repo_id stringlengths 15 89 | file_path stringlengths 27 180 | content stringlengths 1 2.23M | __index_level_0__ int64 0 0 |
|---|---|---|---|
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/utils/doc_utils.py | from typing import Callable
def is_documented_by(function_with_docstring: Callable):
"""Decorator to share docstrings across common functions.
Args:
function_with_docstring (`Callable`): Name of the function with the docstring.
"""
def wrapper(target_function):
target_function.__doc_... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/utils/metadata.py | import textwrap
from collections import Counter
from pathlib import Path
from typing import Any, ClassVar, Dict, Optional, Tuple, Union
import yaml
from huggingface_hub import DatasetCardData
from ..config import METADATA_CONFIGS_FIELD
from ..utils.logging import get_logger
from .deprecation_utils import deprecated
... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/utils/readme.py | # loading package files: https://stackoverflow.com/a/20885799
import importlib.resources as pkg_resources
import logging
from pathlib import Path
from typing import Any, List, Tuple
import yaml
from . import resources
from .deprecation_utils import deprecated
BASE_REF_URL = "https://github.com/huggingface/datasets/... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/utils/sharding.py | from typing import List
import numpy as np
def _number_of_shards_in_gen_kwargs(gen_kwargs: dict) -> int:
"""Return the number of possible shards according to the input gen_kwargs"""
# Having lists of different sizes makes sharding ambigious, raise an error in this case
# until we decide how to define sha... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/utils/filelock.py | # deprecated, please use the `filelock` package instead
from filelock import ( # noqa: F401 # imported for backward compatibility TODO: remove in 3.0.0
BaseFileLock,
SoftFileLock,
Timeout,
UnixFileLock,
WindowsFileLock,
)
from ._filelock import FileLock # noqa: F401 # imported for backward compa... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/utils/deprecation_utils.py | import enum
import inspect
import warnings
from functools import wraps
from typing import Callable, Optional
from .logging import get_logger
_emitted_deprecation_warnings = set()
logger = get_logger(__name__)
def deprecated(help_message: Optional[str] = None):
"""Decorator to mark a class or a function as depr... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/utils/logging.py | # Copyright 2020 Optuna, Hugging Face
#
# 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 agreed to in ... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/utils/file_utils.py | """
Utilities for working with the local dataset cache.
This file is adapted from the AllenNLP library at https://github.com/allenai/allennlp
Copyright by the AllenNLP authors.
"""
import copy
import io
import json
import os
import posixpath
import re
import shutil
import sys
import time
import urllib
import warnings
... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/utils/info_utils.py | import enum
import os
from typing import Optional
from huggingface_hub.utils import insecure_hashlib
from .. import config
from .logging import get_logger
logger = get_logger(__name__)
class VerificationMode(enum.Enum):
"""`Enum` that specifies which verification checks to run.
The default mode is `BASIC... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/utils/extract.py | import bz2
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from ._filelock import FileLock
from .logging import get_logger
... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/utils/download_manager.py | # deprecated, please use datasets.download.download_manager
| 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/utils/patching.py | from importlib import import_module
from .logging import get_logger
logger = get_logger(__name__)
class _PatchedModuleObj:
"""Set all the modules components as attributes of the _PatchedModuleObj object."""
def __init__(self, module, attrs=None):
attrs = attrs or []
if module is not None:
... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/utils/typing.py | import os
from typing import Dict, List, Tuple, TypeVar, Union
T = TypeVar("T")
ListLike = Union[List[T], Tuple[T, ...]]
NestedDataStructureLike = Union[T, List[T], Dict[str, T]]
PathLike = Union[str, bytes, os.PathLike]
| 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/utils/__init__.py | # Copyright 2020 The HuggingFace Datasets Authors and the TensorFlow Datasets Authors.
#
# 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
#
# U... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/utils/_filelock.py | #!/usr/bin/env python
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# 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/LI... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/utils/version.py | # Copyright 2020 The HuggingFace Datasets Authors and the TensorFlow Datasets Authors.
#
# 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
#
# U... | 0 |
hf_public_repos/datasets/src/datasets/utils | hf_public_repos/datasets/src/datasets/utils/resources/readme_structure.yaml | name: "" # Filename comes here
allow_empty: false
allow_empty_text: true
subsections:
- name: "Dataset Card for X" # First-level markdown heading
allow_empty: false
allow_empty_text: true
subsections:
- name: "Table of Contents"
allow_empty: false
allow_empty_text: false
subs... | 0 |
hf_public_repos/datasets/src/datasets/utils | hf_public_repos/datasets/src/datasets/utils/resources/multilingualities.json | {
"monolingual": "contains a single language",
"multilingual": "contains multiple languages",
"translation": "contains translated or aligned text",
"other": "other type of language distribution"
}
| 0 |
hf_public_repos/datasets/src/datasets/utils | hf_public_repos/datasets/src/datasets/utils/resources/size_categories.json | [
"unknown",
"n<1K",
"1K<n<10K",
"10K<n<100K",
"100K<n<1M",
"1M<n<10M",
"10M<n<100M",
"100M<n<1B",
"1B<n<10B",
"10B<n<100B",
"100B<n<1T",
"n>1T"
]
| 0 |
hf_public_repos/datasets/src/datasets/utils | hf_public_repos/datasets/src/datasets/utils/resources/creators.json | {
"language": [
"found",
"crowdsourced",
"expert-generated",
"machine-generated",
"other"
],
"annotations": [
"found",
"crowdsourced",
"expert-generated",
"machine-generated",
"no-annotation",
"other"
]
}
| 0 |
hf_public_repos/datasets/src/datasets/utils | hf_public_repos/datasets/src/datasets/utils/resources/languages.json | {
"code": "Programming language (C++, Java, Javascript, Python, etc.)",
"aa": "Afar",
"aaa": "Ghotuo",
"aab": "Alumu-Tesu",
"aac": "Ari",
"aad": "Amal",
"aae": "Arbëreshë Albanian",
"aaf": "Aranadan",
"aag": "Ambrak",
"aah": "Abu' Arapesh",
"aai": "Arifama-Miniafia",
"aak... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/parallel/parallel.py | import contextlib
from multiprocessing import Pool, RLock
from tqdm.auto import tqdm
from ..utils import experimental, logging
logger = logging.get_logger(__name__)
class ParallelBackendConfig:
backend_name = None
@experimental
def parallel_map(function, iterable, num_proc, types, disable_tqdm, desc, single... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/parallel/__init__.py | from .parallel import parallel_backend, parallel_map, ParallelBackendConfig # noqa F401
| 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/download/mock_download_manager.py | # Copyright 2020 The TensorFlow Datasets Authors.
#
# 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 a... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/download/download_config.py | import copy
import warnings
from dataclasses import InitVar, dataclass, field
from pathlib import Path
from typing import Any, Dict, Optional, Union
from .. import config
@dataclass
class DownloadConfig:
"""Configuration for our cached path manager.
Attributes:
cache_dir (`str` or `Path`, *optional*... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/download/streaming_download_manager.py | import glob
import io
import os
import posixpath
import re
import tarfile
import time
import xml.dom.minidom
import zipfile
from asyncio import TimeoutError
from io import BytesIO
from itertools import chain
from pathlib import Path, PurePosixPath
from typing import Any, Callable, Dict, Generator, Iterable, List, Optio... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/download/download_manager.py | # Copyright 2020 The TensorFlow Datasets Authors.
#
# 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 a... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/download/__init__.py | __all__ = [
"DownloadConfig",
"DownloadManager",
"DownloadMode",
"StreamingDownloadManager",
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import StreamingDownloadManager
| 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/tasks/language_modeling.py | from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=True)
class LanguageModeling(TaskTemplate):
task: str = field(default="language-modeling", metadata={"include_in_asdict_even_if_is_default": True})
... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/tasks/text_classification.py | import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=True)
class TextClassification(TaskTemplate):
# `task` is not a ClassVar since we want it to be part of the `asdict` output fo... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/tasks/question_answering.py | from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=True)
class QuestionAnsweringExtractive(TaskTemplate):
# `task` is not a ClassVar since we want it to be part of the `asdict` output for JSO... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/tasks/automatic_speech_recognition.py | import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=True)
class AutomaticSpeechRecognition(TaskTemplate):
task: str = field(default="automatic-speech-recognition", metadata={"include_... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/tasks/base.py | import abc
import copy
import dataclasses
from dataclasses import dataclass
from typing import ClassVar, Dict, Type, TypeVar
from ..features import Features
T = TypeVar("T", bound="TaskTemplate")
@dataclass(frozen=True)
class TaskTemplate(abc.ABC):
# `task` is not a ClassVar since we want it to be part of the ... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/tasks/image_classification.py | import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=True)
class ImageClassification(TaskTemplate):
task: str = field(default="image-classification", metadata={"include_in_asdict_... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/tasks/audio_classification.py | import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, ClassLabel, Features
from .base import TaskTemplate
@dataclass(frozen=True)
class AudioClassification(TaskTemplate):
task: str = field(default="audio-classification", metadata={"include_in_asdict_... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/tasks/__init__.py | from typing import Optional
from ..utils.logging import get_logger
from .audio_classification import AudioClassification
from .automatic_speech_recognition import AutomaticSpeechRecognition
from .base import TaskTemplate
from .image_classification import ImageClassification
from .language_modeling import LanguageModel... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/tasks/summarization.py | from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=True)
class Summarization(TaskTemplate):
# `task` is not a ClassVar since we want it to be part of the `asdict` output for JSON serialization
task... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/formatting/jax_formatter.py | # Copyright 2021 The HuggingFace Authors.
#
# 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 agreed to... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/formatting/np_formatter.py | # Copyright 2020 The HuggingFace Authors.
#
# 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 agreed to... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/formatting/formatting.py | # Copyright 2020 The HuggingFace Authors.
#
# 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 agreed to... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/formatting/torch_formatter.py | # Copyright 2020 The HuggingFace Authors.
#
# 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 agreed to... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/formatting/__init__.py | # Copyright 2020 The HuggingFace Datasets Authors and the TensorFlow Datasets Authors.
#
# 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
#
# U... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/formatting/tf_formatter.py | # Copyright 2020 The HuggingFace Authors.
#
# 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 agreed to... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/packaged_modules/__init__.py | import inspect
import re
from typing import Dict, List
from huggingface_hub.utils import insecure_hashlib
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .sql imp... | 0 |
hf_public_repos/datasets/src/datasets/packaged_modules | hf_public_repos/datasets/src/datasets/packaged_modules/generator/generator.py | from dataclasses import dataclass
from typing import Callable, Optional
import datasets
@dataclass
class GeneratorConfig(datasets.BuilderConfig):
generator: Optional[Callable] = None
gen_kwargs: Optional[dict] = None
features: Optional[datasets.Features] = None
def __post_init__(self):
asser... | 0 |
hf_public_repos/datasets/src/datasets/packaged_modules | hf_public_repos/datasets/src/datasets/packaged_modules/arrow/arrow.py | import itertools
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import datasets
from datasets.table import table_cast
logger = datasets.utils.logging.get_logger(__name__)
@dataclass
class ArrowConfig(datasets.BuilderConfig):
"""BuilderConfig for Arrow."""
features: Opt... | 0 |
hf_public_repos/datasets/src/datasets/packaged_modules | hf_public_repos/datasets/src/datasets/packaged_modules/csv/csv.py | import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from datasets.utils.py_util... | 0 |
hf_public_repos/datasets/src/datasets/packaged_modules | hf_public_repos/datasets/src/datasets/packaged_modules/spark/spark.py | import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config import MAX_SHARD_SIZE
from dataset... | 0 |
hf_public_repos/datasets/src/datasets/packaged_modules | hf_public_repos/datasets/src/datasets/packaged_modules/parquet/parquet.py | import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
logger = datasets.utils.logging.get_logger(__name__)
@dataclass
class ParquetConfig(datasets.BuilderConfig):
"""BuilderCo... | 0 |
hf_public_repos/datasets/src/datasets/packaged_modules | hf_public_repos/datasets/src/datasets/packaged_modules/imagefolder/imagefolder.py | from typing import List
import datasets
from datasets.tasks import ImageClassification
from ..folder_based_builder import folder_based_builder
logger = datasets.utils.logging.get_logger(__name__)
class ImageFolderConfig(folder_based_builder.FolderBasedBuilderConfig):
"""BuilderConfig for ImageFolder."""
... | 0 |
hf_public_repos/datasets/src/datasets/packaged_modules | hf_public_repos/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py | import collections
import itertools
import os
from dataclasses import dataclass
from typing import List, Optional, Tuple, Type
import pandas as pd
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.features.features import FeatureType
from datasets.tasks.base import TaskTemplate
logger = ... | 0 |
hf_public_repos/datasets/src/datasets/packaged_modules | hf_public_repos/datasets/src/datasets/packaged_modules/webdataset/webdataset.py | import io
import json
from itertools import islice
from typing import Any, Callable, Dict, List
import numpy as np
import pyarrow as pa
import datasets
logger = datasets.utils.logging.get_logger(__name__)
class WebDataset(datasets.GeneratorBasedBuilder):
DEFAULT_WRITER_BATCH_SIZE = 100
IMAGE_EXTENSIONS: L... | 0 |
hf_public_repos/datasets/src/datasets/packaged_modules | hf_public_repos/datasets/src/datasets/packaged_modules/webdataset/_tenbin.py | #
# Copyright (c) 2017-2021 NVIDIA CORPORATION. All rights reserved.
# This file coems from the WebDataset library.
# See the LICENSE file for licensing terms (BSD-style).
#
"""
Binary tensor encodings for PyTorch and NumPy.
This defines efficient binary encodings for tensors. The format is 8 byte
aligned and can be ... | 0 |
hf_public_repos/datasets/src/datasets/packaged_modules | hf_public_repos/datasets/src/datasets/packaged_modules/json/json.py | import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
logger = datasets.utils.logging.get_logger(__name__)
@dataclass
... | 0 |
hf_public_repos/datasets/src/datasets/packaged_modules | hf_public_repos/datasets/src/datasets/packaged_modules/audiofolder/audiofolder.py | from typing import List
import datasets
from datasets.tasks import AudioClassification
from ..folder_based_builder import folder_based_builder
logger = datasets.utils.logging.get_logger(__name__)
class AudioFolderConfig(folder_based_builder.FolderBasedBuilderConfig):
"""Builder Config for AudioFolder."""
... | 0 |
hf_public_repos/datasets/src/datasets/packaged_modules | hf_public_repos/datasets/src/datasets/packaged_modules/sql/sql.py | import sys
from dataclasses import dataclass
from typing import TYPE_CHECKING, Dict, List, Optional, Tuple, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
if TYPE_CHECKING:
im... | 0 |
hf_public_repos/datasets/src/datasets/packaged_modules | hf_public_repos/datasets/src/datasets/packaged_modules/text/text.py | import itertools
import warnings
from dataclasses import InitVar, dataclass
from io import StringIO
from typing import Optional
import pyarrow as pa
import datasets
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
logger = datasets.utils.logging.get_logger(__name__)
... | 0 |
hf_public_repos/datasets/src/datasets/packaged_modules | hf_public_repos/datasets/src/datasets/packaged_modules/pandas/pandas.py | import itertools
from dataclasses import dataclass
from typing import Optional
import pandas as pd
import pyarrow as pa
import datasets
from datasets.table import table_cast
@dataclass
class PandasConfig(datasets.BuilderConfig):
"""BuilderConfig for Pandas."""
features: Optional[datasets.Features] = None
... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/io/spark.py | from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class SparkDatasetReader(AbstractDatasetReader):
"""A dataset reader that reads from a Spark DataFrame.
... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/io/text.py | from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class TextDatasetReader(AbstractDatasetReader):
def __init__(
self,
path_or_paths: Nest... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/io/csv.py | import multiprocessing
import os
from typing import BinaryIO, Optional, Union
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.csv.csv import Csv
from ..utils import tqdm as hf_tqdm
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc i... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/io/sql.py | import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import tqdm as hf_tqdm
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
import sqlite3
i... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/io/parquet.py | import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules import _PACKAGED_DATASETS_MO... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/io/json.py | import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import tqdm as hf_tqdm
from ..utils.typing import NestedDataStructureLike, Pa... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/io/abc.py | from abc import ABC, abstractmethod
from typing import Optional, Union
from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike
class AbstractDatasetReader(ABC):
def __init__(
self,
path_or_paths: ... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/io/generator.py | from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class GeneratorDatasetInputStream(AbstractDatasetInputStream):
def __init__(
self,
generator: Callable,
features: Optional... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/features/audio.py | import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.download_config import DownloadConfig
from ..download.streaming_download_manager import xopen, ... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/features/translation.py | from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class Translation:
"""`FeatureConnector` for translations with fixed languages per example.
Here for ... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/features/image.py | import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.download_config import DownloadConfig
from ..download.streamin... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/features/features.py | # Copyright 2020 The HuggingFace Datasets Authors and the TensorFlow Datasets Authors.
#
# 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
#
# U... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/features/__init__.py | # flake8: noqa
__all__ = [
"Audio",
"Array2D",
"Array3D",
"Array4D",
"Array5D",
"ClassLabel",
"Features",
"Sequence",
"Value",
"Image",
"Translation",
"TranslationVariableLanguages",
]
from .audio import Audio
from .features import Array2D, Array3D, Array4D, Array5D, Cla... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/commands/dummy_data.py | import fnmatch
import json
import os
import shutil
import tempfile
import xml.etree.ElementTree as ET
from argparse import ArgumentParser
from pathlib import Path
from typing import Optional
from datasets import config
from datasets.commands import BaseDatasetsCLICommand
from datasets.download.download_config import D... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/commands/env.py | import platform
from argparse import ArgumentParser
import fsspec
import huggingface_hub
import pandas
import pyarrow
from datasets import __version__ as version
from datasets.commands import BaseDatasetsCLICommand
def info_command_factory(_):
return EnvironmentCommand()
class EnvironmentCommand(BaseDatasetsC... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/commands/run_beam.py | import os
from argparse import ArgumentParser
from pathlib import Path
from shutil import copyfile
from typing import List
from datasets import config
from datasets.builder import DatasetBuilder
from datasets.commands import BaseDatasetsCLICommand
from datasets.download.download_config import DownloadConfig
from datas... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/commands/convert.py | import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
HIGHLIGHT_MESSAGE_PRE = """<<<<<<< This should probably be modified because it mentions: """
HIGHLIGHT_MESSAGE_POST = """=======
>>>>>>>... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/commands/test.py | import logging
import os
from argparse import ArgumentParser
from pathlib import Path
from shutil import copyfile, rmtree
from typing import Generator
import datasets.config
from datasets.builder import DatasetBuilder
from datasets.commands import BaseDatasetsCLICommand
from datasets.download.download_manager import D... | 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/commands/__init__.py | from abc import ABC, abstractmethod
from argparse import ArgumentParser
class BaseDatasetsCLICommand(ABC):
@staticmethod
@abstractmethod
def register_subcommand(parser: ArgumentParser):
raise NotImplementedError()
@abstractmethod
def run(self):
raise NotImplementedError()
| 0 |
hf_public_repos/datasets/src/datasets | hf_public_repos/datasets/src/datasets/commands/datasets_cli.py | #!/usr/bin/env python
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestComm... | 0 |
hf_public_repos/datasets | hf_public_repos/datasets/tests/test_dataset_dict.py | import os
import tempfile
from unittest import TestCase
import numpy as np
import pandas as pd
import pytest
from datasets import load_from_disk
from datasets.arrow_dataset import Dataset
from datasets.dataset_dict import DatasetDict, IterableDatasetDict
from datasets.features import ClassLabel, Features, Sequence, V... | 0 |
hf_public_repos/datasets | hf_public_repos/datasets/tests/test_download_manager.py | import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
URL = "http://www.mocksite.com/file1.txt"
CONTENT = '"text": ["foo", "fo... | 0 |
hf_public_repos/datasets | hf_public_repos/datasets/tests/test_file_utils.py | import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
get_... | 0 |
hf_public_repos/datasets | hf_public_repos/datasets/tests/README.md | ## Add Dummy data test
**Important** In order to pass the `load_dataset_<dataset_name>` test, dummy data is required for all possible config names.
First we distinguish between datasets scripts that
- A) have no config class and
- B) have a config class
For A) the dummy data folder structure, will always look as fol... | 0 |
hf_public_repos/datasets | hf_public_repos/datasets/tests/test_load.py | import importlib
import os
import pickle
import shutil
import tempfile
import time
from hashlib import sha256
from multiprocessing import Pool
from pathlib import Path
from unittest import TestCase
from unittest.mock import patch
import dill
import pyarrow as pa
import pytest
import requests
import datasets
from data... | 0 |
hf_public_repos/datasets | hf_public_repos/datasets/tests/test_fingerprint.py | import json
import os
import pickle
import subprocess
from functools import partial
from pathlib import Path
from tempfile import gettempdir
from textwrap import dedent
from types import FunctionType
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pytest
from multiprocess import... | 0 |
hf_public_repos/datasets | hf_public_repos/datasets/tests/test_extract.py | import os
import zipfile
import pytest
from datasets.utils.extract import (
Bzip2Extractor,
Extractor,
GzipExtractor,
Lz4Extractor,
SevenZipExtractor,
TarExtractor,
XzExtractor,
ZipExtractor,
ZstdExtractor,
)
from .utils import require_lz4, require_py7zr, require_zstandard
@pyte... | 0 |
hf_public_repos/datasets | hf_public_repos/datasets/tests/test_arrow_writer.py | import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datasets.features import Array... | 0 |
hf_public_repos/datasets | hf_public_repos/datasets/tests/test_version.py | import pytest
from datasets.utils.version import Version
@pytest.mark.parametrize(
"other, expected_equality",
[
(Version("1.0.0"), True),
("1.0.0", True),
(Version("2.0.0"), False),
("2.0.0", False),
("1", False),
("a", False),
(1, False),
(Non... | 0 |
hf_public_repos/datasets | hf_public_repos/datasets/tests/test_tqdm.py | import unittest
from unittest.mock import patch
import pytest
from pytest import CaptureFixture
from datasets.utils import (
are_progress_bars_disabled,
disable_progress_bars,
enable_progress_bars,
tqdm,
)
class TestTqdmUtils(unittest.TestCase):
@pytest.fixture(autouse=True)
def capsys(self,... | 0 |
hf_public_repos/datasets | hf_public_repos/datasets/tests/test_dataset_list.py | from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class DatasetListTest(TestCase):
def _create_example_records(self):
return [
{"col_1": 3, "col_2": "a"},
{"col_1": 2, "col_2": "b"},
{"col_1": 1, "col_2": "c"}... | 0 |
hf_public_repos/datasets | hf_public_repos/datasets/tests/conftest.py | import pytest
import datasets
import datasets.config
# Import fixture modules as plugins
pytest_plugins = ["tests.fixtures.files", "tests.fixtures.hub", "tests.fixtures.fsspec"]
def pytest_collection_modifyitems(config, items):
# Mark tests as "unit" by default if not marked as "integration" (or already marked... | 0 |
hf_public_repos/datasets | hf_public_repos/datasets/tests/test_builder.py | import importlib
import os
import tempfile
import types
from contextlib import nullcontext as does_not_raise
from multiprocessing import Process
from pathlib import Path
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from... | 0 |
hf_public_repos/datasets | hf_public_repos/datasets/tests/test_inspect.py | import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
pytestmark = pytest.mark.integration
@pytest.mark.parametrize("path", ["paws", "csv"])
def test_inspect_dataset(p... | 0 |
hf_public_repos/datasets | hf_public_repos/datasets/tests/utils.py | import asyncio
import importlib.metadata
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patch... | 0 |
hf_public_repos/datasets | hf_public_repos/datasets/tests/test_beam.py | import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import datasets
import datasets.config
from .utils import require_beam
class DummyBeamDataset(datasets.BeamBasedBuilder):
"""Dummy beam dataset."""
def _info(self):
return datasets.... | 0 |
hf_public_repos/datasets | hf_public_repos/datasets/tests/test_filesystem.py | import importlib
import os
import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry
from datasets.filesystems import COMPRESSION_FILESYSTEMS, extract_path_from_uri, is_remote_filesystem
from .utils import require_lz4, require_zstandard
def tes... | 0 |
hf_public_repos/datasets | hf_public_repos/datasets/tests/test_table.py | import copy
import pickle
import warnings
from typing import List, Union
import numpy as np
import pyarrow as pa
import pytest
import datasets
from datasets import Sequence, Value
from datasets.features.features import Array2D, Array2DExtensionType, ClassLabel, Features, Image
from datasets.table import (
Concate... | 0 |
hf_public_repos/datasets | hf_public_repos/datasets/tests/test_metadata_util.py | import re
import sys
import tempfile
import unittest
from pathlib import Path
import pytest
import yaml
from huggingface_hub import DatasetCard, DatasetCardData
from datasets.config import METADATA_CONFIGS_FIELD
from datasets.utils.metadata import MetadataConfigs
def _dedent(string: str) -> str:
indent_level = ... | 0 |
hf_public_repos/datasets | hf_public_repos/datasets/tests/test_search.py | import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pytest
from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex
from .utils import require_elasticsearch, require_... | 0 |
hf_public_repos/datasets | hf_public_repos/datasets/tests/test_info.py | import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
"files",
[
["full:README.md", "dataset_infos.json"],
["empty:README.md", "dataset_infos.json"],
["dataset_infos... | 0 |
hf_public_repos/datasets | hf_public_repos/datasets/tests/test_streaming_download_manager.py | import json
import os
import re
from pathlib import Path
import pytest
from fsspec.registry import _registry as _fsspec_registry
from fsspec.spec import AbstractBufferedFile, AbstractFileSystem
from datasets.download.download_config import DownloadConfig
from datasets.download.streaming_download_manager import (
... | 0 |
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