from ...configuration_utils import PretrainedConfig
from ...utils import logging


__snake_case						=			logging.get_logger(__name__)

__snake_case						=			{
    """google/vivit-b-16x2-kinetics400""": (
        """https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json"""
    ),
    # See all Vivit models at https://huggingface.co/models?filter=vivit
}







class 	__snake_case      (   UpperCAmelCase_      ):
 __lowerCamelCase			:      List[str]           =					'''vivit'''
 def __init__(     self						,      snake_case__=224						,      snake_case__=32						,      snake_case__=[2, 16, 16]						,      snake_case__=3						,      snake_case__=768						,      snake_case__=12						,      snake_case__=12						,      snake_case__=3072						,      snake_case__="gelu_fast"						,      snake_case__=0.0						,      snake_case__=0.0						,      snake_case__=0.02						,      snake_case__=1e-06						,      snake_case__=True						,      **snake_case__						,      )		->							str:
       '''simple docstring'''





       UpperCAmelCase			:       Any			     =hidden_size
       UpperCAmelCase			:       str			     =num_hidden_layers
       UpperCAmelCase			:       Optional[Any]			     =num_attention_heads
       UpperCAmelCase			:       Union[str, Any]			     =intermediate_size
       UpperCAmelCase			:       Any			     =hidden_act
       UpperCAmelCase			:       str			     =hidden_dropout_prob
       UpperCAmelCase			:       int			     =attention_probs_dropout_prob
       UpperCAmelCase			:       Dict			     =initializer_range
       UpperCAmelCase			:       int			     =layer_norm_eps

       UpperCAmelCase			:       Union[str, Any]			     =image_size
       UpperCAmelCase			:       Any			     =num_frames
       UpperCAmelCase			:       Optional[Any]			     =tubelet_size
       UpperCAmelCase			:       int			     =num_channels
       UpperCAmelCase			:       Optional[Any]			     =qkv_bias

       super().__init__(**lowerCAmelCase__  )



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase							:  Optional[int]   	=						{"""configuration_wavlm""": ["""WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """WavLMConfig"""]}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase							:  Any   	=						[
						    """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

						lowerCAmelCase							:  Union[str, Any]   	=						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






