


'''simple docstring'''

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


lowerCamelCase							:   Tuple  						=	logging.get_logger(__name__)

lowerCamelCase							:   Any  						=	{
    'microsoft/markuplm-base': 'https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json',
    'microsoft/markuplm-large': 'https://huggingface.co/microsoft/markuplm-large/resolve/main/config.json',
}
class   __lowerCAmelCase						(lowercase_     ):





      '''simple docstring'''






      lowerCAmelCase__					:     Optional[int]  					=							"""markuplm"""



      def __init__(self    :    Optional[Any]   ,						UpperCamelCase    :    str=30522   ,						UpperCamelCase    :    Tuple=768   ,						UpperCamelCase    :    List[str]=12   ,						UpperCamelCase    :    List[Any]=12   ,						UpperCamelCase    :    List[str]=3072   ,						UpperCamelCase    :    Optional[int]="gelu"   ,						UpperCamelCase    :    Dict=0.1   ,						UpperCamelCase    :    str=0.1   ,						UpperCamelCase    :    Tuple=512   ,						UpperCamelCase    :    Union[str, Any]=2   ,						UpperCamelCase    :    int=0.02   ,						UpperCamelCase    :    str=1E-12   ,						UpperCamelCase    :    List[Any]=0   ,						UpperCamelCase    :    Dict=0   ,						UpperCamelCase    :    Union[str, Any]=2   ,						UpperCamelCase    :    Any=256   ,						UpperCamelCase    :    Dict=1024   ,						UpperCamelCase    :    int=216   ,						UpperCamelCase    :    Optional[int]=1001   ,						UpperCamelCase    :    Dict=32   ,						UpperCamelCase    :    Optional[int]=50   ,						UpperCamelCase    :    str="absolute"   ,						UpperCamelCase    :    Any=True   ,						UpperCamelCase    :    Any=None   ,						**UpperCamelCase    :    Tuple   ,						):

             '''simple docstring'''







             super().__init__(
                 pad_token_id=UpperCamelCase   ,						bos_token_id=UpperCamelCase   ,						eos_token_id=UpperCamelCase   ,						**UpperCamelCase   ,						)
             lowercase__      			= vocab_size
             lowercase__      			= hidden_size
             lowercase__      			= num_hidden_layers
             lowercase__      			= num_attention_heads
             lowercase__      			= hidden_act
             lowercase__      			= intermediate_size
             lowercase__      			= hidden_dropout_prob
             lowercase__      			= attention_probs_dropout_prob
             lowercase__      			= max_position_embeddings
             lowercase__      			= type_vocab_size
             lowercase__      			= initializer_range
             lowercase__      			= layer_norm_eps
             lowercase__      			= position_embedding_type
             lowercase__      			= use_cache
             lowercase__      			= classifier_dropout
             # additional properties
             lowercase__      			= max_depth
             lowercase__      			= max_xpath_tag_unit_embeddings
             lowercase__      			= max_xpath_subs_unit_embeddings
             lowercase__      			= tag_pad_id
             lowercase__      			= subs_pad_id
             lowercase__      			= xpath_unit_hidden_size








'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


lowerCamelCase							:   str  						=	{
    'configuration_rag': ['RagConfig'],
    'retrieval_rag': ['RagRetriever'],
    'tokenization_rag': ['RagTokenizer'],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase							:   Dict  						=	[
     'RagModel',
     'RagPreTrainedModel',
     'RagSequenceForGeneration',
     'RagTokenForGeneration',
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase							:   Optional[int]  						=	[
     'TFRagModel',
     'TFRagPreTrainedModel',
     'TFRagSequenceForGeneration',
     'TFRagTokenForGeneration',
 ]


if TYPE_CHECKING:
 from .configuration_rag import RagConfig
 from .retrieval_rag import RagRetriever
 from .tokenization_rag import RagTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_rag import RagModel, RagPreTrainedModel, RagSequenceForGeneration, RagTokenForGeneration

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_rag import (
      TFRagModel,
      TFRagPreTrainedModel,
      TFRagSequenceForGeneration,
      TFRagTokenForGeneration,
  )

else:
 import sys

 lowerCamelCase							:   Tuple  						=	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




