


'''simple docstring'''

import logging

from transformers.configuration_utils import PretrainedConfig


a_    :							int         =					logging.getLogger(__name__)





class 	snake_case       (       lowercase     ):





  """simple docstring"""




  _lowerCamelCase						       =    "masked_bert"






  def __init__(       self     ,    UpperCamelCase=3_0522     ,    UpperCamelCase=768     ,    UpperCamelCase=12     ,    UpperCamelCase=12     ,    UpperCamelCase=3072     ,    UpperCamelCase="gelu"     ,    UpperCamelCase=0.1     ,    UpperCamelCase=0.1     ,    UpperCamelCase=512     ,    UpperCamelCase=2     ,    UpperCamelCase=0.02     ,    UpperCamelCase=1e-12     ,    UpperCamelCase=0     ,    UpperCamelCase="topK"     ,    UpperCamelCase="constant"     ,    UpperCamelCase=0.0     ,    **UpperCamelCase     ,    ):







   """simple docstring"""
   super().__init__(pad_token_id=UpperCamelCase     ,    **UpperCamelCase	)

   lowerCamelCase_						=    vocab_size
   lowerCamelCase_						=    hidden_size
   lowerCamelCase_						=    num_hidden_layers
   lowerCamelCase_						=    num_attention_heads
   lowerCamelCase_						=    hidden_act
   lowerCamelCase_						=    intermediate_size
   lowerCamelCase_						=    hidden_dropout_prob
   lowerCamelCase_						=    attention_probs_dropout_prob
   lowerCamelCase_						=    max_position_embeddings
   lowerCamelCase_						=    type_vocab_size
   lowerCamelCase_						=    initializer_range
   lowerCamelCase_						=    layer_norm_eps
   lowerCamelCase_						=    pruning_method
   lowerCamelCase_						=    mask_init
   lowerCamelCase_						=    mask_scale






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase_   							=  {
    'configuration_timesformer': ['TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TimesformerConfig'],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_   							=  [
      'TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
      'TimesformerModel',
      'TimesformerForVideoClassification',
      'TimesformerPreTrainedModel',
  ]

if TYPE_CHECKING:
  from .configuration_timesformer import TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, TimesformerConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_timesformer import (
        TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
        TimesformerForVideoClassification,
        TimesformerModel,
        TimesformerPreTrainedModel,
    )

else:
  import sys

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


