


class   A__							:




      def __init__(    self   : List[str]					)							->       None:


          """simple docstring"""





          _SCREAMING_SNAKE_CASE     					={}
          # indexmap keys are an index and it's values are the number at that index
          _SCREAMING_SNAKE_CASE     					={}




      def 							__UpperCamelCase			(    self   : str			,      _a   : List[Any]			,      _a   : Optional[int]					)							->       list[int]:


          """simple docstring"""





          if isinstance(__UpperCamelCase			,      (range, str)					):
              _SCREAMING_SNAKE_CASE     					=list(__UpperCamelCase					)
          elif not isinstance(__UpperCamelCase			,      __UpperCamelCase					):
              raise TypeError(
                  '''binary_search_delete() only accepts either a list, range or str'''					)

          _SCREAMING_SNAKE_CASE     					=0
          _SCREAMING_SNAKE_CASE     					=len(__UpperCamelCase					) - 1

          while low <= high:
              _SCREAMING_SNAKE_CASE     					=(low + high) // 2
              if array[mid] == item:
                  array.pop(__UpperCamelCase					)
                  return array
              elif array[mid] < item:
                  _SCREAMING_SNAKE_CASE     					=mid + 1
              else:
                  _SCREAMING_SNAKE_CASE     					=mid - 1
          raise ValueError(
              '''Either the item is not in the array or the array was unsorted'''					)




      def 							__UpperCamelCase			(    self   : List[str]			,      _a   : List[Any]			,      _a   : List[Any]					)							->       list[int]:


          """simple docstring"""





          if isinstance(__UpperCamelCase			,      (range, str)					):
              _SCREAMING_SNAKE_CASE     					=list(__UpperCamelCase					)
          elif not isinstance(__UpperCamelCase			,      __UpperCamelCase					):
              raise TypeError(
                  '''binary_search_insert() only accepts either a list, range or str'''					)

          _SCREAMING_SNAKE_CASE     					=0
          _SCREAMING_SNAKE_CASE     					=len(__UpperCamelCase					) - 1

          while low <= high:
              _SCREAMING_SNAKE_CASE     					=(low + high) // 2
              if array[mid] == index:
                  # If the item already exists in the array,
                  # insert it after the existing item
                  array.insert(mid + 1			,      __UpperCamelCase					)
                  return array
              elif array[mid] < index:
                  _SCREAMING_SNAKE_CASE     					=mid + 1
              else:
                  _SCREAMING_SNAKE_CASE     					=mid - 1

        # If the item doesn't exist in the array, insert it at the appropriate position
          array.insert(__UpperCamelCase			,      __UpperCamelCase					)
          return array




      def 							__UpperCamelCase			(    self   : List[Any]			,      _a   : int			,      _a   : Tuple					)							->       None:


          """simple docstring"""





          if index in self.indexmap:
              _SCREAMING_SNAKE_CASE     					=self.indexmap[index]
              if len(self.numbermap[n]					) == 1:
                  del self.numbermap[n]
              else:
                  _SCREAMING_SNAKE_CASE     					=self.binary_search_delete(self.numbermap[n]			,      __UpperCamelCase					)

        # Set new index
          _SCREAMING_SNAKE_CASE     					=number

          # Number not seen before or empty so insert number value
          if number not in self.numbermap:
              _SCREAMING_SNAKE_CASE     					=[index]

          # Here we need to perform a binary search insertion in order to insert
          # The item in the correct place
          else:
              _SCREAMING_SNAKE_CASE     					=self.binary_search_insert(
                  self.numbermap[number]			,      __UpperCamelCase					)




      def 							__UpperCamelCase			(    self   : Tuple			,      _a   : Optional[Any]					)							->       int:


          """simple docstring"""





          return self.numbermap.get(__UpperCamelCase			,      [-1]					)[0]


if __name__ == "__main__":
       import doctest

       doctest.testmod()



from collections import OrderedDict
from typing import Mapping

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


snake_case_  :     Tuple							  =							logging.get_logger(__name__)

snake_case_  :     int							  =							{
    '''uclanlp/plbart-base''': '''https://huggingface.co/uclanlp/plbart-base/resolve/main/config.json''',
    # See all PLBART models at https://huggingface.co/models?filter=plbart
}

class   A__							(						UpperCamelCase__					):
						UpperCAmelCase     =  "plbart"
						UpperCAmelCase     =  ["past_key_values"]
						UpperCAmelCase     =  {"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}




						def __init__(    self   : Union[str, Any]			,      _a   : List[str]=5_0005			,      _a   : List[str]=1024			,      _a   : int=6			,      _a   : Union[str, Any]=3072			,      _a   : List[str]=12			,      _a   : int=6			,      _a   : Optional[int]=3072			,      _a   : Any=12			,      _a   : Any=0.0			,      _a   : Optional[Any]=0.0			,      _a   : List[Any]=True			,      _a   : Any=True			,      _a   : Any="gelu"			,      _a   : int=768			,      _a   : int=0.1			,      _a   : int=0.1			,      _a   : List[str]=0.0			,      _a   : Optional[int]=0.02			,      _a   : Dict=0.0			,      _a   : List[str]=True			,      _a   : List[Any]=1			,      _a   : Tuple=0			,      _a   : Tuple=2			,      _a   : Optional[int]=2			,      **_a   : Optional[int]			,      )							->       Optional[int]:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE     					=vocab_size
										_SCREAMING_SNAKE_CASE     					=max_position_embeddings
										_SCREAMING_SNAKE_CASE     					=d_model
										_SCREAMING_SNAKE_CASE     					=encoder_ffn_dim
										_SCREAMING_SNAKE_CASE     					=encoder_layers
										_SCREAMING_SNAKE_CASE     					=encoder_attention_heads
										_SCREAMING_SNAKE_CASE     					=decoder_ffn_dim
										_SCREAMING_SNAKE_CASE     					=decoder_layers
										_SCREAMING_SNAKE_CASE     					=decoder_attention_heads
										_SCREAMING_SNAKE_CASE     					=dropout
										_SCREAMING_SNAKE_CASE     					=attention_dropout
										_SCREAMING_SNAKE_CASE     					=activation_dropout
										_SCREAMING_SNAKE_CASE     					=activation_function
										_SCREAMING_SNAKE_CASE     					=init_std
										_SCREAMING_SNAKE_CASE     					=encoder_layerdrop
										_SCREAMING_SNAKE_CASE     					=decoder_layerdrop
										_SCREAMING_SNAKE_CASE     					=classifier_dropout
										_SCREAMING_SNAKE_CASE     					=use_cache
										_SCREAMING_SNAKE_CASE     					=encoder_layers
										_SCREAMING_SNAKE_CASE     					=scale_embedding  # scale factor will be sqrt(d_model) if True
										super().__init__(
										    pad_token_id=_a			,      bos_token_id=_a			,      eos_token_id=_a			,      is_encoder_decoder=_a			,      forced_eos_token_id=_a			,      **_a			,      )

class   A__							(						UpperCamelCase__					):




						@property
						def 							__UpperCamelCase			(    self   : int					)							->       Mapping[str, Mapping[int, str]]:


										"""simple docstring"""





										return OrderedDict(
										    [
										        ('''input_ids''', {0: '''batch''', 1: '''sequence'''}),
										        ('''attention_mask''', {0: '''batch''', 1: '''sequence'''}),
										    ]					)




						@property
						def 							__UpperCamelCase			(    self   : List[str]					)							->       Mapping[str, Mapping[int, str]]:


										"""simple docstring"""





										if self.use_past:
														return OrderedDict(
														    [
														        ('''last_hidden_state''', {0: '''batch''', 1: '''sequence'''}),
														        ('''past_keys''', {0: '''batch''', 2: '''sequence'''}),
														        ('''encoder_last_hidden_state''', {0: '''batch''', 1: '''sequence'''}),
														    ]					)
										else:
														return OrderedDict(
														    [
														        ('''last_hidden_state''', {0: '''batch''', 1: '''sequence'''}),
														        ('''encoder_last_hidden_state''', {0: '''batch''', 1: '''sequence'''}),
														    ]					)