
from __future__ import annotations

from abc import abstractmethod
from collections.abc import Iterable
from typing import Generic, Protocol, TypeVar






class     a_       (			UpperCAmelCase_							):



       """simple docstring"""






       @abstractmethod
       def __lt__(		self				,       _lowerCamelCase   )					->bool:
           pass






       @abstractmethod
       def __gt__(		self				,       _lowerCamelCase   )					->bool:
           pass






       @abstractmethod
       def __eq__(		self				,       _lowerCamelCase   )					->bool:
           pass





a__				:      List[str]    		=     TypeVar('''T''', bound=Comparable)






class     a_       (			Generic[T]							):



       """simple docstring"""






       def __init__(		self   )					->None:
           SCREAMING_SNAKE_CASE				:				list[T]				      = []
           SCREAMING_SNAKE_CASE				:				int				      = 0






       def __repr__(		self   )					->str:
           return str(self.h   )






       def 	__lowerCAmelCase     (		self				,       _lowerCamelCase   )					->int | None:
           if child_idx > 0:
               return (child_idx - 1) // 2
           return None






       def 	__lowerCAmelCase     (		self				,       _lowerCamelCase   )					->int | None:
           SCREAMING_SNAKE_CASE				:				str				      = 2 * parent_idx + 1
           if left_child_index < self.heap_size:
               return left_child_index
           return None






       def 	__lowerCAmelCase     (		self				,       _lowerCamelCase   )					->int | None:
           SCREAMING_SNAKE_CASE				:				Optional[int]				      = 2 * parent_idx + 2
           if right_child_index < self.heap_size:
               return right_child_index
           return None






       def 	__lowerCAmelCase     (		self				,       _lowerCamelCase   )					->None:
           if index < self.heap_size:
               SCREAMING_SNAKE_CASE				:				int				      = index
               SCREAMING_SNAKE_CASE				:				str				      = self.left_child_idx(a__   )
               SCREAMING_SNAKE_CASE				:				Tuple				      = self.right_child_idx(a__   )
               # check which child is larger than its parent
               if left_child is not None and self.h[left_child] > self.h[violation]:
                   SCREAMING_SNAKE_CASE				:				Union[str, Any]				      = left_child
               if right_child is not None and self.h[right_child] > self.h[violation]:
                   SCREAMING_SNAKE_CASE				:				str				      = right_child
               # if violation indeed exists
               if violation != index:
                   # swap to fix the violation
                   SCREAMING_SNAKE_CASE				:				Any				      = self.h[index], self.h[violation]
                   # fix the subsequent violation recursively if any
                   self.max_heapify(a__   )






       def 	__lowerCAmelCase     (		self				,       _lowerCamelCase   )					->None:
           SCREAMING_SNAKE_CASE				:				Optional[Any]				      = list(a__   )
           SCREAMING_SNAKE_CASE				:				Optional[Any]				      = len(self.h   )
           if self.heap_size > 1:
               # max_heapify from right to left but exclude leaves (last level)
               for i in range(self.heap_size // 2 - 1				,       -1				,       -1   ):
                   self.max_heapify(a__   )






       def 	__lowerCAmelCase     (		self   )					->T:
           if self.heap_size >= 2:
               SCREAMING_SNAKE_CASE				:				Union[str, Any]				      = self.h[0]
               SCREAMING_SNAKE_CASE				:				Tuple				      = self.h.pop(-1   )
               self.heap_size -= 1
               self.max_heapify(0   )
               return me
           elif self.heap_size == 1:
               self.heap_size -= 1
               return self.h.pop(-1   )
           else:
               raise Exception('''Empty heap'''   )






       def 	__lowerCAmelCase     (		self				,       _lowerCamelCase   )					->None:
           self.h.append(a__   )
           SCREAMING_SNAKE_CASE				:				List[Any]				      = (self.heap_size - 1) // 2
           self.heap_size += 1
           while idx >= 0:
               self.max_heapify(a__   )
               SCREAMING_SNAKE_CASE				:				Optional[int]				      = (idx - 1) // 2






       def 	__lowerCAmelCase     (		self   )					->None:
           SCREAMING_SNAKE_CASE				:				Dict				      = self.heap_size
           for j in range(size - 1				,       0				,       -1   ):
               SCREAMING_SNAKE_CASE				:				Dict				      = self.h[j], self.h[0]
               self.heap_size -= 1
               self.max_heapify(0   )
           SCREAMING_SNAKE_CASE				:				int				      = size


if __name__ == "__main__":
      import doctest

      # run doc test
      doctest.testmod()

      # demo
      for unsorted in [
          [0],
          [2],
          [3, 5],
          [5, 3],
          [5, 5],
          [0, 0, 0, 0],
          [1, 1, 1, 1],
          [2, 2, 3, 5],
          [0, 2, 2, 3, 5],
          [2, 5, 3, 0, 2, 3, 0, 3],
          [6, 1, 2, 7, 9, 3, 4, 5, 10, 8],
          [103, 9, 1, 7, 11, 15, 25, 201, 209, 107, 5],
          [-45, -2, -5],
      ]:
            print(F"unsorted array: {unsorted}")

            a__				:      int    		=     Heap()
            heap.build_max_heap(unsorted)
            print(F"after build heap: {heap}")

            print(F"max value: {heap.extract_max()}")
            print(F"after max value removed: {heap}")

            heap.insert(100)
            print(F"after new value 100 inserted: {heap}")

            heap.heap_sort()
            print(F"heap-sorted array: {heap}\n")






'''simple docstring'''





from typing import Mapping

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


lowercase__								=						logging.get_logger(__name__)






class     lowercase  ( UpperCAmelCase_):
      __lowercase					=	'''mt5'''
      __lowercase					=	['''past_key_values''']






      def __init__(self			,	a__=2_5_0_1_1_2			,	a__=5_1_2			,	a__=6_4			,	a__=1_0_2_4			,	a__=8			,	a__=None			,	a__=6			,	a__=3_2			,	a__=1_2_8			,	a__=0.1			,	a__=1E-6			,	a__=1.0			,	a__="gated-gelu"			,	a__=True			,	a__=True			,	a__="T5Tokenizer"			,	a__=False			,	a__=0			,	a__=1			,	a__=0			,	**a__			,	)							-> List[Any]:
         super().__init__(
             is_encoder_decoder=a__			,	tokenizer_class=a__			,	tie_word_embeddings=a__			,	pad_token_id=a__			,	eos_token_id=a__			,	decoder_start_token_id=a__			,	**a__			,	)
         SCREAMING_SNAKE_CASE__      :					Optional[int]							    =			vocab_size
         SCREAMING_SNAKE_CASE__      :					Tuple							    =			d_model
         SCREAMING_SNAKE_CASE__      :					Optional[Any]							    =			d_kv
         SCREAMING_SNAKE_CASE__      :					Optional[int]							    =			d_ff
         SCREAMING_SNAKE_CASE__      :					Optional[Any]							    =			num_layers
         SCREAMING_SNAKE_CASE__      :					Optional[int]							    =			(
             num_decoder_layers if num_decoder_layers is not None else self.num_layers
         )  # default = symmetry
         SCREAMING_SNAKE_CASE__      :					Any							    =			num_heads
         SCREAMING_SNAKE_CASE__      :					Any							    =			relative_attention_num_buckets
         SCREAMING_SNAKE_CASE__      :					Any							    =			relative_attention_max_distance
         SCREAMING_SNAKE_CASE__      :					Any							    =			dropout_rate
         SCREAMING_SNAKE_CASE__      :					Optional[int]							    =			layer_norm_epsilon
         SCREAMING_SNAKE_CASE__      :					List[str]							    =			initializer_factor
         SCREAMING_SNAKE_CASE__      :					List[Any]							    =			feed_forward_proj
         SCREAMING_SNAKE_CASE__      :					Any							    =			use_cache

         SCREAMING_SNAKE_CASE__      :					int							    =			self.feed_forward_proj.split('''-'''       )
         SCREAMING_SNAKE_CASE__      :					Optional[int]							    =			act_info[-1]
         SCREAMING_SNAKE_CASE__      :					Union[str, Any]							    =			act_info[0] == '''gated'''

         if len(a__       ) > 1 and act_info[0] != "gated" or len(a__       ) > 2:
            raise ValueError(
                f"""`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer."""
                '''Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. '''
                '''\'gated-gelu\' or \'relu\''''       )

         # for backwards compatibility
         if feed_forward_proj == "gated-gelu":
            SCREAMING_SNAKE_CASE__      :					int							    =			'''gelu_new'''






      @property
      def  A__(self       )							-> Dict:
         return self.d_model






      @property
      def  A__(self       )							-> Tuple:
         return self.num_heads






      @property
      def  A__(self       )							-> List[str]:
         return self.num_layers






class     lowercase  ( UpperCAmelCase_):






      @property
      # Copied from transformers.models.t5.configuration_t5.T5OnnxConfig.inputs
      def  A__(self       )							-> Mapping[str, Mapping[int, str]]:
         SCREAMING_SNAKE_CASE__      :					List[Any]							    =			{
             '''input_ids''': {0: '''batch''', 1: '''encoder_sequence'''},
             '''attention_mask''': {0: '''batch''', 1: '''encoder_sequence'''},
         }
         if self.use_past:
            SCREAMING_SNAKE_CASE__      :					Union[str, Any]							    =			'''past_encoder_sequence + sequence'''
            SCREAMING_SNAKE_CASE__      :					str							    =			{0: '''batch'''}
            SCREAMING_SNAKE_CASE__      :					List[Any]							    =			{0: '''batch''', 1: '''past_decoder_sequence + sequence'''}
         else:
            SCREAMING_SNAKE_CASE__      :					int							    =			{0: '''batch''', 1: '''decoder_sequence'''}
            SCREAMING_SNAKE_CASE__      :					Tuple							    =			{0: '''batch''', 1: '''decoder_sequence'''}

         if self.use_past:
            self.fill_with_past_key_values_(a__			,	direction='''inputs'''       )

         return common_inputs






      @property
      # Copied from transformers.models.t5.configuration_t5.T5OnnxConfig.default_onnx_opset
      def  A__(self       )							-> int:
         return 1_3






      @property
      def  A__(self       )							-> float:
         return 5E-4

