





"""simple docstring"""
import warnings
from typing import List, Optional, Union

from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType




class        __snake_case	(					UpperCAmelCase__    ):
      a__				=		['image_processor', 'tokenizer']
      a__				=		'FlavaImageProcessor'
      a__				=		('BertTokenizer', 'BertTokenizerFast')



      def __init__(						self   ,      lowercase=None   ,      lowercase=None   ,      **lowercase)     ->      str:





        '''simple docstring'''





        a__:					Union[str, Any]      							=     None
        if "feature_extractor" in kwargs:
          warnings.warn(
              'The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'
              ' instead.'   ,      _SCREAMING_SNAKE_CASE   ,      )
          a__:					Optional[Any]      							=     kwargs.pop('feature_extractor')

        a__:					Tuple      							=     image_processor if image_processor is not None else feature_extractor
        if image_processor is None:
          raise ValueError('You need to specify an `image_processor`.')
        if tokenizer is None:
          raise ValueError('You need to specify a `tokenizer`.')

        super().__init__(_SCREAMING_SNAKE_CASE   ,      _SCREAMING_SNAKE_CASE)
        a__:					Any      							=     self.image_processor



      def __call__(						self   ,      lowercase = None   ,      lowercase = None   ,      lowercase = True   ,      lowercase = False   ,      lowercase = False   ,      lowercase = None   ,      lowercase = 0   ,      lowercase = None   ,      lowercase = None   ,      lowercase = None   ,      lowercase = None   ,      lowercase = None   ,      lowercase = False   ,      lowercase = False   ,      lowercase = False   ,      lowercase = False   ,      lowercase = True   ,      lowercase = None   ,      **lowercase   ,      )     ->      Optional[Any]:





        '''simple docstring'''





        if text is None and images is None:
          raise ValueError('You have to specify either text or images. Both cannot be none.')

        if text is not None:
          a__:					Optional[Any]      							=     self.tokenizer(
              text=_SCREAMING_SNAKE_CASE   ,      add_special_tokens=_SCREAMING_SNAKE_CASE   ,      padding=_SCREAMING_SNAKE_CASE   ,      truncation=_SCREAMING_SNAKE_CASE   ,      max_length=_SCREAMING_SNAKE_CASE   ,      stride=_SCREAMING_SNAKE_CASE   ,      pad_to_multiple_of=_SCREAMING_SNAKE_CASE   ,      return_token_type_ids=_SCREAMING_SNAKE_CASE   ,      return_attention_mask=_SCREAMING_SNAKE_CASE   ,      return_overflowing_tokens=_SCREAMING_SNAKE_CASE   ,      return_special_tokens_mask=_SCREAMING_SNAKE_CASE   ,      return_offsets_mapping=_SCREAMING_SNAKE_CASE   ,      return_length=_SCREAMING_SNAKE_CASE   ,      verbose=_SCREAMING_SNAKE_CASE   ,      return_tensors=_SCREAMING_SNAKE_CASE   ,      **_SCREAMING_SNAKE_CASE   ,      )
        if images is not None:
          a__:					List[str]      							=     self.image_processor(
              _SCREAMING_SNAKE_CASE   ,      return_image_mask=_SCREAMING_SNAKE_CASE   ,      return_codebook_pixels=_SCREAMING_SNAKE_CASE   ,      return_tensors=_SCREAMING_SNAKE_CASE   ,      **_SCREAMING_SNAKE_CASE   ,      )

        if text is not None and images is not None:
          encoding.update(_SCREAMING_SNAKE_CASE)
          return encoding
        elif text is not None:
          return encoding
        else:
          return BatchEncoding(data=dict(**_SCREAMING_SNAKE_CASE)   ,      tensor_type=_SCREAMING_SNAKE_CASE)



      def   lowerCamelCase_       (						self   ,      *lowercase   ,      **lowercase)     ->      List[Any]:





        '''simple docstring'''





        return self.tokenizer.batch_decode(*_SCREAMING_SNAKE_CASE   ,      **_SCREAMING_SNAKE_CASE)



      def   lowerCamelCase_       (						self   ,      *lowercase   ,      **lowercase)     ->      List[Any]:





        '''simple docstring'''





        return self.tokenizer.decode(*_SCREAMING_SNAKE_CASE   ,      **_SCREAMING_SNAKE_CASE)



      @property
      def   lowerCamelCase_       (						self)     ->      int:





        '''simple docstring'''





        a__:					Union[str, Any]      							=     self.tokenizer.model_input_names
        a__:					Optional[Any]      							=     self.image_processor.model_input_names
        return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names))



      @property
      def   lowerCamelCase_       (						self)     ->      int:





        '''simple docstring'''





        warnings.warn(
            '`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'   ,      _SCREAMING_SNAKE_CASE   ,      )
        return self.image_processor_class



      @property
      def   lowerCamelCase_       (						self)     ->      List[Any]:





        '''simple docstring'''





        warnings.warn(
            '`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'   ,      _SCREAMING_SNAKE_CASE   ,      )
        return self.image_processor



"""simple docstring"""
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position

lowercase__ 	=     '2.13.1'

import platform

import pyarrow
from packaging import version


if version.parse(platform.python_version()) < version.parse('3.7'):
 raise ImportWarning(
     'To use `datasets`, Python>=3.7 is required, and the current version of Python doesn\'t match this condition.'
 )

if version.parse(pyarrow.__version__).major < 8:
 raise ImportWarning(
     'To use `datasets`, the module `pyarrow>=8.0.0` is required, and the current version of `pyarrow` doesn\'t match this condition.\n'
     'If you are running this in a Google Colab, you should probably just restart the runtime to use the right version of `pyarrow`.'
 )

del platform
del pyarrow
del version

from .arrow_dataset import Dataset
from .arrow_reader import ReadInstruction
from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
from .combine import concatenate_datasets, interleave_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .download import *
from .features import *
from .fingerprint import disable_caching, enable_caching, is_caching_enabled, set_caching_enabled
from .info import DatasetInfo, MetricInfo
from .inspect import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
    list_datasets,
    list_metrics,
)
from .iterable_dataset import IterableDataset
from .load import load_dataset, load_dataset_builder, load_from_disk, load_metric
from .metric import Metric
from .splits import (
    NamedSplit,
    NamedSplitAll,
    Split,
    SplitBase,
    SplitDict,
    SplitGenerator,
    SplitInfo,
    SubSplitInfo,
    percent,
)
from .tasks import *
from .utils import *
from .utils import logging


# deprecated modules
from datasets import arrow_dataset as _arrow_dataset  # isort:skip
from datasets import utils as _utils  # isort:skip
from datasets.utils import download_manager as _deprecated_download_manager  # isort:skip

lowercase__ 	=     concatenate_datasets
lowercase__ 	=     DownloadConfig
lowercase__ 	=     DownloadManager
lowercase__ 	=     DownloadMode
lowercase__ 	=     DownloadConfig
lowercase__ 	=     DownloadMode
lowercase__ 	=     DownloadManager

del _arrow_dataset, _utils, _deprecated_download_manager


