




'''simple docstring'''



from __future__ import annotations

import time
from collections.abc import Sequence
from random import randint

from matplotlib import pyplot as plt




def    lowercase__(       __UpperCamelCase: Sequence[float]	,__UpperCamelCase: int	,__UpperCamelCase: int  ):

      """simple docstring"""






      if not arr:
            return None, None, 0
      if low == high:
            return low, high, arr[low]

      SCREAMING_SNAKE_CASE					:	Dict   =		(low + high) // 2
      SCREAMING_SNAKE_CASE					:	Tuple   =		max_subarray(snake_case_	,snake_case_	,snake_case_  )
      SCREAMING_SNAKE_CASE					:	Union[str, Any]   =		max_subarray(snake_case_	,mid + 1	,snake_case_  )
      SCREAMING_SNAKE_CASE					:	Union[str, Any]   =		max_cross_sum(snake_case_	,snake_case_	,snake_case_	,snake_case_  )
      if left_sum >= right_sum and left_sum >= cross_sum:
            return left_low, left_high, left_sum
      elif right_sum >= left_sum and right_sum >= cross_sum:
            return right_low, right_high, right_sum
      return cross_left, cross_right, cross_sum




def    lowercase__(       __UpperCamelCase: Sequence[float]	,__UpperCamelCase: int	,__UpperCamelCase: int	,__UpperCamelCase: int  ):

      """simple docstring"""






      SCREAMING_SNAKE_CASE					:	Dict   =		float('-inf'  ), -1
      SCREAMING_SNAKE_CASE					:	List[Any]   =		float('-inf'  ), -1

      SCREAMING_SNAKE_CASE					:	int | float   =		0
      for i in range(snake_case_	,low - 1	,-1  ):
            summ += arr[i]
            if summ > left_sum:
                  SCREAMING_SNAKE_CASE					:	str   =		summ
                  SCREAMING_SNAKE_CASE					:	Optional[int]   =		i

      SCREAMING_SNAKE_CASE					:	Any   =		0
      for i in range(mid + 1	,high + 1  ):
            summ += arr[i]
            if summ > right_sum:
                  SCREAMING_SNAKE_CASE					:	int   =		summ
                  SCREAMING_SNAKE_CASE					:	Tuple   =		i

      return max_left, max_right, (left_sum + right_sum)




def    lowercase__(       __UpperCamelCase: int  ):

      """simple docstring"""






      SCREAMING_SNAKE_CASE					:	Union[str, Any]   =		[randint(1	,snake_case_  ) for _ in range(snake_case_  )]
      SCREAMING_SNAKE_CASE					:	Optional[Any]   =		time.time()
      max_subarray(snake_case_	,0	,input_size - 1  )
      SCREAMING_SNAKE_CASE					:	Dict   =		time.time()
      return end - start




def    lowercase__(       ):

      """simple docstring"""






      SCREAMING_SNAKE_CASE					:	Optional[int]   =		[10, 1_00, 10_00, 1_00_00, 5_00_00, 10_00_00, 20_00_00, 30_00_00, 40_00_00, 50_00_00]
      SCREAMING_SNAKE_CASE					:	List[str]   =		[time_max_subarray(snake_case_  ) for input_size in input_sizes]
      print('No of Inputs\t\tTime Taken'  )
      for input_size, runtime in zip(snake_case_	,snake_case_  ):
            print(snake_case_	,'\t\t'	,snake_case_  )
      plt.plot(snake_case_	,snake_case_  )
      plt.xlabel('Number of Inputs'  )
      plt.ylabel('Time taken in seconds'  )
      plt.show()


if __name__ == "__main__":
      from doctest import testmod

      testmod()









"""simple docstring"""



from collections import OrderedDict
from typing import Mapping

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


a_ =			logging.get_logger(__name__)

a_ =			{
    """bert-base-uncased""": """https://huggingface.co/bert-base-uncased/resolve/main/config.json""",
    """bert-large-uncased""": """https://huggingface.co/bert-large-uncased/resolve/main/config.json""",
    """bert-base-cased""": """https://huggingface.co/bert-base-cased/resolve/main/config.json""",
    """bert-large-cased""": """https://huggingface.co/bert-large-cased/resolve/main/config.json""",
    """bert-base-multilingual-uncased""": """https://huggingface.co/bert-base-multilingual-uncased/resolve/main/config.json""",
    """bert-base-multilingual-cased""": """https://huggingface.co/bert-base-multilingual-cased/resolve/main/config.json""",
    """bert-base-chinese""": """https://huggingface.co/bert-base-chinese/resolve/main/config.json""",
    """bert-base-german-cased""": """https://huggingface.co/bert-base-german-cased/resolve/main/config.json""",
    """bert-large-uncased-whole-word-masking""": (
        """https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/config.json"""
    ),
    """bert-large-cased-whole-word-masking""": (
        """https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/config.json"""
    ),
    """bert-large-uncased-whole-word-masking-finetuned-squad""": (
        """https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/config.json"""
    ),
    """bert-large-cased-whole-word-masking-finetuned-squad""": (
        """https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/config.json"""
    ),
    """bert-base-cased-finetuned-mrpc""": """https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/config.json""",
    """bert-base-german-dbmdz-cased""": """https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/config.json""",
    """bert-base-german-dbmdz-uncased""": """https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/config.json""",
    """cl-tohoku/bert-base-japanese""": """https://huggingface.co/cl-tohoku/bert-base-japanese/resolve/main/config.json""",
    """cl-tohoku/bert-base-japanese-whole-word-masking""": (
        """https://huggingface.co/cl-tohoku/bert-base-japanese-whole-word-masking/resolve/main/config.json"""
    ),
    """cl-tohoku/bert-base-japanese-char""": (
        """https://huggingface.co/cl-tohoku/bert-base-japanese-char/resolve/main/config.json"""
    ),
    """cl-tohoku/bert-base-japanese-char-whole-word-masking""": (
        """https://huggingface.co/cl-tohoku/bert-base-japanese-char-whole-word-masking/resolve/main/config.json"""
    ),
    """TurkuNLP/bert-base-finnish-cased-v1""": (
        """https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/config.json"""
    ),
    """TurkuNLP/bert-base-finnish-uncased-v1""": (
        """https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/config.json"""
    ),
    """wietsedv/bert-base-dutch-cased""": """https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/config.json""",
    # See all BERT models at https://huggingface.co/models?filter=bert
}






class 		__snake_case					(		SCREAMING_SNAKE_CASE__     ):





 """simple docstring"""


 _lowerCamelCase        =     """bert"""

 def __init__(    self					,						__lowerCamelCase=3_0522					,						__lowerCamelCase=768					,						__lowerCamelCase=12					,						__lowerCamelCase=12					,						__lowerCamelCase=3072					,						__lowerCamelCase="gelu"					,						__lowerCamelCase=0.1					,						__lowerCamelCase=0.1					,						__lowerCamelCase=512					,						__lowerCamelCase=2					,						__lowerCamelCase=0.0_2					,						__lowerCamelCase=1e-1_2					,						__lowerCamelCase=0					,						__lowerCamelCase="absolute"					,						__lowerCamelCase=True					,						__lowerCamelCase=None					,						**__lowerCamelCase					,						):



     '''simple docstring'''




     super().__init__(pad_token_id=__lowerCamelCase					,						**__lowerCamelCase  )

     __A    :						Dict						 =     vocab_size
     __A    :						Any						 =     hidden_size
     __A    :						str						 =     num_hidden_layers
     __A    :						int						 =     num_attention_heads
     __A    :						Optional[int]						 =     hidden_act
     __A    :						List[Any]						 =     intermediate_size
     __A    :						Tuple						 =     hidden_dropout_prob
     __A    :						Optional[int]						 =     attention_probs_dropout_prob
     __A    :						Optional[int]						 =     max_position_embeddings
     __A    :						Optional[Any]						 =     type_vocab_size
     __A    :						Optional[Any]						 =     initializer_range
     __A    :						Dict						 =     layer_norm_eps
     __A    :						Any						 =     position_embedding_type
     __A    :						Optional[int]						 =     use_cache
     __A    :						str						 =     classifier_dropout






class 		__snake_case					(		SCREAMING_SNAKE_CASE__     ):





 """simple docstring"""


 @property
 def 					UpperCamelCase__(    self  ):



     '''simple docstring'''




     if self.task == "multiple-choice":
         __A    :						str						 =     {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
     else:
         __A    :						Tuple						 =     {0: '''batch''', 1: '''sequence'''}
     return OrderedDict(
         [
             ('''input_ids''', dynamic_axis),
             ('''attention_mask''', dynamic_axis),
             ('''token_type_ids''', dynamic_axis),
         ]  )




