






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


_SCREAMING_SNAKE_CASE					:  Any             =      logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE					:  List[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 	UpperCAmelCase__		(	A__	):






  """simple docstring"""


  a									= """markuplm"""






  def __init__(							self						:		Any     ,       __lowerCamelCase						:		Tuple=3_0522     ,       __lowerCamelCase						:		List[Any]=768     ,       __lowerCamelCase						:		int=12     ,       __lowerCamelCase						:		str=12     ,       __lowerCamelCase						:		Tuple=3072     ,       __lowerCamelCase						:		int="gelu"     ,       __lowerCamelCase						:		str=0.1     ,       __lowerCamelCase						:		Optional[Any]=0.1     ,       __lowerCamelCase						:		List[Any]=512     ,       __lowerCamelCase						:		Tuple=2     ,       __lowerCamelCase						:		List[str]=0.02     ,       __lowerCamelCase						:		Tuple=1e-12     ,       __lowerCamelCase						:		Dict=0     ,       __lowerCamelCase						:		Optional[Any]=0     ,       __lowerCamelCase						:		Tuple=2     ,       __lowerCamelCase						:		Tuple=256     ,       __lowerCamelCase						:		Union[str, Any]=1024     ,       __lowerCamelCase						:		int=216     ,       __lowerCamelCase						:		Union[str, Any]=1001     ,       __lowerCamelCase						:		str=32     ,       __lowerCamelCase						:		List[Any]=50     ,       __lowerCamelCase						:		Dict="absolute"     ,       __lowerCamelCase						:		List[str]=True     ,       __lowerCamelCase						:		List[Any]=None     ,       **__lowerCamelCase						:		Optional[int]     ,       )		->							int:
       super().__init__(
           pad_token_id=_lowercase     ,       bos_token_id=_lowercase     ,       eos_token_id=_lowercase     ,       **_lowercase     ,       )
       SCREAMING_SNAKE_CASE__   =   vocab_size
       SCREAMING_SNAKE_CASE__   =   hidden_size
       SCREAMING_SNAKE_CASE__   =   num_hidden_layers
       SCREAMING_SNAKE_CASE__   =   num_attention_heads
       SCREAMING_SNAKE_CASE__   =   hidden_act
       SCREAMING_SNAKE_CASE__   =   intermediate_size
       SCREAMING_SNAKE_CASE__   =   hidden_dropout_prob
       SCREAMING_SNAKE_CASE__   =   attention_probs_dropout_prob
       SCREAMING_SNAKE_CASE__   =   max_position_embeddings
       SCREAMING_SNAKE_CASE__   =   type_vocab_size
       SCREAMING_SNAKE_CASE__   =   initializer_range
       SCREAMING_SNAKE_CASE__   =   layer_norm_eps
       SCREAMING_SNAKE_CASE__   =   position_embedding_type
       SCREAMING_SNAKE_CASE__   =   use_cache
       SCREAMING_SNAKE_CASE__   =   classifier_dropout
       # additional properties
       SCREAMING_SNAKE_CASE__   =   max_depth
       SCREAMING_SNAKE_CASE__   =   max_xpath_tag_unit_embeddings
       SCREAMING_SNAKE_CASE__   =   max_xpath_subs_unit_embeddings
       SCREAMING_SNAKE_CASE__   =   tag_pad_id
       SCREAMING_SNAKE_CASE__   =   subs_pad_id
       SCREAMING_SNAKE_CASE__   =   xpath_unit_hidden_size





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


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

_SCREAMING_SNAKE_CASE					:  Tuple             =      {
    '''transfo-xl-wt103''': '''https://huggingface.co/transfo-xl-wt103/resolve/main/config.json''',
}






class 	UpperCAmelCase__		(	A__	):






  """simple docstring"""


  a									= "transfo-xl"
  a									= ["mems"]
  a									= {
      "n_token": "vocab_size",
      "hidden_size": "d_model",
      "num_attention_heads": "n_head",
      "num_hidden_layers": "n_layer",
  }






  def __init__(							self						:		Any     ,       __lowerCamelCase						:		int=26_7735     ,       __lowerCamelCase						:		Any=[2_0000, 4_0000, 20_0000]     ,       __lowerCamelCase						:		Dict=1024     ,       __lowerCamelCase						:		Optional[int]=1024     ,       __lowerCamelCase						:		List[Any]=16     ,       __lowerCamelCase						:		Union[str, Any]=64     ,       __lowerCamelCase						:		Dict=4096     ,       __lowerCamelCase						:		int=4     ,       __lowerCamelCase						:		Dict=False     ,       __lowerCamelCase						:		Tuple=18     ,       __lowerCamelCase						:		Optional[int]=1600     ,       __lowerCamelCase						:		str=1000     ,       __lowerCamelCase						:		Any=True     ,       __lowerCamelCase						:		Dict=True     ,       __lowerCamelCase						:		List[Any]=0     ,       __lowerCamelCase						:		int=-1     ,       __lowerCamelCase						:		Tuple=True     ,       __lowerCamelCase						:		List[Any]=0.1     ,       __lowerCamelCase						:		int=0.0     ,       __lowerCamelCase						:		int=True     ,       __lowerCamelCase						:		str="normal"     ,       __lowerCamelCase						:		List[str]=0.01     ,       __lowerCamelCase						:		Any=0.01     ,       __lowerCamelCase						:		List[str]=0.02     ,       __lowerCamelCase						:		List[str]=1e-5     ,       __lowerCamelCase						:		Union[str, Any]=0     ,       **__lowerCamelCase						:		int     ,       )		->							Optional[Any]:
       SCREAMING_SNAKE_CASE__   =   vocab_size
       SCREAMING_SNAKE_CASE__   =   []
       self.cutoffs.extend(__lowerCamelCase )
       if proj_share_all_but_first:
            SCREAMING_SNAKE_CASE__   =   [False] + [True] * len(self.cutoffs )
       else:
            SCREAMING_SNAKE_CASE__   =   [False] + [False] * len(self.cutoffs )
       SCREAMING_SNAKE_CASE__   =   d_model
       SCREAMING_SNAKE_CASE__   =   d_embed
       SCREAMING_SNAKE_CASE__   =   d_head
       SCREAMING_SNAKE_CASE__   =   d_inner
       SCREAMING_SNAKE_CASE__   =   div_val
       SCREAMING_SNAKE_CASE__   =   pre_lnorm
       SCREAMING_SNAKE_CASE__   =   n_layer
       SCREAMING_SNAKE_CASE__   =   n_head
       SCREAMING_SNAKE_CASE__   =   mem_len
       SCREAMING_SNAKE_CASE__   =   same_length
       SCREAMING_SNAKE_CASE__   =   attn_type
       SCREAMING_SNAKE_CASE__   =   clamp_len
       SCREAMING_SNAKE_CASE__   =   sample_softmax
       SCREAMING_SNAKE_CASE__   =   adaptive
       SCREAMING_SNAKE_CASE__   =   dropout
       SCREAMING_SNAKE_CASE__   =   dropatt
       SCREAMING_SNAKE_CASE__   =   untie_r
       SCREAMING_SNAKE_CASE__   =   init
       SCREAMING_SNAKE_CASE__   =   init_range
       SCREAMING_SNAKE_CASE__   =   proj_init_std
       SCREAMING_SNAKE_CASE__   =   init_std
       SCREAMING_SNAKE_CASE__   =   layer_norm_epsilon
       super().__init__(eos_token_id=__lowerCamelCase     ,       **__lowerCamelCase )






  @property
  def 				lowercase_		(							self						:		str )		->							Dict:
       # Message copied from Transformer-XL documentation
       logger.info(f'''The model {self.model_type} is one of the few models that has no sequence length limit.''' )
       return -1







  @max_position_embeddings.setter
  def 				lowercase_		(							self						:		List[str]     ,       __lowerCamelCase						:		Any )		->							List[Any]:
       # Message copied from Transformer-XL documentation
       raise NotImplementedError(
           f'''The model {self.model_type} is one of the few models that has no sequence length limit.''' )


