





'''simple docstring'''







def  _lowerCamelCase				( )	->	list[list[int]]:
				return [list(range(1000 - i    ,							-1000 - i    ,							-1						)						) for i in range(1000						)]


lowerCAmelCase_					:    Tuple      	=			generate_large_matrix()
lowerCAmelCase_					:    Union[str, Any]      	=			(
    [[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -2, -3]],
    [[3, 2], [1, 0]],
    [[7, 7, 6]],
    [[7, 7, 6], [-1, -2, -3]],
    grid,
)






def  _lowerCamelCase				( lowercase						:      list[list[int]]						)	->	None:
				assert all(row == sorted(lowercase    ,							reverse=lowercase						) for row in grid						)
				assert all(list(lowercase						) == sorted(lowercase    ,							reverse=lowercase						) for col in zip(*lowercase						)						)






def  _lowerCamelCase				( lowercase						:      list[int]						)	->	int:
				_a								= 0
				_a								= len(lowercase						) - 1

				# Edge cases such as no values or all numbers are negative.
				if not array or array[0] < 0:
								return 0

				while right + 1 > left:
								_a								= (left + right) // 2
								_a								= array[mid]

								# Num must be negative and the index must be greater than or equal to 0.
								if num < 0 and array[mid - 1] >= 0:
												return mid

								if num >= 0:
												_a								= mid + 1
								else:
												_a								= mid - 1
    # No negative numbers so return the last index of the array + 1 which is the length.
				return len(lowercase						)






def  _lowerCamelCase				( lowercase						:      list[list[int]]						)	->	int:
				_a								= 0
				_a								= len(grid[0]						)

				for i in range(len(lowercase						)						):
								_a								= find_negative_index(grid[i][:bound]						)
								total += bound
				return (len(lowercase						) * len(grid[0]						)) - total






def  _lowerCamelCase				( lowercase						:      list[list[int]]						)	->	int:
				return len([number for row in grid for number in row if number < 0]						)






def  _lowerCamelCase				( lowercase						:      list[list[int]]						)	->	int:
				_a								= 0
				for row in grid:
								for i, number in enumerate(lowercase						):
												if number < 0:
																total += len(lowercase						) - i
																break
				return total






def  _lowerCamelCase				( )	->	None:
				from timeit import timeit

				print("Running benchmarks"						)
				_a								= (
				    "from __main__ import count_negatives_binary_search, "
				    "count_negatives_brute_force, count_negatives_brute_force_with_break, grid"
				)
				for func in (
				    "count_negatives_binary_search",  # took 0.7727 seconds
				    "count_negatives_brute_force_with_break",  # took 4.6505 seconds
				    "count_negatives_brute_force",  # took 12.8160 seconds
				):
								_a								= timeit(F'{func}(grid=grid)'    ,							setup=lowercase    ,							number=500						)
								print(F'{func}() took {time:0.4f} seconds'						)


if __name__ == "__main__":
					import doctest

					doctest.testmod()
					benchmark()







'''simple docstring'''







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


lowerCAmelCase_					:    Dict      	=			logging.get_logger(__name__)

lowerCAmelCase_					:    int      	=			{
    'bigcode/gpt_bigcode-santacoder': 'https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json',
}
class 				__SCREAMING_SNAKE_CASE  (lowerCamelCase_      ):






				"""simple docstring"""







				__a            ='gpt_bigcode'
				__a            =['past_key_values']
				__a            ={
				    'hidden_size': 'n_embd',
				    'max_position_embeddings': 'n_positions',
				    'num_attention_heads': 'n_head',
				    'num_hidden_layers': 'n_layer',
				}




				def __init__(  self     :					Optional[Any]					,				__a     :					Tuple=5_02_57					,				__a     :					str=10_24					,				__a     :					Dict=7_68					,				__a     :					Tuple=12					,				__a     :					str=12					,				__a     :					Optional[int]=None					,				__a     :					Dict="gelu_pytorch_tanh"					,				__a     :					Tuple=0.1					,				__a     :					Tuple=0.1					,				__a     :					Union[str, Any]=0.1					,				__a     :					Tuple=1e-5					,				__a     :					str=0.02					,				__a     :					Dict=True					,				__a     :					Union[str, Any]=True					,				__a     :					Optional[int]=5_02_56					,				__a     :					Optional[int]=5_02_56					,				__a     :					Union[str, Any]=True					,				__a     :					Dict=True					,				__a     :					Union[str, Any]=True					,				**__a     :					List[Any]					,				):
								_a								= vocab_size
								_a								= n_positions
								_a								= n_embd
								_a								= n_layer
								_a								= n_head
								_a								= n_inner
								_a								= activation_function
								_a								= resid_pdrop
								_a								= embd_pdrop
								_a								= attn_pdrop
								_a								= layer_norm_epsilon
								_a								= initializer_range
								_a								= scale_attn_weights
								_a								= use_cache
								_a								= attention_softmax_in_fpaa
								_a								= scale_attention_softmax_in_fpaa
								_a								= multi_query

								_a								= bos_token_id
								_a								= eos_token_id

								super().__init__(bos_token_id=__a					,				eos_token_id=__a					,				**__a					)
