'''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


SCREAMING_SNAKE_CASE_:					Tuple  =logging.get_logger(__name__)


SCREAMING_SNAKE_CASE_:					Dict  =TypeVar('DatasetType', Dataset, IterableDataset)





def      lowerCAmelCase_    ( snake_case_	:			List[DatasetType] ,   snake_case_	:			Optional[List[float]] = None ,   snake_case_	:			Optional[int] = None ,   snake_case_	:			Optional[DatasetInfo] = None ,   snake_case_	:			Optional[NamedSplit] = None ,   snake_case_	:			Literal["first_exhausted", "all_exhausted"] = "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(snake_case_      ):
          if not isinstance(snake_case_ ,   (Dataset, IterableDataset)      ):
               if isinstance(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(snake_case_      )}\n"""
                        f"""Please pick one to interleave with the other datasets, for example: dataset['{next(iter(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(snake_case_      ).__name__}."""      )
          if i == 0:
               UpperCAmelCase_   ,			UpperCAmelCase_	   =       (
                   (Dataset, IterableDataset) if isinstance(snake_case_ ,   snake_case_      ) else (IterableDataset, Dataset)
               )
          elif not isinstance(snake_case_ ,   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(
              snake_case_ ,   snake_case_ ,   snake_case_ ,   info=snake_case_ ,   split=snake_case_ ,   stopping_strategy=snake_case_      )
     else:
          return _interleave_iterable_datasets(
              snake_case_ ,   snake_case_ ,   snake_case_ ,   info=snake_case_ ,   split=snake_case_ ,   stopping_strategy=snake_case_      )






def      lowerCAmelCase_    ( snake_case_	:			List[DatasetType] ,   snake_case_	:			Optional[DatasetInfo] = None ,   snake_case_	:			Optional[NamedSplit] = None ,   snake_case_	:			int = 0 ,   )   ->				DatasetType:


     '''simple docstring'''




     if not dsets:
          raise ValueError("Unable to concatenate an empty list of datasets."      )
     for i, dataset in enumerate(snake_case_      ):
          if not isinstance(snake_case_ ,   (Dataset, IterableDataset)      ):
               if isinstance(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(snake_case_      )}\n"""
                        f"""Please pick one to interleave with the other datasets, for example: dataset['{next(iter(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(snake_case_      ).__name__}."""      )
          if i == 0:
               UpperCAmelCase_   ,			UpperCAmelCase_	   =       (
                   (Dataset, IterableDataset) if isinstance(snake_case_ ,   snake_case_      ) else (IterableDataset, Dataset)
               )
          elif not isinstance(snake_case_ ,   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(snake_case_ ,   info=snake_case_ ,   split=snake_case_ ,   axis=snake_case_      )
     else:
          return _concatenate_iterable_datasets(snake_case_ ,   info=snake_case_ ,   split=snake_case_ ,   axis=snake_case_      )





'''simple docstring'''





import unittest

from transformers import load_tool
from transformers.utils import is_torch_available


if is_torch_available():
    import torch

from transformers.testing_utils import require_torch

from .test_tools_common import ToolTesterMixin




@require_torch
class 	__A				(			unittest.TestCase		,     UpperCamelCase__     ):



    def  _lowercase						(self   :   Tuple			):
         UpperCAmelCase_	   =       load_tool("text-to-speech"			)
         self.tool.setup()



    def  _lowercase						(self   :   Union[str, Any]			):
         # SpeechT5 isn't deterministic
         torch.manual_seed(0			)
         UpperCAmelCase_	   =       self.tool("hey"			)
         UpperCAmelCase_	   =       result.to_raw()
         self.assertTrue(
             torch.allclose(
                 resulting_tensor[:3]       ,      torch.tensor([-0.0_00_59_66_66_88_32_11_58_29, -0.0_00_36_57_64_01_90_79_50_64, -0.00_01_34_39_50_27_99_88_34_85]			)       ,      )			)






    def  _lowercase						(self   :   List[str]			):
         # SpeechT5 isn't deterministic
         torch.manual_seed(0			)
         UpperCAmelCase_	   =       self.tool("hey"			)
         UpperCAmelCase_	   =       result.to_raw()
         self.assertTrue(
             torch.allclose(
                 resulting_tensor[:3]       ,      torch.tensor([-0.0_00_59_66_66_88_32_11_58_29, -0.0_00_36_57_64_01_90_79_50_64, -0.00_01_34_39_50_27_99_88_34_85]			)       ,      )			)




