



'''simple docstring'''




import warnings

from ..trainer import Trainer
from ..utils import logging


UpperCamelCase__ :			Optional[int]												=				logging.get_logger(__name__)






class 		_UpperCamelCase						(							lowerCamelCase__					):


			'''simple docstring'''

			def __init__(							self  :				List[Any]							,  lowerCAmelCase__  :				Tuple=None							,  **lowerCAmelCase__  :				Tuple		):





					"""simple docstring"""






					warnings.warn(
					    """`SageMakerTrainer` is deprecated and will be removed in v5 of Transformers. You can use `Trainer` """
					    """instead."""							,  lowerCAmelCase__							,  )
					super().__init__(args=lowerCAmelCase__							,  **lowerCAmelCase__		)




'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCamelCase__ :			Optional[int]												=				{'''configuration_wavlm''': ['''WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''WavLMConfig''']}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase__ :			Tuple												=				[
						    '''WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''WavLMForAudioFrameClassification''',
						    '''WavLMForCTC''',
						    '''WavLMForSequenceClassification''',
						    '''WavLMForXVector''',
						    '''WavLMModel''',
						    '''WavLMPreTrainedModel''',
						]

if TYPE_CHECKING:
						from .configuration_wavlm import WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP, WavLMConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_wavlm import (
												    WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST,
												    WavLMForAudioFrameClassification,
												    WavLMForCTC,
												    WavLMForSequenceClassification,
												    WavLMForXVector,
												    WavLMModel,
												    WavLMPreTrainedModel,
												)

else:
						import sys

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