





'''simple docstring'''


from collections import OrderedDict
from typing import Mapping

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


_lowerCamelCase				:	int				    =       logging.get_logger(__name__)

_lowerCamelCase				:	Optional[Any]				    =       {
    '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 							__UpperCAmelCase  (       A_						):







		'''simple docstring'''







		__lowerCAmelCase 				=    '''plbart'''
		__lowerCAmelCase 				=    ['''past_key_values''']
		__lowerCAmelCase 				=    {'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}







		def __init__(self						:      List[Any]      ,      _lowerCAmelCase						:      int=5_0005      ,      _lowerCAmelCase						:      Tuple=1024      ,      _lowerCAmelCase						:      Optional[int]=6      ,      _lowerCAmelCase						:      Any=3072      ,      _lowerCAmelCase						:      Any=12      ,      _lowerCAmelCase						:      List[str]=6      ,      _lowerCAmelCase						:      Any=3072      ,      _lowerCAmelCase						:      Optional[int]=12      ,      _lowerCAmelCase						:      Any=0.0      ,      _lowerCAmelCase						:      Optional[Any]=0.0      ,      _lowerCAmelCase						:      str=True      ,      _lowerCAmelCase						:      List[Any]=True      ,      _lowerCAmelCase						:      List[str]="gelu"      ,      _lowerCAmelCase						:      List[Any]=768      ,      _lowerCAmelCase						:      Tuple=0.1      ,      _lowerCAmelCase						:      Optional[Any]=0.1      ,      _lowerCAmelCase						:      int=0.0      ,      _lowerCAmelCase						:      Any=0.02      ,      _lowerCAmelCase						:      int=0.0      ,      _lowerCAmelCase						:      Dict=True      ,      _lowerCAmelCase						:      Any=1      ,      _lowerCAmelCase						:      Optional[Any]=0      ,      _lowerCAmelCase						:      List[str]=2      ,      _lowerCAmelCase						:      Optional[Any]=2      ,      **_lowerCAmelCase						:      int      ,      ):
			A							  =      vocab_size
			A							  =      max_position_embeddings
			A							  =      d_model
			A							  =      encoder_ffn_dim
			A							  =      encoder_layers
			A							  =      encoder_attention_heads
			A							  =      decoder_ffn_dim
			A							  =      decoder_layers
			A							  =      decoder_attention_heads
			A							  =      dropout
			A							  =      attention_dropout
			A							  =      activation_dropout
			A							  =      activation_function
			A							  =      init_std
			A							  =      encoder_layerdrop
			A							  =      decoder_layerdrop
			A							  =      classifier_dropout
			A							  =      use_cache
			A							  =      encoder_layers
			A							  =      scale_embedding  # scale factor will be sqrt(d_model) if True
			super().__init__(
			    pad_token_id=_lowerCAmelCase      ,      bos_token_id=_lowerCAmelCase      ,      eos_token_id=_lowerCAmelCase      ,      is_encoder_decoder=_lowerCAmelCase      ,      forced_eos_token_id=_lowerCAmelCase      ,      **_lowerCAmelCase      ,      )






class 							__UpperCAmelCase  (       A_						):







		'''simple docstring'''







		@property
		def        A     (self						:      Optional[int]      ):
			return OrderedDict(
			    [
			        ("""input_ids""", {0: """batch""", 1: """sequence"""}),
			        ("""attention_mask""", {0: """batch""", 1: """sequence"""}),
			    ]      )







		@property
		def        A     (self						:      Tuple      ):



			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"""}),
				    ]      )








'''simple docstring'''


class 							__UpperCAmelCase  :







		'''simple docstring'''







		def __init__(self						:      List[str]      ):
			# numbermap keys are the number and its values are lists of indexes sorted
			# in ascending order
			A							  =      {}
			# indexmap keys are an index and it's values are the number at that index
			A							  =      {}







		def        A     (self						:      Union[str, Any]      ,      _lowerCAmelCase						:      list | str | range      ,      _lowerCAmelCase						:      int      ):
			if isinstance(_lowerCAmelCase      ,      (range, str)      ):
				A							  =      list(_lowerCAmelCase      )
			elif not isinstance(_lowerCAmelCase      ,      _lowerCAmelCase      ):
				raise TypeError(
				    """binary_search_delete() only accepts either a list, range or str"""      )

			A							  =      0
			A							  =      len(_lowerCAmelCase      ) - 1

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







		def        A     (self						:      Dict      ,      _lowerCAmelCase						:      list | str | range      ,      _lowerCAmelCase						:      int      ):
			if isinstance(_lowerCAmelCase      ,      (range, str)      ):
				A							  =      list(_lowerCAmelCase      )
			elif not isinstance(_lowerCAmelCase      ,      _lowerCAmelCase      ):
				raise TypeError(
				    """binary_search_insert() only accepts either a list, range or str"""      )

			A							  =      0
			A							  =      len(_lowerCAmelCase      ) - 1

			while low <= high:
				A							  =      (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      ,      _lowerCAmelCase      )
					return array
				elif array[mid] < index:
					A							  =      mid + 1
				else:
					A							  =      mid - 1

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







		def        A     (self						:      List[str]      ,      _lowerCAmelCase						:      int      ,      _lowerCAmelCase						:      int      ):
			# Remove previous index
			if index in self.indexmap:
				A							  =      self.indexmap[index]
				if len(self.numbermap[n]      ) == 1:
					del self.numbermap[n]
				else:
					A							  =      self.binary_search_delete(self.numbermap[n]      ,      _lowerCAmelCase      )

        # Set new index
			A							  =      number

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

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







		def        A     (self						:      int      ,      _lowerCAmelCase						:      int      ):
			return self.numbermap.get(_lowerCAmelCase      ,      [-1]      )[0]


if __name__ == "__main__":
				import doctest

				doctest.testmod()

