
from typing import List

import datasets
from datasets.tasks import AudioClassification

from ..folder_based_builder import folder_based_builder


lowerCamelCase__	=							datasets.utils.logging.get_logger(__name__)







class        lowerCAmelCase__      (   folder_based_builder.FolderBasedBuilderConfig	):
						UpperCamelCase_							: bool	=		None
						UpperCamelCase_							: bool	=		None







class        lowerCAmelCase__      (   folder_based_builder.FolderBasedBuilder	):
						UpperCamelCase_							: Tuple	=		datasets.Audio()
						UpperCamelCase_							: Tuple	=		"audio"
						UpperCamelCase_							: str	=		AudioFolderConfig
						UpperCamelCase_							: List[str]  # definition at the bottom of the script
						UpperCamelCase_							: int	=		AudioClassification(audio_column="audio"		,	label_column="label"	)




lowerCamelCase__	=							[
    ".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",
]
lowerCamelCase__	=							AUDIO_EXTENSIONS





from typing import TYPE_CHECKING

from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase__	=							{
    "configuration_mctct": ["MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MCTCTConfig"],
    "feature_extraction_mctct": ["MCTCTFeatureExtractor"],
    "processing_mctct": ["MCTCTProcessor"],
}


try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCamelCase__	=							[
		    "MCTCT_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "MCTCTForCTC",
		    "MCTCTModel",
		    "MCTCTPreTrainedModel",
		]


if TYPE_CHECKING:
		from .configuration_mctct import MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP, MCTCTConfig
		from .feature_extraction_mctct import MCTCTFeatureExtractor
		from .processing_mctct import MCTCTProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_mctct import MCTCT_PRETRAINED_MODEL_ARCHIVE_LIST, MCTCTForCTC, MCTCTModel, MCTCTPreTrainedModel

else:
		import sys

		lowerCamelCase__	=							_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



