
'''simple docstring'''

# 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/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ..models.auto import AutoModelForVisionaSeq
from ..utils import requires_backends
from .base import PipelineTool


if TYPE_CHECKING:
    from PIL import Image


class  _UpperCAmelCase ( UpperCamelCase__    ):

     """simple docstring"""

     a_    	=					"Salesforce/blip-image-captioning-base"
     a_    	=					(
         "This is a tool that generates a description of an image. It takes an input named `image` which should be the "
         "image to caption, and returns a text that contains the description in English."
     )
     a_    	=					"image_captioner"
     a_    	=					AutoModelForVisionaSeq

     a_    	=					["image"]
     a_    	=					["text"]


     def __init__(      self							,		*lowerCAmelCase_							,		**lowerCAmelCase_ ):

       '''simple docstring'''

       requires_backends(self							,		["""vision"""] )
       super().__init__(*__A							,		**__A )


     def 							_lowerCAmelCase  (      self							,		lowerCAmelCase_ ):

       '''simple docstring'''

       return self.pre_processor(images=__A							,		return_tensors="""pt""" )


     def 							_lowerCAmelCase  (      self							,		lowerCAmelCase_ ):

       '''simple docstring'''

       return self.model.generate(**__A )






     def 							_lowerCAmelCase  (      self							,		lowerCAmelCase_ ):

       '''simple docstring'''

       return self.pre_processor.batch_decode(__A							,		skip_special_tokens=__A )[0].strip()

'''simple docstring'''

from typing import List, Optional, TypeVar

from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _interleave_iterable_datasets
from .splits import NamedSplit
from .utils import logging
from .utils.py_utils import Literal


__snake_case:  Optional[Any]								=			logging.get_logger(__name__)


__snake_case:  Tuple								=			TypeVar("DatasetType", Dataset, IterableDataset)






def 	_snake_case						(      A_       :    List[DatasetType]     ,		A_       :    Optional[List[float]] = None     ,		A_       :    Optional[int] = None     ,		A_       :    Optional[DatasetInfo] = None     ,		A_       :    Optional[NamedSplit] = None     ,		A_       :    Literal["first_exhausted", "all_exhausted"] = "first_exhausted"     ,		):
  """simple docstring"""







  from .arrow_dataset import Dataset
  from .iterable_dataset import IterableDataset

  if not datasets:
    raise ValueError("""Unable to interleave an empty list of datasets."""   )
  for i, dataset in enumerate(A_   ):
    if not isinstance(A_     ,		(Dataset, IterableDataset)   ):
      if isinstance(A_     ,		(DatasetDict, IterableDatasetDict)   ):
        if not dataset:
          raise ValueError(
              f'''Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} '''
              """is an empty dataset dictionary."""   )
        raise ValueError(
            f'''Dataset at position {i} has at least one split: {list(A_   )}\n'''
            f'''Please pick one to interleave with the other datasets, for example: dataset[\'{next(iter(A_   )   )}\']'''   )
      raise ValueError(
          f'''Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(A_   ).__name__}.'''   )
    if i == 0:
      a_      , a_      :	Union[str, Any]      =							(
          (Dataset, IterableDataset) if isinstance(A_     ,		A_   ) else (IterableDataset, Dataset)
      )
    elif not isinstance(A_     ,		A_   ):
      raise ValueError(
          f'''Unable to interleave a {dataset_type.__name__} (at position 0) with a {other_type.__name__} (at position {i}). Expected a list of Dataset objects or a list of IterableDataset objects.'''   )
  if stopping_strategy not in ["first_exhausted", "all_exhausted"]:
    raise ValueError(f'''{stopping_strategy} is not supported. Please enter a valid stopping_strategy.'''   )
  if dataset_type is Dataset:
    return _interleave_map_style_datasets(
        A_     ,		A_     ,		A_     ,		info=A_     ,		split=A_     ,		stopping_strategy=A_   )
  else:
    return _interleave_iterable_datasets(
        A_     ,		A_     ,		A_     ,		info=A_     ,		split=A_     ,		stopping_strategy=A_   )






def 	_snake_case						(      A_       :    List[DatasetType]     ,		A_       :    Optional[DatasetInfo] = None     ,		A_       :    Optional[NamedSplit] = None     ,		A_       :    int = 0     ,		):
  """simple docstring"""







  if not dsets:
    raise ValueError("""Unable to concatenate an empty list of datasets."""   )
  for i, dataset in enumerate(A_   ):
    if not isinstance(A_     ,		(Dataset, IterableDataset)   ):
      if isinstance(A_     ,		(DatasetDict, IterableDatasetDict)   ):
        if not dataset:
          raise ValueError(
              f'''Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} '''
              """is an empty dataset dictionary."""   )
        raise ValueError(
            f'''Dataset at position {i} has at least one split: {list(A_   )}\n'''
            f'''Please pick one to interleave with the other datasets, for example: dataset[\'{next(iter(A_   )   )}\']'''   )
      raise ValueError(
          f'''Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(A_   ).__name__}.'''   )
    if i == 0:
      a_      , a_      :	str      =							(
          (Dataset, IterableDataset) if isinstance(A_     ,		A_   ) else (IterableDataset, Dataset)
      )
    elif not isinstance(A_     ,		A_   ):
      raise ValueError(
          f'''Unable to interleave a {dataset_type.__name__} (at position 0) with a {other_type.__name__} (at position {i}). Expected a list of Dataset objects or a list of IterableDataset objects.'''   )
  if dataset_type is Dataset:
    return _concatenate_map_style_datasets(A_     ,		info=A_     ,		split=A_     ,		axis=A_   )
  else:
    return _concatenate_iterable_datasets(A_     ,		info=A_     ,		split=A_     ,		axis=A_   )


