





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


_UpperCamelCase    =	logging.get_logger(__name__)

_UpperCamelCase    =	{
    '''MCG-NJU/videomae-base''': '''https://huggingface.co/MCG-NJU/videomae-base/resolve/main/config.json''',
}




class 			_lowerCamelCase	(      a      ):



      """simple docstring"""






      UpperCAmelCase_  : str				      ="videomae"







      def __init__(	self			,  UpperCAmelCase=224			,  UpperCAmelCase=16			,  UpperCAmelCase=3			,  UpperCAmelCase=16			,  UpperCAmelCase=2			,  UpperCAmelCase=768			,  UpperCAmelCase=12			,  UpperCAmelCase=12			,  UpperCAmelCase=3072			,  UpperCAmelCase="gelu"			,  UpperCAmelCase=0.0			,  UpperCAmelCase=0.0			,  UpperCAmelCase=0.02			,  UpperCAmelCase=1E-12			,  UpperCAmelCase=True			,  UpperCAmelCase=True			,  UpperCAmelCase=6			,  UpperCAmelCase=384			,  UpperCAmelCase=4			,  UpperCAmelCase=1536			,  UpperCAmelCase=True			,  **UpperCAmelCase			,  )    ->				Tuple:






        '''simple docstring'''






        super().__init__(**UpperCAmelCase				)

        __snake_case				:			Union[str, Any]            =    image_size
        __snake_case				:			List[Any]            =    patch_size
        __snake_case				:			Union[str, Any]            =    num_channels
        __snake_case				:			Optional[int]            =    num_frames
        __snake_case				:			int            =    tubelet_size

        __snake_case				:			List[Any]            =    hidden_size
        __snake_case				:			Optional[int]            =    num_hidden_layers
        __snake_case				:			List[Any]            =    num_attention_heads
        __snake_case				:			int            =    intermediate_size
        __snake_case				:			Union[str, Any]            =    hidden_act
        __snake_case				:			Optional[Any]            =    hidden_dropout_prob
        __snake_case				:			Any            =    attention_probs_dropout_prob
        __snake_case				:			Optional[int]            =    initializer_range
        __snake_case				:			Any            =    layer_norm_eps
        __snake_case				:			Union[str, Any]            =    qkv_bias
        __snake_case				:			str            =    use_mean_pooling

        __snake_case				:			Tuple            =    decoder_num_attention_heads
        __snake_case				:			Tuple            =    decoder_hidden_size
        __snake_case				:			List[str]            =    decoder_num_hidden_layers
        __snake_case				:			List[str]            =    decoder_intermediate_size
        __snake_case				:			List[str]            =    norm_pix_loss








from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_UpperCamelCase    =	{
    '''configuration_dpr''': ['''DPR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DPRConfig'''],
    '''tokenization_dpr''': [
        '''DPRContextEncoderTokenizer''',
        '''DPRQuestionEncoderTokenizer''',
        '''DPRReaderOutput''',
        '''DPRReaderTokenizer''',
    ],
}


try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase    =	[
         '''DPRContextEncoderTokenizerFast''',
         '''DPRQuestionEncoderTokenizerFast''',
         '''DPRReaderTokenizerFast''',
     ]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase    =	[
         '''DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''DPRContextEncoder''',
         '''DPRPretrainedContextEncoder''',
         '''DPRPreTrainedModel''',
         '''DPRPretrainedQuestionEncoder''',
         '''DPRPretrainedReader''',
         '''DPRQuestionEncoder''',
         '''DPRReader''',
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase    =	[
         '''TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''TFDPRContextEncoder''',
         '''TFDPRPretrainedContextEncoder''',
         '''TFDPRPretrainedQuestionEncoder''',
         '''TFDPRPretrainedReader''',
         '''TFDPRQuestionEncoder''',
         '''TFDPRReader''',
     ]


if TYPE_CHECKING:
     from .configuration_dpr import DPR_PRETRAINED_CONFIG_ARCHIVE_MAP, DPRConfig
     from .tokenization_dpr import (
         DPRContextEncoderTokenizer,
         DPRQuestionEncoderTokenizer,
         DPRReaderOutput,
         DPRReaderTokenizer,
     )

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_dpr_fast import (
              DPRContextEncoderTokenizerFast,
              DPRQuestionEncoderTokenizerFast,
              DPRReaderTokenizerFast,
          )

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_dpr import (
              DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
              DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
              DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
              DPRContextEncoder,
              DPRPretrainedContextEncoder,
              DPRPreTrainedModel,
              DPRPretrainedQuestionEncoder,
              DPRPretrainedReader,
              DPRQuestionEncoder,
              DPRReader,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_dpr import (
              TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
              TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
              TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFDPRContextEncoder,
              TFDPRPretrainedContextEncoder,
              TFDPRPretrainedQuestionEncoder,
              TFDPRPretrainedReader,
              TFDPRQuestionEncoder,
              TFDPRReader,
          )

else:
     import sys

     _UpperCamelCase    =	_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

