



'''simple docstring'''



from collections import OrderedDict
from typing import Mapping

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


a__    :      str      				=      logging.get_logger(__name__)

a__    :      Dict      				=      {
    'camembert-base': 'https://huggingface.co/camembert-base/resolve/main/config.json',
    'umberto-commoncrawl-cased-v1': (
        'https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json'
    ),
    'umberto-wikipedia-uncased-v1': (
        'https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json'
    ),
}
class 							UpperCAmelCase__	(     __a):
 __SCREAMING_SNAKE_CASE          =					'''camembert'''



 def __init__(	self		,						lowercase=3_0_5_2_2		,						lowercase=7_6_8		,						lowercase=1_2		,						lowercase=1_2		,						lowercase=3_0_7_2		,						lowercase="gelu"		,						lowercase=0.1		,						lowercase=0.1		,						lowercase=5_1_2		,						lowercase=2		,						lowercase=0.02		,						lowercase=1E-12		,						lowercase=1		,						lowercase=0		,						lowercase=2		,						lowercase="absolute"		,						lowercase=True		,						lowercase=None		,						**lowercase		,						)	->				Any:
  super().__init__(pad_token_id=lowercase_		,						bos_token_id=lowercase_		,						eos_token_id=lowercase_		,						**lowercase_      )

  __UpperCamelCase					   =	vocab_size
  __UpperCamelCase					   =	hidden_size
  __UpperCamelCase					   =	num_hidden_layers
  __UpperCamelCase					   =	num_attention_heads
  __UpperCamelCase					   =	hidden_act
  __UpperCamelCase					   =	intermediate_size
  __UpperCamelCase					   =	hidden_dropout_prob
  __UpperCamelCase					   =	attention_probs_dropout_prob
  __UpperCamelCase					   =	max_position_embeddings
  __UpperCamelCase					   =	type_vocab_size
  __UpperCamelCase					   =	initializer_range
  __UpperCamelCase					   =	layer_norm_eps
  __UpperCamelCase					   =	position_embedding_type
  __UpperCamelCase					   =	use_cache
  __UpperCamelCase					   =	classifier_dropout


class 							UpperCAmelCase__	(     __a):



 @property
 def  __lowerCamelCase					(	self      )	->				List[str]:


  if self.task == "multiple-choice":
   __UpperCamelCase					   =	{0: """batch""", 1: """choice""", 2: """sequence"""}
  else:
   __UpperCamelCase					   =	{0: """batch""", 1: """sequence"""}
  return OrderedDict(
      [
          ("""input_ids""", dynamic_axis),
          ("""attention_mask""", dynamic_axis),
      ]      )






'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__snake_case						  =		{
    """configuration_git""": ["""GIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GitConfig""", """GitVisionConfig"""],
    """processing_git""": ["""GitProcessor"""],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __snake_case						  =		[
           """GIT_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """GitForCausalLM""",
           """GitModel""",
           """GitPreTrainedModel""",
           """GitVisionModel""",
       ]

if TYPE_CHECKING:
       from .configuration_git import GIT_PRETRAINED_CONFIG_ARCHIVE_MAP, GitConfig, GitVisionConfig
       from .processing_git import GitProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_git import (
                  GIT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  GitForCausalLM,
                  GitModel,
                  GitPreTrainedModel,
                  GitVisionModel,
              )

else:
       import sys

       __snake_case						  =		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

