id int64 0 190k | prompt stringlengths 21 13.4M | docstring stringlengths 1 12k ⌀ |
|---|---|---|
18,017 | import filecmp
import glob
import importlib
import inspect
import json
import os
import posixpath
import shutil
import signal
import time
import warnings
from collections import Counter
from contextlib import nullcontext
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Dict, Lis... | Create a module with name `name` in which you can add dynamic modules such as metrics or datasets. The module can be imported using its name. The module is created in the HF_MODULE_CACHE directory by default (~/.cache/huggingface/modules) but it can be overridden by specifying a path to another directory in `hf_modules... |
18,018 | import filecmp
import glob
import importlib
import inspect
import json
import os
import posixpath
import shutil
import signal
import time
import warnings
from collections import Counter
from contextlib import nullcontext
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Dict, Lis... | Convert a list of scripts or text files provided in file_paths into a hashed filename in a repeatable way. |
18,019 | import filecmp
import glob
import importlib
import inspect
import json
import os
import posixpath
import shutil
import signal
import time
import warnings
from collections import Counter
from contextlib import nullcontext
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Dict, Lis... | Update the download count of a dataset or metric. |
18,020 | import filecmp
import glob
import importlib
import inspect
import json
import os
import posixpath
import shutil
import signal
import time
import warnings
from collections import Counter
from contextlib import nullcontext
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Dict, Lis... | Download additional module for a module <name>.py at URL (or local path) <base_path>/<name>.py The imports must have been parsed first using ``get_imports``. If some modules need to be installed with pip, an error is raised showing how to install them. This function return the list of downloaded modules as tuples (impo... |
18,021 | import filecmp
import glob
import importlib
import inspect
import json
import os
import posixpath
import shutil
import signal
import time
import warnings
from collections import Counter
from contextlib import nullcontext
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Dict, Lis... | null |
18,022 | import filecmp
import glob
import importlib
import inspect
import json
import os
import posixpath
import shutil
import signal
import time
import warnings
from collections import Counter
from contextlib import nullcontext
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Dict, Lis... | null |
18,023 | import filecmp
import glob
import importlib
import inspect
import json
import os
import posixpath
import shutil
import signal
import time
import warnings
from collections import Counter
from contextlib import nullcontext
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Dict, Lis... | null |
18,024 | import filecmp
import glob
import importlib
import inspect
import json
import os
import posixpath
import shutil
import signal
import time
import warnings
from collections import Counter
from contextlib import nullcontext
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Dict, Lis... | Infer module (and builder kwargs) from data files. Raise if module names for different splits don't match. Args: data_files ([`DataFilesDict`]): Dict of list of data files. path (str, *optional*): Dataset name or path. download_config ([`DownloadConfig`], *optional*): Specific download configuration parameters to authe... |
18,025 | import filecmp
import glob
import importlib
import inspect
import json
import os
import posixpath
import shutil
import signal
import time
import warnings
from collections import Counter
from contextlib import nullcontext
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Dict, Lis... | null |
18,026 | import filecmp
import glob
import importlib
import inspect
import json
import os
import posixpath
import shutil
import signal
import time
import warnings
from collections import Counter
from contextlib import nullcontext
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Dict, Lis... | Load a `datasets.Metric`. <Deprecated version="2.5.0"> Use `evaluate.load` instead, from the new library 🤗 Evaluate: https://huggingface.co/docs/evaluate </Deprecated> Args: path (``str``): path to the metric processing script with the metric builder. Can be either: - a local path to processing script or the directory... |
18,027 | import filecmp
import glob
import importlib
import inspect
import json
import os
import posixpath
import shutil
import signal
import time
import warnings
from collections import Counter
from contextlib import nullcontext
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Dict, Lis... | Load a dataset from the Hugging Face Hub, or a local dataset. You can find the list of datasets on the [Hub](https://huggingface.co/datasets) or with [`huggingface_hub.list_datasets`]. A dataset is a directory that contains: - some data files in generic formats (JSON, CSV, Parquet, text, etc.). - and optionally a datas... |
18,028 | import filecmp
import glob
import importlib
import inspect
import json
import os
import posixpath
import shutil
import signal
import time
import warnings
from collections import Counter
from contextlib import nullcontext
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Dict, Lis... | Loads a dataset that was previously saved using [`~Dataset.save_to_disk`] from a dataset directory, or from a filesystem using any implementation of `fsspec.spec.AbstractFileSystem`. Args: dataset_path (`str`): Path (e.g. `"dataset/train"`) or remote URI (e.g. `"s3://my-bucket/dataset/train"`) of the [`Dataset`] or [`D... |
18,029 | from typing import TypeVar
from .arrow_dataset import Dataset, _split_by_node_map_style_dataset
from .iterable_dataset import IterableDataset, _split_by_node_iterable_dataset
DatasetType = TypeVar("DatasetType", Dataset, IterableDataset)
class Dataset(DatasetInfoMixin, IndexableMixin, TensorflowDatasetMixin):
"""A... | Split a dataset for the node at rank `rank` in a pool of nodes of size `world_size`. For map-style datasets: Each node is assigned a chunk of data, e.g. rank 0 is given the first chunk of the dataset. To maximize data loading throughput, chunks are made of contiguous data on disk if possible. For iterable datasets: If ... |
18,030 | import inspect
import os
import shutil
import warnings
from pathlib import Path, PurePath
from typing import Dict, List, Mapping, Optional, Sequence, Union
import huggingface_hub
from . import config
from .download.download_config import DownloadConfig
from .download.download_manager import DownloadMode
from .download.... | List all the datasets scripts available on the Hugging Face Hub. Args: with_community_datasets (`bool`, *optional*, defaults to `True`): Include the community provided datasets. with_details (`bool`, *optional*, defaults to `False`): Return the full details on the datasets instead of only the short name. Example: ```py... |
18,031 | import inspect
import os
import shutil
import warnings
from pathlib import Path, PurePath
from typing import Dict, List, Mapping, Optional, Sequence, Union
import huggingface_hub
from . import config
from .download.download_config import DownloadConfig
from .download.download_manager import DownloadMode
from .download.... | List all the metrics script available on the Hugging Face Hub. <Deprecated version="2.5.0"> Use `evaluate.list_evaluation_modules` instead, from the new library 🤗 Evaluate: https://huggingface.co/docs/evaluate </Deprecated> Args: with_community_metrics (:obj:`bool`, optional, default ``True``): Include the community p... |
18,032 | import inspect
import os
import shutil
import warnings
from pathlib import Path, PurePath
from typing import Dict, List, Mapping, Optional, Sequence, Union
import huggingface_hub
from . import config
from .download.download_config import DownloadConfig
from .download.download_manager import DownloadMode
from .download.... | Allow inspection/modification of a dataset script by copying on local drive at local_path. Args: path (`str`): Path to the dataset processing script with the dataset builder. Can be either: - a local path to processing script or the directory containing the script (if the script has the same name as the directory), e.g... |
18,033 | import inspect
import os
import shutil
import warnings
from pathlib import Path, PurePath
from typing import Dict, List, Mapping, Optional, Sequence, Union
import huggingface_hub
from . import config
from .download.download_config import DownloadConfig
from .download.download_manager import DownloadMode
from .download.... | r""" Allow inspection/modification of a metric script by copying it on local drive at local_path. <Deprecated version="2.5.0"> Use `evaluate.inspect_evaluation_module` instead, from the new library 🤗 Evaluate instead: https://huggingface.co/docs/evaluate </Deprecated> Args: path (``str``): path to the dataset processi... |
18,034 | import inspect
import os
import shutil
import warnings
from pathlib import Path, PurePath
from typing import Dict, List, Mapping, Optional, Sequence, Union
import huggingface_hub
from . import config
from .download.download_config import DownloadConfig
from .download.download_manager import DownloadMode
from .download.... | Get the meta information about a dataset, returned as a dict mapping config name to DatasetInfoDict. Args: path (`str`): path to the dataset processing script with the dataset builder. Can be either: - a local path to processing script or the directory containing the script (if the script has the same name as the direc... |
18,035 | import inspect
import os
import shutil
import warnings
from pathlib import Path, PurePath
from typing import Dict, List, Mapping, Optional, Sequence, Union
import huggingface_hub
from . import config
from .download.download_config import DownloadConfig
from .download.download_manager import DownloadMode
from .download.... | Get the default config name for a particular dataset. Can return None only if the dataset has multiple configurations and no default configuration. Args: path (`str`): path to the dataset processing script with the dataset builder. Can be either: - a local path to processing script or the directory containing the scrip... |
18,036 | import inspect
import os
import shutil
import warnings
from pathlib import Path, PurePath
from typing import Dict, List, Mapping, Optional, Sequence, Union
import huggingface_hub
from . import config
from .download.download_config import DownloadConfig
from .download.download_manager import DownloadMode
from .download.... | Get the list of available splits for a particular config and dataset. Args: path (`str`): path to the dataset processing script with the dataset builder. Can be either: - a local path to processing script or the directory containing the script (if the script has the same name as the directory), e.g. `'./dataset/squad'`... |
18,037 | import os
import re
from functools import partial
from glob import has_magic
from pathlib import Path, PurePath
from typing import Callable, Dict, List, Optional, Set, Tuple, Union
import huggingface_hub
from fsspec.core import url_to_fs
from fsspec.implementations.http import HTTPFileSystem
from huggingface_hub import... | null |
18,038 | import os
import re
from functools import partial
from glob import has_magic
from pathlib import Path, PurePath
from typing import Callable, Dict, List, Optional, Set, Tuple, Union
import huggingface_hub
from fsspec.core import url_to_fs
from fsspec.implementations.http import HTTPFileSystem
from huggingface_hub import... | null |
18,039 | import os
from typing import BinaryIO, Optional, Union
import fsspec
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... | Get the writer_batch_size that defines the maximum row group size in the parquet files. The default in `datasets` is 1,000 but we lower it to 100 for image datasets. This allows to optimize random access to parquet file, since accessing 1 row requires to read its entire row group. This can be improved to get optimized ... |
18,040 | from collections.abc import Mapping, MutableMapping
from functools import partial
from typing import Any, Callable, Dict, Generic, Iterable, List, Optional, TypeVar, Union
import numpy as np
import pandas as pd
import pyarrow as pa
from packaging import version
from .. import config
from ..features import Features
from... | null |
18,041 | from collections.abc import Mapping, MutableMapping
from functools import partial
from typing import Any, Callable, Dict, Generic, Iterable, List, Optional, TypeVar, Union
import numpy as np
import pandas as pd
import pyarrow as pa
from packaging import version
from .. import config
from ..features import Features
from... | Return the first element of a batch (dict) as a row (dict) |
18,042 | from collections.abc import Mapping, MutableMapping
from functools import partial
from typing import Any, Callable, Dict, Generic, Iterable, List, Optional, TypeVar, Union
import numpy as np
import pandas as pd
import pyarrow as pa
from packaging import version
from .. import config
from ..features import Features
from... | Query a Table to extract the subtable that correspond to the given key. Args: table (``datasets.table.Table``): The input Table to query from key (``Union[int, slice, range, str, Iterable]``): The key can be of different types: - an integer i: the subtable containing only the i-th row - a slice [i:j:k]: the subtable co... |
18,043 | from collections.abc import Mapping, MutableMapping
from functools import partial
from typing import Any, Callable, Dict, Generic, Iterable, List, Optional, TypeVar, Union
import numpy as np
import pandas as pd
import pyarrow as pa
from packaging import version
from .. import config
from ..features import Features
from... | Format a Table depending on the key that was used and a Formatter object. Args: table (``datasets.table.Table``): The input Table to format key (``Union[int, slice, range, str, Iterable]``): Depending on the key that was used, the formatter formats the table as either a row, a column or a batch. formatter (``datasets.f... |
18,044 | import itertools
import os
import re
def filename_prefix_for_split(name, split):
if os.path.basename(name) != name:
raise ValueError(f"Should be a dataset name, not a path: {name}")
if not re.match(_split_re, split):
raise ValueError(f"Split name should match '{_split_re}'' but got '{split}'.")
... | null |
18,045 | import os
import types
import uuid
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
from filelock import BaseFileLock, Timeout
from . import config
from .arrow_dataset import Dataset
from .arrow_reader import ArrowReader
from .arrow_writer import ArrowWriter
from .downl... | null |
18,046 | import errno
import json
import os
import sys
from pathlib import Path
from typing import Any, Dict, Iterable, List, Optional, Tuple, Union
import fsspec
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
from fsspec.core import url_to_fs
from . import config
from .features import Features, Image, Val... | null |
18,047 | import errno
import json
import os
import sys
from pathlib import Path
from typing import Any, Dict, Iterable, List, Optional, Tuple, Union
import fsspec
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
from fsspec.core import url_to_fs
from . import config
from .features import Features, Image, Val... | Convert parquet file to arrow file. Inputs can be str paths or file-like objects |
18,048 | import enum
import io
import os
import posixpath
import tarfile
import warnings
import zipfile
from datetime import datetime
from functools import partial
from itertools import chain
from typing import Callable, Dict, Generator, List, Optional, Tuple, Union
from .. import config
from ..utils import tqdm as hf_tqdm
from... | null |
18,049 | import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union
_VERSION_REG = re.compile(r"^(?P<major>\d+)" r"\.(?P<minor>\d+)" r"\.(?P<patch>\d+)$")
The provided code snippet includes necessary dependencies for implementing the `_str_to_version_t... | Return the tuple (major, minor, patch) version extracted from the str. |
18,050 | import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union
The provided code snippet includes necessary dependencies for implementing the `_version_tuple_to_str` function. Write a Python function `def _version_tuple_to_str(version_tuple)` to s... | Return the str version from the version tuple (major, minor, patch). |
18,051 | import os
import warnings
from functools import partial
from math import ceil
from uuid import uuid4
import numpy as np
import pyarrow as pa
from multiprocess import get_context
from .. import config
def minimal_tf_collate_fn(features):
if isinstance(features, dict): # case batch_size=None: nothing to collate
... | null |
18,052 | import os
import warnings
from functools import partial
from math import ceil
from uuid import uuid4
import numpy as np
import pyarrow as pa
from multiprocess import get_context
from .. import config
def is_numeric_pa_type(pa_type):
if pa.types.is_list(pa_type):
return is_numeric_pa_type(pa_type.value_type)... | null |
18,053 | import os
import warnings
from functools import partial
from math import ceil
from uuid import uuid4
import numpy as np
import pyarrow as pa
from multiprocess import get_context
from .. import config
def np_get_batch(
indices, dataset, cols_to_retain, collate_fn, collate_fn_args, columns_to_np_types, return_dict=Fa... | Create a tf.data.Dataset from the underlying Dataset. This is a single-process method - the multiprocess equivalent is multiprocess_dataset_to_tf. Args: dataset (`Dataset`): Dataset to wrap with tf.data.Dataset. cols_to_retain (`List[str]`): Dataset column(s) to load in the tf.data.Dataset. It is acceptable to include ... |
18,054 | import os
import warnings
from functools import partial
from math import ceil
from uuid import uuid4
import numpy as np
import pyarrow as pa
from multiprocess import get_context
from .. import config
class NumpyMultiprocessingGenerator:
def __init__(
self,
dataset,
cols_to_retain,
co... | Create a tf.data.Dataset from the underlying Dataset. This is a multi-process method - the single-process equivalent is dataset_to_tf. Args: dataset (`Dataset`): Dataset to wrap with tf.data.Dataset. cols_to_retain (`List[str]`): Dataset column(s) to load in the tf.data.Dataset. It is acceptable to include column names... |
18,055 | import os
from apache_beam.io.filesystems import FileSystems
from apache_beam.pipeline import Pipeline
from .logging import get_logger
CHUNK_SIZE = 2 << 20
logger = get_logger(__name__)
The provided code snippet includes necessary dependencies for implementing the `upload_local_to_remote` function. Write a Python fun... | Use the Beam Filesystems to upload to a remote directory on gcs/s3/hdfs... |
18,056 | import os
from apache_beam.io.filesystems import FileSystems
from apache_beam.pipeline import Pipeline
from .logging import get_logger
CHUNK_SIZE = 2 << 20
logger = get_logger(__name__)
The provided code snippet includes necessary dependencies for implementing the `download_remote_to_local` function. Write a Python f... | Use the Beam Filesystems to download from a remote directory on gcs/s3/hdfs... |
18,057 | import time
from functools import partial
from huggingface_hub import HfApi, hf_hub_url
from huggingface_hub.hf_api import RepoFile
from packaging import version
from requests import ConnectionError, HTTPError
from .. import config
from . import logging
logger = logging.get_logger(__name__)
def preupload_lfs_files(hf_... | null |
18,058 | import time
from functools import partial
from huggingface_hub import HfApi, hf_hub_url
from huggingface_hub.hf_api import RepoFile
from packaging import version
from requests import ConnectionError, HTTPError
from .. import config
from . import logging
def preupload_lfs_files(hf_api: HfApi, **kwargs):
hf_api.... | null |
18,059 | import time
from functools import partial
from huggingface_hub import HfApi, hf_hub_url
from huggingface_hub.hf_api import RepoFile
from packaging import version
from requests import ConnectionError, HTTPError
from .. import config
from . import logging
def list_files_info(hf_api: HfApi, **kwargs):
yield from ... | null |
18,060 | import time
from functools import partial
from huggingface_hub import HfApi, hf_hub_url
from huggingface_hub.hf_api import RepoFile
from packaging import version
from requests import ConnectionError, HTTPError
from .. import config
from . import logging
def list_files_info(hf_api: HfApi, **kwargs):
kwargs = {*... | null |
18,061 | from typing import Callable
The provided code snippet includes necessary dependencies for implementing the `is_documented_by` function. Write a Python function `def is_documented_by(function_with_docstring: Callable)` to solve the following problem:
Decorator to share docstrings across common functions. Args: function... | Decorator to share docstrings across common functions. Args: function_with_docstring (`Callable`): Name of the function with the docstring. |
18,062 | from typing import Any, Dict, List, Optional, Union
from .. import config
from ..exceptions import DatasetsError
from .file_utils import (
get_authentication_headers_for_url,
http_get,
)
from .logging import get_logger
logger = get_logger(__name__)
class DatasetsServerError(DatasetsError):
"""Dataset-server... | Get the dataset exported parquet files Docs: https://huggingface.co/docs/datasets-server/parquet |
18,063 | from typing import Any, Dict, List, Optional, Union
from .. import config
from ..exceptions import DatasetsError
from .file_utils import (
get_authentication_headers_for_url,
http_get,
)
from .logging import get_logger
logger = get_logger(__name__)
class DatasetsServerError(DatasetsError):
"""Dataset-server... | Get the dataset information, can be useful to get e.g. the dataset features. Docs: https://huggingface.co/docs/datasets-server/info |
18,064 | import logging
import os
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
from .tqdm import ( # noqa: F401 # imported for backward compatibility
disable_pro... | null |
18,065 | import logging
import os
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
from .tqdm import ( # noqa: F401 # imported for backward compatibility
disable_pro... | null |
18,066 | import logging
import os
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
from .tqdm import ( # noqa: F401 # imported for backward compatibility
disable_pro... | Return a logger with the specified name. This function can be used in dataset scripts. |
18,067 | import logging
import os
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
from .tqdm import ( # noqa: F401 # imported for backward compatibility
disable_pro... | Set the level for the Hugging Face datasets library's root logger to `INFO`. This will display most of the logging information and tqdm bars. Shortcut to `datasets.logging.set_verbosity(datasets.logging.INFO)`. |
18,068 | import logging
import os
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
from .tqdm import ( # noqa: F401 # imported for backward compatibility
disable_pro... | Set the level for the Hugging Face datasets library's root logger to `DEBUG`. This will display all the logging information and tqdm bars. Shortcut to `datasets.logging.set_verbosity(datasets.logging.DEBUG)`. |
18,069 | import logging
import os
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
from .tqdm import ( # noqa: F401 # imported for backward compatibility
disable_pro... | Set the level for the Hugging Face datasets library's root logger to `ERROR`. This will display only the errors logging information and tqdm bars. Shortcut to `datasets.logging.set_verbosity(datasets.logging.ERROR)`. |
18,070 | import logging
import os
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
from .tqdm import ( # noqa: F401 # imported for backward compatibility
disable_pro... | Disable propagation of the library log outputs. Note that log propagation is disabled by default. |
18,071 | import logging
import os
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
from .tqdm import ( # noqa: F401 # imported for backward compatibility
disable_pro... | Enable propagation of the library log outputs. Please disable the Hugging Face datasets library's default handler to prevent double logging if the root logger has been configured. |
18,072 | import copy
import io
import json
import multiprocessing
import os
import posixpath
import re
import shutil
import sys
import time
import urllib
import warnings
from contextlib import closing, contextmanager
from functools import partial
from pathlib import Path
from typing import Optional, TypeVar, Union
from unittest... | null |
18,073 | import copy
import io
import json
import multiprocessing
import os
import posixpath
import re
import shutil
import sys
import time
import urllib
import warnings
from contextlib import closing, contextmanager
from functools import partial
from pathlib import Path
from typing import Optional, TypeVar, Union
from unittest... | null |
18,074 | import copy
import io
import json
import multiprocessing
import os
import posixpath
import re
import shutil
import sys
import time
import urllib
import warnings
from contextlib import closing, contextmanager
from functools import partial
from pathlib import Path
from typing import Optional, TypeVar, Union
from unittest... | null |
18,075 | import copy
import io
import json
import multiprocessing
import os
import posixpath
import re
import shutil
import sys
import time
import urllib
import warnings
from contextlib import closing, contextmanager
from functools import partial
from pathlib import Path
from typing import Optional, TypeVar, Union
from unittest... | null |
18,076 | import copy
import io
import json
import multiprocessing
import os
import posixpath
import re
import shutil
import sys
import time
import urllib
import warnings
from contextlib import closing, contextmanager
from functools import partial
from pathlib import Path
from typing import Optional, TypeVar, Union
from unittest... | null |
18,077 | import copy
import io
import json
import multiprocessing
import os
import posixpath
import re
import shutil
import sys
import time
import urllib
import warnings
from contextlib import closing, contextmanager
from functools import partial
from pathlib import Path
from typing import Optional, TypeVar, Union
from unittest... | null |
18,078 | import copy
import io
import json
import multiprocessing
import os
import posixpath
import re
import shutil
import sys
import time
import urllib
import warnings
from contextlib import closing, contextmanager
from functools import partial
from pathlib import Path
from typing import Optional, TypeVar, Union
from unittest... | null |
18,079 | import copy
import io
import json
import multiprocessing
import os
import posixpath
import re
import shutil
import sys
import time
import urllib
import warnings
from contextlib import closing, contextmanager
from functools import partial
from pathlib import Path
from typing import Optional, TypeVar, Union
from unittest... | null |
18,080 | import enum
import inspect
import warnings
from functools import wraps
from typing import Callable, Optional
from .logging import get_logger
_emitted_deprecation_warnings = set()
The provided code snippet includes necessary dependencies for implementing the `deprecated` function. Write a Python function `def deprecate... | Decorator to mark a class or a function as deprecated. Args: help_message (:obj:`str`, optional): An optional message to guide the user on how to switch to non-deprecated usage of the library. |
18,081 | import numpy as np
def approximate_mode(class_counts, n_draws, rng):
"""Computes approximate mode of multivariate hypergeometric.
This is an approximation to the mode of the multivariate
hypergeometric given by class_counts and n_draws.
It shouldn't be off by more than one.
It is the mostly likely o... | Provides train/test indices to split data in train/test sets. It's reference is taken from StratifiedShuffleSplit implementation of scikit-learn library. Args ---------- n_train : int, represents the absolute number of train samples. n_test : int, represents the absolute number of test samples. random_state : int or Ra... |
18,082 | import os
import sys
from io import BytesIO
from types import CodeType, FunctionType
import dill
from packaging import version
from .. import config
class Pickler(dill.Pickler):
dispatch = dill._dill.MetaCatchingDict(dill.Pickler.dispatch.copy())
_legacy_no_dict_keys_sorting = False
def save(self, obj, save... | Register a custom reducer for the type. |
18,083 | import os
import sys
from io import BytesIO
from types import CodeType, FunctionType
import dill
from packaging import version
from .. import config
def dump(obj, file):
"""Pickle an object to a file."""
Pickler(file, recurse=True).dump(obj)
The provided code snippet includes necessary dependencies for impleme... | Pickle an object to a string. |
18,084 | import os
import sys
from io import BytesIO
from types import CodeType, FunctionType
import dill
from packaging import version
from .. import config
if config.DILL_VERSION < version.parse("0.3.6"):
def log(pickler, msg):
dill._dill.log.info(msg)
elif config.DILL_VERSION.release[:3] in [
version.parse("0... | null |
18,085 | import os
import sys
from io import BytesIO
from types import CodeType, FunctionType
import dill
from packaging import version
from .. import config
if config.DILL_VERSION < version.parse("0.3.6"):
def log(pickler, msg):
dill._dill.log.info(msg)
elif config.DILL_VERSION.release[:3] in [
version.parse("0... | null |
18,086 | import os
import sys
from io import BytesIO
from types import CodeType, FunctionType
import dill
from packaging import version
from .. import config
if config.DILL_VERSION < version.parse("0.3.6"):
def log(pickler, msg):
elif config.DILL_VERSION.release[:3] in [
version.parse("0.3.6").release,
version.parse... | null |
18,087 | import os
import sys
from io import BytesIO
from types import CodeType, FunctionType
import dill
from packaging import version
from .. import config
if config.DILL_VERSION < version.parse("0.3.6"):
def log(pickler, msg):
dill._dill.log.info(msg)
elif config.DILL_VERSION.release[:3] in [
version.parse("0... | null |
18,088 | import os
import sys
from io import BytesIO
from types import CodeType, FunctionType
import dill
from packaging import version
from .. import config
if config.DILL_VERSION < version.parse("0.3.6"):
def log(pickler, msg):
elif config.DILL_VERSION.release[:3] in [
version.parse("0.3.6").release,
version.parse... | null |
18,089 | import os
import sys
from io import BytesIO
from types import CodeType, FunctionType
import dill
from packaging import version
from .. import config
if config.DILL_VERSION < version.parse("0.3.6"):
def log(pickler, msg):
dill._dill.log.info(msg)
elif config.DILL_VERSION.release[:3] in [
version.parse("0... | null |
18,090 | import os
import sys
from io import BytesIO
from types import CodeType, FunctionType
import dill
from packaging import version
from .. import config
if config.DILL_VERSION < version.parse("0.3.6"):
def log(pickler, msg):
dill._dill.log.info(msg)
elif config.DILL_VERSION.release[:3] in [
version.parse("0... | null |
18,091 | import os
import sys
from io import BytesIO
from types import CodeType, FunctionType
import dill
from packaging import version
from .. import config
if config.DILL_VERSION < version.parse("0.3.6"):
def log(pickler, msg):
dill._dill.log.info(msg)
elif config.DILL_VERSION.release[:3] in [
version.parse("0... | From dill._dill.save_code This is a modified version that removes the origin (filename + line no.) of functions created in notebooks or shells for example. |
18,092 | import os
import sys
from io import BytesIO
from types import CodeType, FunctionType
import dill
from packaging import version
from .. import config
def save_code(pickler, obj):
dill._dill.logger.trace(pickler, "Co: %s", obj)
############################################################################... | null |
18,093 | import copy
import functools
import itertools
import multiprocessing.pool
import os
import queue
import re
import types
import warnings
from contextlib import contextmanager
from dataclasses import fields, is_dataclass
from multiprocessing import Manager
from pathlib import Path
from queue import Empty
from shutil impo... | Returns a human readable size string. If size_in_bytes is None, then returns "Unknown size". For example `size_str(1.5 * datasets.units.GiB) == "1.50 GiB"`. Args: size_in_bytes: `int` or `None`, the size, in bytes, that we want to format as a human-readable size string. |
18,094 | import copy
import functools
import itertools
import multiprocessing.pool
import os
import queue
import re
import types
import warnings
from contextlib import contextmanager
from dataclasses import fields, is_dataclass
from multiprocessing import Manager
from pathlib import Path
from queue import Empty
from shutil impo... | Converts a size expressed as a string with digits an unit (like `"50MB"`) to an integer (in bytes). Args: size (`int` or `str`): The size to convert. Will be directly returned if an `int`. Example: ```py >>> convert_file_size_to_int("1MiB") 1048576 ``` |
18,095 | import copy
import functools
import itertools
import multiprocessing.pool
import os
import queue
import re
import types
import warnings
from contextlib import contextmanager
from dataclasses import fields, is_dataclass
from multiprocessing import Manager
from pathlib import Path
from queue import Empty
from shutil impo... | Temporarily assign obj.attr to value. |
18,096 | import copy
import functools
import itertools
import multiprocessing.pool
import os
import queue
import re
import types
import warnings
from contextlib import contextmanager
from dataclasses import fields, is_dataclass
from multiprocessing import Manager
from pathlib import Path
from queue import Empty
from shutil impo... | Temporarily set the random seed. This works for python numpy, pytorch and tensorflow. |
18,097 | import copy
import functools
import itertools
import multiprocessing.pool
import os
import queue
import re
import types
import warnings
from contextlib import contextmanager
from dataclasses import fields, is_dataclass
from multiprocessing import Manager
from pathlib import Path
from queue import Empty
from shutil impo... | Apply a function recursively to each element of a nested data struct. Use multiprocessing if num_proc > 1 and the length of data_struct is greater than or equal to `parallel_min_length`. <Changed version="2.5.0"> Before version 2.5.0, multiprocessing was not used if `num_proc` was greater than or equal to ``len(iterabl... |
18,098 | import copy
import functools
import itertools
import multiprocessing.pool
import os
import queue
import re
import types
import warnings
from contextlib import contextmanager
from dataclasses import fields, is_dataclass
from multiprocessing import Manager
from pathlib import Path
from queue import Empty
from shutil impo... | null |
18,099 | import copy
import functools
import itertools
import multiprocessing.pool
import os
import queue
import re
import types
import warnings
from contextlib import contextmanager
from dataclasses import fields, is_dataclass
from multiprocessing import Manager
from pathlib import Path
from queue import Empty
from shutil impo... | null |
18,100 | import copy
import functools
import itertools
import multiprocessing.pool
import os
import queue
import re
import types
import warnings
from contextlib import contextmanager
from dataclasses import fields, is_dataclass
from multiprocessing import Manager
from pathlib import Path
from queue import Empty
from shutil impo... | null |
18,101 | 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/tree/main/src/datasets/utils"
def load_yaml_resource(resource: st... | null |
18,102 | import warnings
from tqdm.auto import tqdm as old_tqdm
from ..config import HF_DATASETS_DISABLE_PROGRESS_BARS
_hf_datasets_progress_bars_disabled: bool = HF_DATASETS_DISABLE_PROGRESS_BARS or False
HF_DATASETS_DISABLE_PROGRESS_BARS: Optional[bool] = (
__HF_DATASETS_DISABLE_PROGRESS_BARS.upper() in ENV_VARS_TRUE_VAL... | Disable globally progress bars used in `datasets` except if `HF_DATASETS_DISABLE_PROGRESS_BAR` environment variable has been set. Use [`~utils.enable_progress_bars`] to re-enable them. |
18,103 | import warnings
from tqdm.auto import tqdm as old_tqdm
from ..config import HF_DATASETS_DISABLE_PROGRESS_BARS
_hf_datasets_progress_bars_disabled: bool = HF_DATASETS_DISABLE_PROGRESS_BARS or False
HF_DATASETS_DISABLE_PROGRESS_BARS: Optional[bool] = (
__HF_DATASETS_DISABLE_PROGRESS_BARS.upper() in ENV_VARS_TRUE_VAL... | Enable globally progress bars used in `datasets` except if `HF_DATASETS_DISABLE_PROGRESS_BAR` environment variable has been set. Use [`~utils.disable_progress_bars`] to disable them. |
18,104 | import warnings
from tqdm.auto import tqdm as old_tqdm
from ..config import HF_DATASETS_DISABLE_PROGRESS_BARS
def are_progress_bars_disabled() -> bool:
"""Return whether progress bars are globally disabled or not.
Progress bars used in `datasets` can be enable or disabled globally using [`~utils.enable_progress... | null |
18,105 | 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 UnexpectedDownloadedFile(ChecksumVerificationException):
"""Some downloaded files were not expected."""
class ExpectedMoreDow... | null |
18,106 | 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 UnexpectedSplits(SplitsVerificationException):
"""The expected splits of the downloaded file is missing."""
class ExpectedMor... | null |
18,107 | import enum
import os
from typing import Optional
from huggingface_hub.utils import insecure_hashlib
from .. import config
from .logging import get_logger
The provided code snippet includes necessary dependencies for implementing the `get_size_checksum_dict` function. Write a Python function `def get_size_checksum_dic... | Compute the file size and the sha256 checksum of a file |
18,108 | 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 shardi... | Split the gen_kwargs into `max_num_job` gen_kwargs |
18,109 | from typing import List
import numpy as np
def _merge_gen_kwargs(gen_kwargs_list: List[dict]) -> dict:
return {
key: [value for gen_kwargs in gen_kwargs_list for value in gen_kwargs[key]]
if isinstance(gen_kwargs_list[0][key], list)
else gen_kwargs_list[0][key]
for key in gen_kwargs... | null |
18,110 | from typing import List
import numpy as np
The provided code snippet includes necessary dependencies for implementing the `_shuffle_gen_kwargs` function. Write a Python function `def _shuffle_gen_kwargs(rng: np.random.Generator, gen_kwargs: dict) -> dict` to solve the following problem:
Return a shuffled copy of the i... | Return a shuffled copy of the input gen_kwargs |
18,111 | import re
import textwrap
from collections import Counter
from itertools import groupby
from operator import itemgetter
from pathlib import Path
from typing import Any, ClassVar, Dict, List, Optional, Tuple, Union
import yaml
from huggingface_hub import DatasetCardData
from ..config import METADATA_CONFIGS_FIELD
from .... | null |
18,112 | import warnings
from functools import wraps
from typing import Callable
The provided code snippet includes necessary dependencies for implementing the `experimental` function. Write a Python function `def experimental(fn: Callable) -> Callable` to solve the following problem:
Decorator to flag a feature as experimenta... | Decorator to flag a feature as experimental. An experimental feature trigger a warning when used as it might be subject to breaking changes in the future. Args: fn (`Callable`): The function to flag as experimental. Returns: `Callable`: The decorated function. Example: ```python >>> from datasets.utils import experimen... |
18,113 | import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def get_duration(func):
def wrapper(*args, **kwargs):
starttime = timeit.default_timer()
_ = func(*args, **kwargs)
delta = timeit.default_timer() - ... | null |
18,114 | import json
import os
import tempfile
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features import Array2D
from utils import generate_examples, get_duration
SPEED_TEST_SHAPE = (100, 100)
SPEED_TEST_N_EXAMPLES = 100
RESULTS_FILE_PATH = os.path.join(RESULTS_BASEPATH, "results", RESULTS_FILE... | null |
18,115 | import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
SPEED_TEST_N_EXAMPLES = 500_000
RESULTS_FILE_PATH = os.path.join(RESULTS_BASEPATH, "results", RESULTS_FILENAME.replace(".py", ".json"))
def map(dataset: datasets.Dataset, **kwargs):
_ =... | null |
18,116 | import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
SPEED_TEST_N_EXAMPLES = 500_000
RESULTS_FILE_PATH = os.path.join(RESULTS_BASEPATH, "results", RESULTS_FILENAME.replace(".py", ".json"))
def select(dataset: datasets.Dataset):
_ = dataset.select(range(0, le... | null |
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