

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


_SCREAMING_SNAKE_CASE					:  Tuple             =      logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE					:  Union[str, Any]             =      {
    '''unc-nlp/lxmert-base-uncased''': '''https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json''',
}






class 	UpperCAmelCase__		(	A__	):






  """simple docstring"""


  a									= "lxmert"
  a									= {}






  def __init__(							self						:		Dict     ,       __lowerCamelCase						:		Any=3_0522     ,       __lowerCamelCase						:		int=768     ,       __lowerCamelCase						:		Optional[int]=12     ,       __lowerCamelCase						:		Dict=9500     ,       __lowerCamelCase						:		List[str]=1600     ,       __lowerCamelCase						:		Tuple=400     ,       __lowerCamelCase						:		List[str]=3072     ,       __lowerCamelCase						:		str="gelu"     ,       __lowerCamelCase						:		Dict=0.1     ,       __lowerCamelCase						:		Optional[int]=0.1     ,       __lowerCamelCase						:		List[str]=512     ,       __lowerCamelCase						:		Any=2     ,       __lowerCamelCase						:		Union[str, Any]=0.02     ,       __lowerCamelCase						:		str=1e-12     ,       __lowerCamelCase						:		Optional[Any]=9     ,       __lowerCamelCase						:		List[Any]=5     ,       __lowerCamelCase						:		List[str]=5     ,       __lowerCamelCase						:		List[Any]=2048     ,       __lowerCamelCase						:		int=4     ,       __lowerCamelCase						:		Tuple=6.67     ,       __lowerCamelCase						:		Optional[int]=True     ,       __lowerCamelCase						:		Optional[int]=True     ,       __lowerCamelCase						:		List[str]=True     ,       __lowerCamelCase						:		List[str]=True     ,       __lowerCamelCase						:		str=True     ,       __lowerCamelCase						:		Tuple=True     ,       __lowerCamelCase						:		str=True     ,       **__lowerCamelCase						:		List[Any]     ,       )		->							Dict:
       SCREAMING_SNAKE_CASE__   =   vocab_size
       SCREAMING_SNAKE_CASE__   =   hidden_size
       SCREAMING_SNAKE_CASE__   =   num_attention_heads
       SCREAMING_SNAKE_CASE__   =   hidden_act
       SCREAMING_SNAKE_CASE__   =   intermediate_size
       SCREAMING_SNAKE_CASE__   =   hidden_dropout_prob
       SCREAMING_SNAKE_CASE__   =   attention_probs_dropout_prob
       SCREAMING_SNAKE_CASE__   =   max_position_embeddings
       SCREAMING_SNAKE_CASE__   =   type_vocab_size
       SCREAMING_SNAKE_CASE__   =   initializer_range
       SCREAMING_SNAKE_CASE__   =   layer_norm_eps
       SCREAMING_SNAKE_CASE__   =   num_qa_labels
       SCREAMING_SNAKE_CASE__   =   num_object_labels
       SCREAMING_SNAKE_CASE__   =   num_attr_labels
       SCREAMING_SNAKE_CASE__   =   l_layers
       SCREAMING_SNAKE_CASE__   =   x_layers
       SCREAMING_SNAKE_CASE__   =   r_layers
       SCREAMING_SNAKE_CASE__   =   visual_feat_dim
       SCREAMING_SNAKE_CASE__   =   visual_pos_dim
       SCREAMING_SNAKE_CASE__   =   visual_loss_normalizer
       SCREAMING_SNAKE_CASE__   =   task_matched
       SCREAMING_SNAKE_CASE__   =   task_mask_lm
       SCREAMING_SNAKE_CASE__   =   task_obj_predict
       SCREAMING_SNAKE_CASE__   =   task_qa
       SCREAMING_SNAKE_CASE__   =   visual_obj_loss
       SCREAMING_SNAKE_CASE__   =   visual_attr_loss
       SCREAMING_SNAKE_CASE__   =   visual_feat_loss
       SCREAMING_SNAKE_CASE__   =   {'''vision''': r_layers, '''cross_encoder''': x_layers, '''language''': l_layers}
       super().__init__(**__lowerCamelCase )







from __future__ import annotations

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

from matplotlib import pyplot as plt
def     UpperCAmelCase_       (						_A				,		_A				,		_A    ):





     '''simple docstring'''




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

     SCREAMING_SNAKE_CASE__   =   (low + high) // 2
     SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__   =   max_subarray(_A				,		_A				,		_A    )
     SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__   =   max_subarray(_A				,		mid + 1				,		_A    )
     SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__   =   max_cross_sum(_A				,		_A				,		_A				,		_A    )
     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     UpperCAmelCase_       (						_A				,		_A				,		_A				,		_A    ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__   =   float('''-inf'''    ), -1
     SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__   =   float('''-inf'''    ), -1

     SCREAMING_SNAKE_CASE__   =   0
     for i in range(_A				,		low - 1				,		-1    ):
          summ += arr[i]
          if summ > left_sum:
               SCREAMING_SNAKE_CASE__   =   summ
               SCREAMING_SNAKE_CASE__   =   i

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

     return max_left, max_right, (left_sum + right_sum)
def     UpperCAmelCase_       (						_A    ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__   =   [randint(1				,		_A    ) for _ in range(_A    )]
     SCREAMING_SNAKE_CASE__   =   time.time()
     max_subarray(_A				,		0				,		input_size - 1    )
     SCREAMING_SNAKE_CASE__   =   time.time()
     return end - start
def     UpperCAmelCase_       (						):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__   =   [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__   =   [time_max_subarray(_A    ) for input_size in input_sizes]
     print('''No of Inputs\t\tTime Taken'''    )
     for input_size, runtime in zip(_A				,		_A    ):
          print(_A				,		'''\t\t'''				,		_A    )
     plt.plot(_A				,		_A    )
     plt.xlabel('''Number of Inputs'''    )
     plt.ylabel('''Time taken in seconds'''    )
     plt.show()


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

       testmod()


