

from typing import Callable, Optional

from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream






class _UpperCamelCase				(				__A ):
			'''simple docstring'''







			def __init__(      self				:			int   ,   a				:			Callable   ,   a				:			Optional[Features] = None   ,   a				:			str = None   ,   a				:			bool = False   ,   a				:			bool = False   ,   a				:			Optional[dict] = None   ,   a				:			Optional[int] = None   ,   **a				:			Union[str, Any]   ,   )				->							int:

				"""simple docstring"""

				super().__init__(
				    features=a   ,   cache_dir=a   ,   keep_in_memory=a   ,   streaming=a   ,   num_proc=a   ,   **a   ,   )
				SCREAMING_SNAKE_CASE :   Tuple					  =							Generator(
				    cache_dir=a   ,   features=a   ,   generator=a   ,   gen_kwargs=a   ,   **a   ,   )






			def 				__UpperCamelCase			(      self				:			Any						)				->							Union[str, Any]:

				"""simple docstring"""

				if self.streaming:
					SCREAMING_SNAKE_CASE :   Dict					  =							self.builder.as_streaming_dataset(split="train"						)
				# Build regular (map-style) dataset
				else:
					SCREAMING_SNAKE_CASE :   Optional[Any]					  =							None
					SCREAMING_SNAKE_CASE :   Optional[Any]					  =							None
					SCREAMING_SNAKE_CASE :   Optional[Any]					  =							None
					SCREAMING_SNAKE_CASE :   Any					  =							None

					self.builder.download_and_prepare(
					    download_config=a   ,   download_mode=a   ,   verification_mode=a   ,   base_path=a   ,   num_proc=self.num_proc   ,   )
					SCREAMING_SNAKE_CASE :   int					  =							self.builder.as_dataset(
					    split="train"   ,   verification_mode=a   ,   in_memory=self.keep_in_memory						)
				return dataset



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


SCREAMING_SNAKE_CASE						:str			=  {'''configuration_unispeech''': ['''UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''UniSpeechConfig''']}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE						:List[str]			=  [
       '''UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''UniSpeechForCTC''',
       '''UniSpeechForPreTraining''',
       '''UniSpeechForSequenceClassification''',
       '''UniSpeechModel''',
       '''UniSpeechPreTrainedModel''',
   ]

if TYPE_CHECKING:
   from .configuration_unispeech import UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_unispeech import (
          UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST,
          UniSpeechForCTC,
          UniSpeechForPreTraining,
          UniSpeechForSequenceClassification,
          UniSpeechModel,
          UniSpeechPreTrainedModel,
      )

else:
   import sys

   SCREAMING_SNAKE_CASE						:List[str]			=  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




