






import logging

from transformers import PretrainedConfig


lowercase  :							List[Any]			  =    logging.getLogger(__name__)


lowercase  :							Tuple			  =    {
    '''bertabs-finetuned-cnndm''': '''https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolve/main/config.json''',
}




class 		UpperCAmelCase_						(	SCREAMING_SNAKE_CASE__					):


						'''simple docstring'''




						A     :   Optional[Any]						=					'bertabs'






						def __init__(	self		,				_SCREAMING_SNAKE_CASE=3_0522		,				_SCREAMING_SNAKE_CASE=512		,				_SCREAMING_SNAKE_CASE=6		,				_SCREAMING_SNAKE_CASE=512		,				_SCREAMING_SNAKE_CASE=8		,				_SCREAMING_SNAKE_CASE=512		,				_SCREAMING_SNAKE_CASE=0.2		,				_SCREAMING_SNAKE_CASE=6		,				_SCREAMING_SNAKE_CASE=768		,				_SCREAMING_SNAKE_CASE=8		,				_SCREAMING_SNAKE_CASE=2048		,				_SCREAMING_SNAKE_CASE=0.2		,				**_SCREAMING_SNAKE_CASE		,				) ->				int:
								super().__init__(**_SCREAMING_SNAKE_CASE				)

								snake_case_				:							List[Any]						 =       vocab_size
								snake_case_				:							Any						 =       max_pos

								snake_case_				:							str						 =       enc_layers
								snake_case_				:							Tuple						 =       enc_hidden_size
								snake_case_				:							List[Any]						 =       enc_heads
								snake_case_				:							Tuple						 =       enc_ff_size
								snake_case_				:							Dict						 =       enc_dropout

								snake_case_				:							List[str]						 =       dec_layers
								snake_case_				:							Tuple						 =       dec_hidden_size
								snake_case_				:							Tuple						 =       dec_heads
								snake_case_				:							Optional[int]						 =       dec_ff_size
								snake_case_				:							Optional[int]						 =       dec_dropout








from typing import TYPE_CHECKING

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


lowercase  :							int			  =    {
    '''configuration_audio_spectrogram_transformer''': [
        '''AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''ASTConfig''',
    ]
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase  :							Optional[Any]			  =    [
							    '''AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''ASTForAudioClassification''',
							    '''ASTModel''',
							    '''ASTPreTrainedModel''',
							]

try:
							if not is_speech_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase  :							Optional[int]			  =    ['''ASTFeatureExtractor''']

if TYPE_CHECKING:
							from .configuration_audio_spectrogram_transformer import (
							    AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    ASTConfig,
							)

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_audio_spectrogram_transformer import (
														    AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
														    ASTForAudioClassification,
														    ASTModel,
														    ASTPreTrainedModel,
														)

							try:
														if not is_speech_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_audio_spectrogram_transformer import ASTFeatureExtractor


else:
							import sys

							lowercase  :							Optional[int]			  =    _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
