZipper,
Mapper,
Filter,
Demultiplexer,
TarArchiveLoader,
Enumerator,
)
from tor... | [
"torchdata.datapipes.iter.Mapper",
"torchdata.datapipes.iter.LineReader",
"torchdata.datapipes.iter.Demultiplexer",
"torchdata.datapipes.iter.TarArchiveLoader",
"torchdata.datapipes.iter.Enumerator",
"torchdata.datapipes.iter.Filter"
] | [((2802, 2845), 're.compile', 're.compile', (['"""(?P<wnid>n\\\\d{8})_\\\\d+[.]JPEG"""'], {}), "('(?P<wnid>n\\\\d{8})_\\\\d+[.]JPEG')\n", (2812, 2845), False, 'import re\n'), ((4568, 4625), 're.compile', 're.compile', (['"""ILSVRC2012_(val|test)_(?P<id>\\\\d{8})[.]JPEG"""'], {}), "('ILSVRC2012_(val|test)_(?P<id>\\\\d{8... |
import pathlib
from typing import Any, Dict, List, Tuple, Union
from torchdata.datapipes.iter import IterDataPipe, Mapper
from torchvision.prototype.datasets.utils import Dataset, HttpResource, OnlineResource
from torchvision.prototype.datasets.utils._internal import hint_sharding, hint_shuffling
from torchvision.prot... | [
"torchdata.datapipes.iter.Mapper"
] | [((1887, 1905), 'torchvision.prototype.datasets.utils._internal.hint_shuffling', 'hint_shuffling', (['dp'], {}), '(dp)\n', (1901, 1905), False, 'from torchvision.prototype.datasets.utils._internal import hint_sharding, hint_shuffling\n'), ((1919, 1936), 'torchvision.prototype.datasets.utils._internal.hint_sharding', 'h... |
# Copyright (c) Facebook, Inc. and its affiliates.
from functools import partial
from typing import List, Optional, TypeVar
from torchdata.datapipes import functional_datapipe
from torchdata.datapipes.iter import IterDataPipe
try: # TODO: Create dependency on TorchArrow?
import pyarrow.parquet as parquet
imp... | [
"torchdata.datapipes.functional_datapipe"
] | [((404, 419), 'typing.TypeVar', 'TypeVar', (['"""T_co"""'], {}), "('T_co')\n", (411, 419), False, 'from typing import List, Optional, TypeVar\n'), ((423, 455), 'torchdata.datapipes.functional_datapipe', 'functional_datapipe', (['"""dataframe"""'], {}), "('dataframe')\n", (442, 455), False, 'from torchdata.datapipes imp... |
import abc
import functools
import io
import pathlib
import pickle
from typing import Any, Callable, Dict, List, Optional, Tuple, Union, Iterator, cast
import numpy as np
import torch
from torchdata.datapipes.iter import (
IterDataPipe,
Filter,
Mapper,
)
from torchvision.prototype.datasets.decoder import r... | [
"torchdata.datapipes.iter.Mapper"
] | [((2739, 2798), 'torchvision.prototype.features.Label', 'Label', (['category_idx'], {'category': 'self.categories[category_idx]'}), '(category_idx, category=self.categories[category_idx])\n', (2744, 2798), False, 'from torchvision.prototype.features import Label, Image\n'), ((3197, 3223), 'torchdata.datapipes.iter.Mapp... |
import os
import tarfile
import enum
import functools
import pathlib
from tqdm import tqdm
import h5py
import torch
from typing import Any, Dict, List, Optional, Tuple, BinaryIO, cast, Union
from xml.etree import ElementTree
from torch.utils.data import DataLoader2
from Dataset4EO import transforms
import pdb
import nu... | [
"torchdata.datapipes.iter.Mapper"
] | [((1640, 1682), 'os.path.join', 'os.path.join', (['self.root', '"""landslide4sense"""'], {}), "(self.root, 'landslide4sense')\n", (1652, 1682), False, 'import os\n'), ((2169, 2208), 'os.path.join', 'os.path.join', (['decom_dir', '"""train"""', '"""img"""'], {}), "(decom_dir, 'train', 'img')\n", (2181, 2208), False, 'im... |
import csv
import io
from typing import Any, Callable, Dict, List, Optional, Tuple, Iterator, Sequence
import torch
from torchdata.datapipes.iter import (
IterDataPipe,
Mapper,
Shuffler,
Filter,
ZipArchiveReader,
Zipper,
IterKeyZipper,
)
from torchvision.prototype.datasets.utils import (
... | [
"torchdata.datapipes.iter.Mapper",
"torchdata.datapipes.iter.Shuffler",
"torchdata.datapipes.iter.ZipArchiveReader"
] | [((532, 600), 'csv.register_dialect', 'csv.register_dialect', (['"""celeba"""'], {'delimiter': '""" """', 'skipinitialspace': '(True)'}), "('celeba', delimiter=' ', skipinitialspace=True)\n", (552, 600), False, 'import csv\n'), ((1949, 2061), 'torchvision.prototype.datasets.utils.DatasetInfo', 'DatasetInfo', (['"""cele... |
# Copyright (c) Facebook, Inc. and its affiliates.
import csv
import os
from functools import partial
from torchtext._internal.module_utils import is_module_available
from torchtext.data.datasets_utils import (
_create_dataset_directory,
_wrap_split_argument,
)
if is_module_available("torchdata"):
from to... | [
"torchdata.datapipes.iter.FileOpener",
"torchdata.datapipes.iter.IterableWrapper"
] | [((275, 307), 'torchtext._internal.module_utils.is_module_available', 'is_module_available', (['"""torchdata"""'], {}), "('torchdata')\n", (294, 307), False, 'from torchtext._internal.module_utils import is_module_available\n'), ((1450, 1502), 'torchtext.data.datasets_utils._create_dataset_directory', '_create_dataset_... |
import functools
import io
import pathlib
import re
from typing import Any, Callable, Dict, List, Optional, Tuple, cast
import numpy as np
import torch
from torchdata.datapipes.iter import (
IterDataPipe,
Mapper,
Demultiplexer,
Filter,
IterKeyZipper,
LineReader,
)
from torchvision.prototype.dat... | [
"torchdata.datapipes.iter.Demultiplexer",
"torchdata.datapipes.iter.Mapper",
"torchdata.datapipes.iter.LineReader"
] | [((1193, 1398), 'torchvision.prototype.datasets.utils.HttpResource', 'HttpResource', (['"""https://www2.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/semantic_contours/benchmark.tgz"""'], {'sha256': '"""6a5a2918d5c73ce032fdeba876574d150d9d04113ab87540a1304cbcc715be53"""'}), "(\n 'https://www2.eecs.berkeley.... |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import os
import pickle
import unittest
import warnings
from functools import partial
from io import StringIO
f... | [
"torchdata.datapipes.map.SequenceWrapper",
"torchdata.datapipes.iter.IterableWrapper"
] | [((726, 753), 'dill.extend', 'dill.extend', ([], {'use_dill': '(False)'}), '(use_dill=False)\n', (737, 753), False, 'import dill\n'), ((15119, 15134), 'unittest.main', 'unittest.main', ([], {}), '()\n', (15132, 15134), False, 'import unittest\n'), ((944, 964), 'rarfile.tool_setup', 'rarfile.tool_setup', ([], {}), '()\n... |
# Copyright (c) Facebook, Inc. and its affiliates.
from torchdata.datapipes.iter import HttpReader
from .utils import _add_docstring_header, _create_dataset_directory, _wrap_split_argument
URL = {
"train": "https://raw.githubusercontent.com/mhjabreel/CharCnn_Keras/master/data/ag_news_csv/train.csv",
"test": "... | [
"torchdata.datapipes.iter.HttpReader"
] | [((1063, 1087), 'torchdata.datapipes.iter.HttpReader', 'HttpReader', (['[URL[split]]'], {}), '([URL[split]])\n', (1073, 1087), False, 'from torchdata.datapipes.iter import HttpReader\n')] |
import functools
import pathlib
import pickle
from typing import BinaryIO
from typing import (
Sequence,
Callable,
Union,
Any,
Tuple,
TypeVar,
Iterator,
Dict,
IO,
Sized,
)
from typing import cast
import torch
import torch.distributed as dist
import torch.utils.data
from torchdat... | [
"torchdata.datapipes.iter.IoPathFileLister",
"torchdata.datapipes.iter.Shuffler",
"torchdata.datapipes.iter.ShardingFilter",
"torchdata.datapipes.iter.IoPathFileOpener"
] | [((733, 745), 'typing.TypeVar', 'TypeVar', (['"""K"""'], {}), "('K')\n", (740, 745), False, 'from typing import Sequence, Callable, Union, Any, Tuple, TypeVar, Iterator, Dict, IO, Sized\n'), ((750, 762), 'typing.TypeVar', 'TypeVar', (['"""D"""'], {}), "('D')\n", (757, 762), False, 'from typing import Sequence, Callable... |
import pathlib
from typing import Any, Dict, List, Optional, Tuple
from torchdata.datapipes.iter import IterDataPipe, Mapper, Filter, CSVDictParser, Zipper, Demultiplexer
from torchvision.prototype.datasets.utils import (
Dataset,
DatasetConfig,
DatasetInfo,
OnlineResource,
HttpResource,
)
from tor... | [
"torchdata.datapipes.iter.Demultiplexer",
"torchdata.datapipes.iter.Mapper",
"torchdata.datapipes.iter.Zipper",
"torchdata.datapipes.iter.CSVDictParser"
] | [((1968, 1989), 'pathlib.Path', 'pathlib.Path', (['data[0]'], {}), '(data[0])\n', (1980, 1989), False, 'import pathlib\n'), ((3477, 3513), 'torchdata.datapipes.iter.CSVDictParser', 'CSVDictParser', (['ann_dp'], {'delimiter': '""";"""'}), "(ann_dp, delimiter=';')\n", (3490, 3513), False, 'from torchdata.datapipes.iter i... |
import functools
import pathlib
import re
from typing import Any, Dict, List, Optional, Tuple, BinaryIO, Match, cast
from torchdata.datapipes.iter import (
IterDataPipe,
LineReader,
IterKeyZipper,
Mapper,
Filter,
Demultiplexer,
TarArchiveLoader,
Enumerator,
)
from torchvision.prototype.... | [
"torchdata.datapipes.iter.Demultiplexer",
"torchdata.datapipes.iter.Mapper",
"torchdata.datapipes.iter.Enumerator",
"torchdata.datapipes.iter.LineReader",
"torchdata.datapipes.iter.TarArchiveLoader"
] | [((3107, 3150), 're.compile', 're.compile', (['"""(?P<wnid>n\\\\d{8})_\\\\d+[.]JPEG"""'], {}), "('(?P<wnid>n\\\\d{8})_\\\\d+[.]JPEG')\n", (3117, 3150), False, 'import re\n'), ((4503, 4560), 're.compile', 're.compile', (['"""ILSVRC2012_(val|test)_(?P<id>\\\\d{8})[.]JPEG"""'], {}), "('ILSVRC2012_(val|test)_(?P<id>\\\\d{8... |
#!python3
"""training the model in pytorch"""
from torchmodel import PHMModel
from torchdata import load_traindata
from argparse import ArgumentParser
def parse_args():
parser = ArgumentParser(description='train model')
# data parameters
parser.add_argument('--traindata', help='path to training data', ... | [
"torchdata.load_traindata"
] | [((186, 227), 'argparse.ArgumentParser', 'ArgumentParser', ([], {'description': '"""train model"""'}), "(description='train model')\n", (200, 227), False, 'from argparse import ArgumentParser\n'), ((1534, 1556), 'torchdata.load_traindata', 'load_traindata', (['params'], {}), '(params)\n', (1548, 1556), False, 'from tor... |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
from unittest import TestCase
from torchdata.dataloader2 import DataLoader2
from torchdata.dataloader2.datalo... | [
"torchdata.dataloader2.DataLoader2"
] | [((595, 631), 'torchdata.dataloader2.DataLoader2', 'DataLoader2', ([], {'datapipe': 'test_data_pipe'}), '(datapipe=test_data_pipe)\n', (606, 631), False, 'from torchdata.dataloader2 import DataLoader2\n'), ((907, 943), 'torchdata.dataloader2.DataLoader2', 'DataLoader2', ([], {'datapipe': 'test_data_pipe'}), '(datapipe=... |
from torchtext._internal.module_utils import is_module_available
from typing import Union, Tuple
if is_module_available("torchdata"):
from torchdata.datapipes.iter import FileOpener, HttpReader, IterableWrapper
from torchtext.data.datasets_utils import (
_wrap_split_argument,
_add_docstring_header,
_c... | [
"torchdata.datapipes.iter.FileOpener",
"torchdata.datapipes.iter.HttpReader",
"torchdata.datapipes.iter.IterableWrapper"
] | [((101, 133), 'torchtext._internal.module_utils.is_module_available', 'is_module_available', (['"""torchdata"""'], {}), "('torchdata')\n", (120, 133), False, 'from torchtext._internal.module_utils import is_module_available\n'), ((722, 764), 'torchtext.data.datasets_utils._add_docstring_header', '_add_docstring_header'... |
import os
from pathlib import Path
from typing import Union, Tuple
from torchtext._internal.module_utils import is_module_available
from torchtext.data.datasets_utils import _add_docstring_header
from torchtext.data.datasets_utils import _create_dataset_directory
from torchtext.data.datasets_utils import _wrap_split_a... | [
"torchdata.datapipes.iter.FileOpener",
"torchdata.datapipes.iter.HttpReader",
"torchdata.datapipes.iter.IterableWrapper"
] | [((332, 364), 'torchtext._internal.module_utils.is_module_available', 'is_module_available', (['"""torchdata"""'], {}), "('torchdata')\n", (351, 364), False, 'from torchtext._internal.module_utils import is_module_available\n'), ((673, 730), 'torchtext.data.datasets_utils._add_docstring_header', '_add_docstring_header'... |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
from abc import ABC, abstractmethod
from typing import Callable, Optional
from torch.utils.data import DataLo... | [
"torchdata.datapipes.iter.IterableWrapper"
] | [((3588, 3874), 'torch.utils.data.DataLoader', 'DataLoader', (['datapipe'], {'num_workers': 'self.num_workers', 'pin_memory': 'self.pin_memory', 'timeout': 'self.timeout', 'worker_init_fn': 'self.worker_init_fn', 'multiprocessing_context': 'self.multiprocessing_context', 'prefetch_factor': 'self.prefetch_factor', 'pers... |
from typing import Any, Dict, List, cast
import torch
from torchdata.datapipes.iter import IterDataPipe, Mapper, CSVDictParser
from torchvision.prototype.datasets.utils import (
Dataset,
DatasetConfig,
DatasetInfo,
OnlineResource,
KaggleDownloadResource,
)
from torchvision.prototype.datasets.utils.... | [
"torchdata.datapipes.iter.Mapper",
"torchdata.datapipes.iter.CSVDictParser"
] | [((1896, 1913), 'torchdata.datapipes.iter.CSVDictParser', 'CSVDictParser', (['dp'], {}), '(dp)\n', (1909, 1913), False, 'from torchdata.datapipes.iter import IterDataPipe, Mapper, CSVDictParser\n'), ((1927, 1945), 'torchvision.prototype.datasets.utils._internal.hint_shuffling', 'hint_shuffling', (['dp'], {}), '(dp)\n',... |
import pathlib
from typing import Any, Dict, List, Tuple, Union
from torchdata.datapipes.iter import IterDataPipe, Mapper, Filter
from torchvision.prototype.datasets.utils import Dataset, HttpResource, OnlineResource
from torchvision.prototype.datasets.utils._internal import (
path_comparator,
hint_sharding,
... | [
"torchdata.datapipes.iter.Mapper"
] | [((2199, 2217), 'torchvision.prototype.datasets.utils._internal.hint_shuffling', 'hint_shuffling', (['dp'], {}), '(dp)\n', (2213, 2217), False, 'from torchvision.prototype.datasets.utils._internal import path_comparator, hint_sharding, hint_shuffling, read_categories_file\n'), ((2231, 2248), 'torchvision.prototype.data... |
import tkinter as tk
import tkinter.filedialog
import tkinter.font
from functools import lru_cache
import torch
import torchvision.transforms
from PIL import ImageTk, Image
from torch.autograd import Variable
from torchdata.mpii import MPII_Joint_Names, MpiiData
from dsnt.data import MPIIDataset
from dsnt.util import... | [
"torchdata.mpii.MpiiData"
] | [((338, 359), 'functools.lru_cache', 'lru_cache', ([], {'maxsize': '(32)'}), '(maxsize=32)\n', (347, 359), False, 'from functools import lru_cache\n'), ((8328, 8354), 'torchdata.mpii.MpiiData', 'MpiiData', (['"""/datasets/mpii"""'], {}), "('/datasets/mpii')\n", (8336, 8354), False, 'from torchdata.mpii import MPII_Join... |
# Copyright (c) Facebook, Inc. and its affiliates.
import os
from torchdata.datapipes.iter import (
GDriveReader,
IterableWrapper,
)
from .utils import (
_wrap_split_argument,
_add_docstring_header,
_create_dataset_directory,
)
URL = "https://drive.google.com/uc?export=download&id=0Bz8a_Dbh9QhbaW... | [
"torchdata.datapipes.iter.IterableWrapper"
] | [((516, 578), 'os.path.join', 'os.path.join', (['_PATH', '"""amazon_review_polarity_csv"""', '"""train.csv"""'], {}), "(_PATH, 'amazon_review_polarity_csv', 'train.csv')\n", (528, 578), False, 'import os\n'), ((592, 653), 'os.path.join', 'os.path.join', (['_PATH', '"""amazon_review_polarity_csv"""', '"""test.csv"""'], ... |
# Copyright (c) Facebook, Inc. and its affiliates.
import re
from typing import Iterator, Optional, Tuple
from urllib.parse import urlparse
import requests
from requests.exceptions import HTTPError, RequestException
from torchdata.datapipes.iter import IterDataPipe
from torchdata.datapipes.utils import StreamWrapper
... | [
"torchdata.datapipes.utils.StreamWrapper"
] | [((2338, 2356), 'requests.Session', 'requests.Session', ([], {}), '()\n', (2354, 2356), False, 'import requests\n'), ((3293, 3363), 're.findall', 're.findall', (['"""filename="(.+)\\""""', "response.headers['content-disposition']"], {}), '(\'filename="(.+)"\', response.headers[\'content-disposition\'])\n', (3303, 3363)... |
import pathlib
from typing import Any, Dict, List, Tuple, Union
import torch
from torchdata.datapipes.iter import (
IterDataPipe,
Mapper,
CSVParser,
)
from torchvision.prototype.datasets.utils import (
Dataset,
HttpResource,
OnlineResource,
)
from torchvision.prototype.datasets.utils._internal ... | [
"torchdata.datapipes.iter.CSVParser",
"torchdata.datapipes.iter.Mapper"
] | [((1056, 1239), 'torchvision.prototype.datasets.utils.HttpResource', 'HttpResource', (['"""http://archive.ics.uci.edu/ml/machine-learning-databases/semeion/semeion.data"""'], {'sha256': '"""f43228ae3da5ea6a3c95069d53450b86166770e3b719dcc333182128fe08d4b1"""'}), "(\n 'http://archive.ics.uci.edu/ml/machine-learning-da... |
# Copyright (c) Facebook, Inc. and its affiliates.
import io
import expecttest
import os
import unittest
import warnings
from torchdata.datapipes.iter import (
HttpReader,
IterableWrapper,
)
from _utils._common_utils_for_test import (
create_temp_dir,
)
class TestDataPipeRemoteIO(expecttest.TestCase):
... | [
"torchdata.datapipes.iter.HttpReader",
"torchdata.datapipes.iter.IterableWrapper"
] | [((1788, 1803), 'unittest.main', 'unittest.main', ([], {}), '()\n', (1801, 1803), False, 'import unittest\n'), ((364, 381), '_utils._common_utils_for_test.create_temp_dir', 'create_temp_dir', ([], {}), '()\n', (379, 381), False, 'from _utils._common_utils_for_test import create_temp_dir\n'), ((1645, 1672), 'torchdata.d... |
# Copyright (c) Facebook, Inc. and its affiliates.
import io
import itertools
import unittest
import warnings
from collections import defaultdict
from typing import Dict
import expecttest
import torch.utils.data.datapipes.iter
import torchdata
from _utils._common_utils_for_test import IDP_NoLen, reset_after_n_next_... | [
"torchdata.datapipes.iter.Rows2Columnar",
"torchdata.datapipes.iter.Cycler",
"torchdata.datapipes.iter.ParagraphAggregator",
"torchdata.datapipes.iter.MapKeyZipper",
"torchdata.datapipes.iter.IndexAdder",
"torchdata.datapipes.iter.LineReader",
"torchdata.datapipes.iter.Header",
"torchdata.datapipes.it... | [((26031, 26046), 'unittest.main', 'unittest.main', ([], {}), '()\n', (26044, 26046), False, 'import unittest\n'), ((2523, 2561), 'torchdata.datapipes.iter.InMemoryCacheHolder', 'InMemoryCacheHolder', (['source_dp'], {'size': '(5)'}), '(source_dp, size=5)\n', (2542, 2561), False, 'from torchdata.datapipes.iter import B... |
import pathlib
from typing import Any, Dict, List, Tuple, BinaryIO, Union
import numpy as np
from torchdata.datapipes.iter import (
IterDataPipe,
Mapper,
UnBatcher,
)
from torchvision.prototype.datasets.utils import (
Dataset,
HttpResource,
OnlineResource,
)
from torchvision.prototype.datasets.... | [
"torchdata.datapipes.iter.Mapper",
"torchdata.datapipes.iter.UnBatcher"
] | [((1544, 1664), 'torchvision.prototype.datasets.utils.HttpResource', 'HttpResource', (['f"""http://ufldl.stanford.edu/housenumbers/{self._split}_32x32.mat"""'], {'sha256': 'self._CHECKSUMS[self._split]'}), "(f'http://ufldl.stanford.edu/housenumbers/{self._split}_32x32.mat',\n sha256=self._CHECKSUMS[self._split])\n",... |
#!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import os
from typing import List
from torch import distributed as dist... | [
"torchdata.datapipes.iter.S3FileLister",
"torchdata.datapipes.iter.S3FileLoader"
] | [((8563, 8600), 'torchdata.datapipes.iter.S3FileLister', 'S3FileLister', (['[args.s3_criteo_prefix]'], {}), '([args.s3_criteo_prefix])\n', (8575, 8600), False, 'from torchdata.datapipes.iter import S3FileLister, S3FileLoader\n'), ((9365, 9386), 'torchdata.datapipes.iter.S3FileLoader', 'S3FileLoader', (['s3_urls'], {}),... |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import unittest
from typing import Iterator, List, Tuple, TypeVar
import expecttest
from _utils._common_util... | [
"torchdata.dataloader2.MultiProcessingReadingService",
"torchdata.dataloader2.graph.traverse",
"torchdata.dataloader2.graph.find_dps",
"torchdata.dataloader2.graph.replace_dp",
"torchdata.dataloader2.graph.remove_dp",
"torchdata.dataloader2.DataLoader2"
] | [((644, 675), 'typing.TypeVar', 'TypeVar', (['"""T_co"""'], {'covariant': '(True)'}), "('T_co', covariant=True)\n", (651, 675), False, 'from typing import Iterator, List, Tuple, TypeVar\n'), ((5039, 5097), 'unittest.skipIf', 'unittest.skipIf', (['IS_WINDOWS', '"""Fork is required for lambda"""'], {}), "(IS_WINDOWS, 'Fo... |
import csv
import os
from typing import Union, Tuple
from torchtext._internal.module_utils import is_module_available
from torchtext.data.datasets_utils import (
_wrap_split_argument,
_create_dataset_directory,
)
if is_module_available("torchdata"):
from torchdata.datapipes.iter import FileOpener, HttpRea... | [
"torchdata.datapipes.iter.FileOpener",
"torchdata.datapipes.iter.HttpReader",
"torchdata.datapipes.iter.IterableWrapper"
] | [((226, 258), 'torchtext._internal.module_utils.is_module_available', 'is_module_available', (['"""torchdata"""'], {}), "('torchdata')\n", (245, 258), False, 'from torchtext._internal.module_utils import is_module_available\n'), ((730, 782), 'torchtext.data.datasets_utils._create_dataset_directory', '_create_dataset_di... |
# Copyright (c) Facebook, Inc. and its affiliates.
import http.server
import os
import re
import threading
import torch
import torch.utils.data.backward_compatibility
import torchvision.datasets as datasets
import torchvision.datasets.folder
import torchvision.transforms as transforms
from PIL import Image
from torch.... | [
"torchdata.datapipes.iter.FileLister",
"torchdata.datapipes.iter.HttpReader"
] | [((438, 477), 'os.path.join', 'os.path.join', (['"""fakedata"""', '"""imagefolder"""'], {}), "('fakedata', 'imagefolder')\n", (450, 477), False, 'import os\n'), ((1144, 1184), 'os.path.relpath', 'os.path.relpath', (['path'], {'start': 'IMAGES_ROOT'}), '(path, start=IMAGES_ROOT)\n', (1159, 1184), False, 'import os\n'), ... |
import csv
import os
from functools import partial
from torchtext._internal.module_utils import is_module_available
from torchtext.data.datasets_utils import (
_create_dataset_directory,
_wrap_split_argument,
)
if is_module_available("torchdata"):
from torchdata.datapipes.iter import FileOpener, IterableW... | [
"torchdata.datapipes.iter.FileOpener",
"torchdata.datapipes.iter.IterableWrapper"
] | [((224, 256), 'torchtext._internal.module_utils.is_module_available', 'is_module_available', (['"""torchdata"""'], {}), "('torchdata')\n", (243, 256), False, 'from torchtext._internal.module_utils import is_module_available\n'), ((1298, 1350), 'torchtext.data.datasets_utils._create_dataset_directory', '_create_dataset_... |
import os
import tarfile
import enum
import functools
from tqdm import tqdm
import h5py
import torch
from typing import Any, Dict, List, Optional, Tuple, BinaryIO, cast, Union
from xml.etree import ElementTree
from torch.utils.data import DataLoader2
from Dataset4EO import transforms
import pathlib
import pdb
import nu... | [
"torchdata.datapipes.iter.Mapper"
] | [((1874, 1913), 'os.path.join', 'os.path.join', (['decom_dir', '"""train"""', '"""img"""'], {}), "(decom_dir, 'train', 'img')\n", (1886, 1913), False, 'import os\n'), ((1939, 1979), 'os.path.join', 'os.path.join', (['decom_dir', '"""train"""', '"""mask"""'], {}), "(decom_dir, 'train', 'mask')\n", (1951, 1979), False, '... |
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