

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


__UpperCAmelCase    				=     logging.get_logger(__name__)


__UpperCAmelCase    				=     TypeVar('DatasetType', Dataset, IterableDataset)







def 	_snake_case		(    SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE = None		,							SCREAMING_SNAKE_CASE = None		,							SCREAMING_SNAKE_CASE = None		,							SCREAMING_SNAKE_CASE = None		,							SCREAMING_SNAKE_CASE = "first_exhausted"		,							)       ->      DatasetType:

     """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(SCREAMING_SNAKE_CASE				):
          if not isinstance(SCREAMING_SNAKE_CASE		,							(Dataset, IterableDataset)				):
               if isinstance(SCREAMING_SNAKE_CASE		,							(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(SCREAMING_SNAKE_CASE				)}\n'''
                        f'''Please pick one to interleave with the other datasets, for example: dataset[\'{next(iter(SCREAMING_SNAKE_CASE				)				)}\']'''				)
               raise ValueError(
                   f'''Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(SCREAMING_SNAKE_CASE				).__name__}.'''				)
          if i == 0:
               _lowerCAmelCase   :					Union[str, Any]        =    (
                   (Dataset, IterableDataset) if isinstance(SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE				) else (IterableDataset, Dataset)
               )
          elif not isinstance(SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE				):
               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(
              SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE		,							info=SCREAMING_SNAKE_CASE		,							split=SCREAMING_SNAKE_CASE		,							stopping_strategy=SCREAMING_SNAKE_CASE				)
     else:
          return _interleave_iterable_datasets(
              SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE		,							info=SCREAMING_SNAKE_CASE		,							split=SCREAMING_SNAKE_CASE		,							stopping_strategy=SCREAMING_SNAKE_CASE				)







def 	_snake_case		(    SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE = None		,							SCREAMING_SNAKE_CASE = None		,							SCREAMING_SNAKE_CASE = 0		,							)       ->      DatasetType:

     """simple docstring"""







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









import unittest

from transformers import load_tool

from .test_tools_common import ToolTesterMixin


__UpperCAmelCase    				=     '\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot app targeted at teenagers.[2] After open-sourcing the model behind the chatbot, the company pivoted to focus on being a platform for machine learning.\n\nIn March 2021, Hugging Face raised $40 million in a Series B funding round.[3]\n\nOn April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model.[4] In 2022, the workshop concluded with the announcement of BLOOM, a multilingual large language model with 176 billion parameters.[5]\n'





class A__    ( unittest.TestCase  ,		A ):



 """simple docstring"""







 def    __magic_name__       (		self :	Tuple       ):






      '''simple docstring'''




      _lowerCAmelCase   :					Dict        =    load_tool("text-question-answering"       )
      self.tool.setup()
      _lowerCAmelCase   :					int        =    load_tool("text-question-answering"     ,						remote=A_       )

 def    __magic_name__       (		self :	List[str]       ):






      '''simple docstring'''




      _lowerCAmelCase   :					Dict        =    self.tool(A_     ,						"What did Hugging Face do in April 2021?"       )
      self.assertEqual(A_     ,						"launched the BigScience Research Workshop"       )

 def    __magic_name__       (		self :	Tuple       ):






      '''simple docstring'''




      _lowerCAmelCase   :					int        =    self.remote_tool(A_     ,						"What did Hugging Face do in April 2021?"       )
      self.assertEqual(A_     ,						"launched the BigScience Research Workshop"       )

 def    __magic_name__       (		self :	Dict       ):






      '''simple docstring'''




      _lowerCAmelCase   :					Union[str, Any]        =    self.tool(text=A_     ,						question="What did Hugging Face do in April 2021?"       )
      self.assertEqual(A_     ,						"launched the BigScience Research Workshop"       )


 def    __magic_name__       (		self :	Optional[Any]       ):






      '''simple docstring'''




      _lowerCAmelCase   :					Optional[int]        =    self.remote_tool(text=A_     ,						question="What did Hugging Face do in April 2021?"       )
      self.assertEqual(A_     ,						"launched the BigScience Research Workshop"       )






