






"""simple docstring"""






from typing import List

import datasets
from datasets.tasks import AudioClassification

from ..folder_based_builder import folder_based_builder


UpperCAmelCase_   : Optional[Any]   			= datasets.utils.logging.get_logger(__name__)




class 							lowerCAmelCase__				(			folder_based_builder.FolderBasedBuilderConfig ):






      '''simple docstring'''

      __UpperCamelCase	 =  None
      __UpperCamelCase	 =  None




class 							lowerCAmelCase__				(			folder_based_builder.FolderBasedBuilder ):






      '''simple docstring'''

      __UpperCamelCase	 =  datasets.Audio()
      __UpperCamelCase	 =  'audio'
      __UpperCamelCase	 =  AudioFolderConfig
      __UpperCamelCase	 =  42  # definition at the bottom of the script
      __UpperCamelCase	 =  AudioClassification(audio_column="audio"				,		label_column="label" )



UpperCAmelCase_   : Any   			= [
    ".aiff",
    ".au",
    ".avr",
    ".caf",
    ".flac",
    ".htk",
    ".svx",
    ".mat4",
    ".mat5",
    ".mpc2k",
    ".ogg",
    ".paf",
    ".pvf",
    ".raw",
    ".rf64",
    ".sd2",
    ".sds",
    ".ircam",
    ".voc",
    ".w64",
    ".wav",
    ".nist",
    ".wavex",
    ".wve",
    ".xi",
    ".mp3",
    ".opus",
]
UpperCAmelCase_   : Union[str, Any]   			= AUDIO_EXTENSIONS







"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A:   List[str]								=		{
    "configuration_clipseg": [
        "CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "CLIPSegConfig",
        "CLIPSegTextConfig",
        "CLIPSegVisionConfig",
    ],
    "processing_clipseg": ["CLIPSegProcessor"],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A:   Optional[int]								=		[
          "CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST",
          "CLIPSegModel",
          "CLIPSegPreTrainedModel",
          "CLIPSegTextModel",
          "CLIPSegVisionModel",
          "CLIPSegForImageSegmentation",
      ]

if TYPE_CHECKING:
      from .configuration_clipseg import (
          CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP,
          CLIPSegConfig,
          CLIPSegTextConfig,
          CLIPSegVisionConfig,
      )
      from .processing_clipseg import CLIPSegProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_clipseg import (
                CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST,
                CLIPSegForImageSegmentation,
                CLIPSegModel,
                CLIPSegPreTrainedModel,
                CLIPSegTextModel,
                CLIPSegVisionModel,
            )

else:
      import sys

      A:   Tuple								=		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
