





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_UpperCamelCase   :							List[str]     =	logging.get_logger(__name__)

_UpperCamelCase   :							int     =	{
    """flaubert/flaubert_small_cased""": """https://huggingface.co/flaubert/flaubert_small_cased/resolve/main/config.json""",
    """flaubert/flaubert_base_uncased""": """https://huggingface.co/flaubert/flaubert_base_uncased/resolve/main/config.json""",
    """flaubert/flaubert_base_cased""": """https://huggingface.co/flaubert/flaubert_base_cased/resolve/main/config.json""",
    """flaubert/flaubert_large_cased""": """https://huggingface.co/flaubert/flaubert_large_cased/resolve/main/config.json""",
}







class 						_lowerCAmelCase(						_a):

  """simple docstring"""







  lowerCamelCase__      					=   '''flaubert'''
  lowerCamelCase__      					=   {
      '''hidden_size''': '''emb_dim''',
      '''num_attention_heads''': '''n_heads''',
      '''num_hidden_layers''': '''n_layers''',
      '''n_words''': '''vocab_size''',  # For backward compatibility
  }

  def __init__( self  ,    UpperCAmelCase=False  ,    UpperCAmelCase=0.0  ,    UpperCAmelCase=3_01_45  ,    UpperCAmelCase=20_48  ,    UpperCAmelCase=12  ,    UpperCAmelCase=16  ,    UpperCAmelCase=0.1  ,    UpperCAmelCase=0.1  ,    UpperCAmelCase=True  ,    UpperCAmelCase=False  ,    UpperCAmelCase=False  ,    UpperCAmelCase=False  ,    UpperCAmelCase=1  ,    UpperCAmelCase=True  ,    UpperCAmelCase=5_12  ,    UpperCAmelCase=20_48**-0.5  ,    UpperCAmelCase=1e-12  ,    UpperCAmelCase=0.02  ,    UpperCAmelCase=0  ,    UpperCAmelCase=1  ,    UpperCAmelCase=2  ,    UpperCAmelCase=3  ,    UpperCAmelCase=5  ,    UpperCAmelCase=True  ,    UpperCAmelCase="first"  ,    UpperCAmelCase=True  ,    UpperCAmelCase=None  ,    UpperCAmelCase=True  ,    UpperCAmelCase=0.1  ,    UpperCAmelCase=5  ,    UpperCAmelCase=5  ,    UpperCAmelCase=0  ,    UpperCAmelCase=0  ,    UpperCAmelCase=2  ,    UpperCAmelCase=0  ,    **UpperCAmelCase  ,    )-> List[str]:
     __A				 =       pre_norm
     __A				 =       layerdrop
     __A				 =       vocab_size
     __A				 =       emb_dim
     __A				 =       n_layers
     __A				 =       n_heads
     __A				 =       dropout
     __A				 =       attention_dropout
     __A				 =       gelu_activation
     __A				 =       sinusoidal_embeddings
     __A				 =       causal
     __A				 =       asm
     __A				 =       n_langs
     __A				 =       use_lang_emb
     __A				 =       layer_norm_eps
     __A				 =       bos_index
     __A				 =       eos_index
     __A				 =       pad_index
     __A				 =       unk_index
     __A				 =       mask_index
     __A				 =       is_encoder
     __A				 =       max_position_embeddings
     __A				 =       embed_init_std
     __A				 =       init_std
     __A				 =       summary_type
     __A				 =       summary_use_proj
     __A				 =       summary_activation
     __A				 =       summary_proj_to_labels
     __A				 =       summary_first_dropout
     __A				 =       start_n_top
     __A				 =       end_n_top
     __A				 =       mask_token_id
     __A				 =       lang_id

     if "n_words" in kwargs:
        __A				 =       kwargs['''n_words''']

     super().__init__(pad_token_id=UpperCAmelCase  ,    bos_token_id=UpperCAmelCase  ,    **UpperCAmelCase     )







class 						_lowerCAmelCase(						_a):

  """simple docstring"""







  @property
  def 		SCREAMING_SNAKE_CASE__	( self     )-> Mapping[str, Mapping[int, str]]:
     if self.task == "multiple-choice":
        __A				 =       {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
     else:
        __A				 =       {0: '''batch''', 1: '''sequence'''}
     return OrderedDict(
         [
             ('''input_ids''', dynamic_axis),
             ('''attention_mask''', dynamic_axis),
         ]     )








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


_UpperCamelCase   :							Dict     =	logging.get_logger(__name__)

_UpperCamelCase   :							Optional[int]     =	{
    """MCG-NJU/videomae-base""": """https://huggingface.co/MCG-NJU/videomae-base/resolve/main/config.json""",
}







class 						_lowerCAmelCase(						_a):

  """simple docstring"""







  lowerCamelCase__      					=   '''videomae'''

  def __init__( self  ,    UpperCAmelCase=2_24  ,    UpperCAmelCase=16  ,    UpperCAmelCase=3  ,    UpperCAmelCase=16  ,    UpperCAmelCase=2  ,    UpperCAmelCase=7_68  ,    UpperCAmelCase=12  ,    UpperCAmelCase=12  ,    UpperCAmelCase=30_72  ,    UpperCAmelCase="gelu"  ,    UpperCAmelCase=0.0  ,    UpperCAmelCase=0.0  ,    UpperCAmelCase=0.02  ,    UpperCAmelCase=1e-12  ,    UpperCAmelCase=True  ,    UpperCAmelCase=True  ,    UpperCAmelCase=6  ,    UpperCAmelCase=3_84  ,    UpperCAmelCase=4  ,    UpperCAmelCase=15_36  ,    UpperCAmelCase=True  ,    **UpperCAmelCase  ,    )-> Any:
     super().__init__(**UpperCAmelCase     )

     __A				 =       image_size
     __A				 =       patch_size
     __A				 =       num_channels
     __A				 =       num_frames
     __A				 =       tubelet_size

     __A				 =       hidden_size
     __A				 =       num_hidden_layers
     __A				 =       num_attention_heads
     __A				 =       intermediate_size
     __A				 =       hidden_act
     __A				 =       hidden_dropout_prob
     __A				 =       attention_probs_dropout_prob
     __A				 =       initializer_range
     __A				 =       layer_norm_eps
     __A				 =       qkv_bias
     __A				 =       use_mean_pooling

     __A				 =       decoder_num_attention_heads
     __A				 =       decoder_hidden_size
     __A				 =       decoder_num_hidden_layers
     __A				 =       decoder_intermediate_size
     __A				 =       norm_pix_loss

