





"""simple docstring"""




import warnings

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


lowerCamelCase_     :						Optional[Any]						=					logging.get_logger(__name__)

lowerCamelCase_     :						List[str]						=					{
    'xlnet-base-cased': 'https://huggingface.co/xlnet-base-cased/resolve/main/config.json',
    'xlnet-large-cased': 'https://huggingface.co/xlnet-large-cased/resolve/main/config.json',
}

class  _UpperCAmelCase  (   UpperCAmelCase__		):



      '''simple docstring'''
      lowercase_      : Optional[Any]	    =   """xlnet"""
      lowercase_      : Dict	    =   ["""mems"""]
      lowercase_      : Optional[int]	    =   {
          """n_token""": """vocab_size""",  # Backward compatibility
          """hidden_size""": """d_model""",
          """num_attention_heads""": """n_head""",
          """num_hidden_layers""": """n_layer""",
      }

      def __init__(     self					,      snake_case_=3_2_0_0_0					,      snake_case_=1_0_2_4					,      snake_case_=2_4					,      snake_case_=1_6					,      snake_case_=4_0_9_6					,      snake_case_="gelu"					,      snake_case_=True					,      snake_case_="bi"					,      snake_case_=0.02					,      snake_case_=1E-12					,      snake_case_=0.1					,      snake_case_=5_1_2					,      snake_case_=None					,      snake_case_=True					,      snake_case_=False					,      snake_case_=False					,      snake_case_=-1					,      snake_case_=False					,      snake_case_="last"					,      snake_case_=True					,      snake_case_="tanh"					,      snake_case_=0.1					,      snake_case_=5					,      snake_case_=5					,      snake_case_=5					,      snake_case_=1					,      snake_case_=2					,      **snake_case_					,      ):

        """simple docstring"""

        A_  :       Tuple										=  vocab_size
        A_  :       Optional[Any]										=  d_model
        A_  :       Union[str, Any]										=  n_layer
        A_  :       Any										=  n_head
        if d_model % n_head != 0:
          raise ValueError(F"""'d_model % n_head' ({d_model % n_head}) should be equal to 0"""  )
        if "d_head" in kwargs:
          if kwargs["d_head"] != d_model // n_head:
            raise ValueError(
                F"""`d_head` ({kwargs["d_head"]}) should be equal to `d_model // n_head` ({d_model // n_head})"""  )
        A_  :       Tuple										=  d_model // n_head
        A_  :       List[Any]										=  ff_activation
        A_  :       Optional[int]										=  d_inner
        A_  :       List[Any]										=  untie_r
        A_  :       Union[str, Any]										=  attn_type

        A_  :       List[Any]										=  initializer_range
        A_  :       Union[str, Any]										=  layer_norm_eps

        A_  :       Dict										=  dropout
        A_  :       List[Any]										=  mem_len
        A_  :       Optional[Any]										=  reuse_len
        A_  :       List[Any]										=  bi_data
        A_  :       List[Any]										=  clamp_len
        A_  :       List[str]										=  same_length

        A_  :       List[Any]										=  summary_type
        A_  :       Optional[int]										=  summary_use_proj
        A_  :       Optional[int]										=  summary_activation
        A_  :       List[str]										=  summary_last_dropout
        A_  :       Dict										=  start_n_top
        A_  :       List[Any]										=  end_n_top

        A_  :       int										=  bos_token_id
        A_  :       Dict										=  pad_token_id
        A_  :       List[str]										=  eos_token_id

        if "use_cache" in kwargs:
          warnings.warn(
              'The `use_cache` argument is deprecated and will be removed in a future version, use `use_mems_eval`'
              ' instead.'					,      snake_case_					,      )
          A_  :       Dict										=  kwargs['use_cache']

        A_  :       Optional[int]										=  use_mems_eval
        A_  :       Optional[int]										=  use_mems_train
        super().__init__(pad_token_id=snake_case_					,      bos_token_id=snake_case_					,      eos_token_id=snake_case_					,      **snake_case_  )

      @property
      def 					lowerCamelCase_			(     self  ):

        """simple docstring"""

        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 					lowerCamelCase_			(     self					,      snake_case_  ):

        """simple docstring"""

        raise NotImplementedError(
            F"""The model {self.model_type} is one of the few models that has no sequence length limit."""  )






"""simple docstring"""




from copy import deepcopy

class  _UpperCAmelCase  :



      '''simple docstring'''

      def __init__(     self					,      snake_case_ = None					,      snake_case_ = None  ):

        """simple docstring"""

        if arr is None and size is not None:
          A_  :       Union[str, Any]										=  size
          A_  :       List[str]										=  [0] * size
        elif arr is not None:
          self.init(snake_case_  )
        else:
          raise ValueError('Either arr or size must be specified'  )

      def 					lowerCamelCase_			(     self					,      snake_case_  ):

        """simple docstring"""

        A_  :       Union[str, Any]										=  len(snake_case_  )
        A_  :       Optional[int]										=  deepcopy(snake_case_  )
        for i in range(1					,      self.size  ):
          A_  :       Optional[Any]										=  self.next_(snake_case_  )
          if j < self.size:
            self.tree[j] += self.tree[i]

      def 					lowerCamelCase_			(     self  ):

        """simple docstring"""

        A_  :       int										=  self.tree[:]
        for i in range(self.size - 1					,      0					,      -1  ):
          A_  :       Optional[int]										=  self.next_(snake_case_  )
          if j < self.size:
            arr[j] -= arr[i]
        return arr

      @staticmethod
      def 					lowerCamelCase_			(     snake_case_  ):

        """simple docstring"""

        return index + (index & (-index))

      @staticmethod
      def 					lowerCamelCase_			(     snake_case_  ):

        """simple docstring"""

        return index - (index & (-index))

      def 					lowerCamelCase_			(     self					,      snake_case_					,      snake_case_  ):

        """simple docstring"""

        if index == 0:
          self.tree[0] += value
          return
        while index < self.size:
          self.tree[index] += value
          A_  :       List[str]										=  self.next_(snake_case_  )

      def 					lowerCamelCase_			(     self					,      snake_case_					,      snake_case_  ):

        """simple docstring"""

        self.add(snake_case_					,      value - self.get(snake_case_  )  )

      def 					lowerCamelCase_			(     self					,      snake_case_  ):

        """simple docstring"""

        if right == 0:
          return 0
        A_  :       Any										=  self.tree[0]
        right -= 1  # make right inclusive
        while right > 0:
          result += self.tree[right]
          A_  :       Tuple										=  self.prev(snake_case_  )
        return result

      def 					lowerCamelCase_			(     self					,      snake_case_					,      snake_case_  ):

        """simple docstring"""

        return self.prefix(snake_case_  ) - self.prefix(snake_case_  )

      def 					lowerCamelCase_			(     self					,      snake_case_  ):

        """simple docstring"""

        return self.query(snake_case_					,      index + 1  )

      def 					lowerCamelCase_			(     self					,      snake_case_  ):

        """simple docstring"""

        value -= self.tree[0]
        if value < 0:
          return -1

        A_  :       List[Any]										=  1  # Largest power of 2 <= size
        while j * 2 < self.size:
          j *= 2

        A_  :       Tuple										=  0

        while j > 0:
          if i + j < self.size and self.tree[i + j] <= value:
            value -= self.tree[i + j]
            i += j
          j //= 2
        return i


if __name__ == "__main__":
   import doctest

   doctest.testmod()