import timeit



class    lowercase_    :



							def __init__(						self      ,				lowercase_				):
													if isinstance(lowercase_      ,				lowercase_				):  # Initializes a matrix identical to the one provided.
																			_snake_case						:     int				=    arg
																			_snake_case						:     Union[str, Any]				=    len(lowercase_				)
													else:  # Initializes a square matrix of the given size and set values to zero.
																			_snake_case						:     Dict				=    arg
																			_snake_case						:     Optional[Any]				=    [[0 for _ in range(self.n				)] for _ in range(self.n				)]



							def __mul__(						self      ,				lowercase_				):
													_snake_case						:     Tuple				=    Matrix(self.n				)
													for i in range(self.n				):
																			for j in range(self.n				):
																									for k in range(self.n				):
																															matrix.t[i][j] += self.t[i][k] * b.t[k][j]
													return matrix




def 					snake_case						(__lowercase					,			__lowercase						)       ->       Tuple:

						'''simple docstring'''



						_snake_case						:     Any				=    Matrix([[1, 0], [0, 1]]						)
						while b > 0:
												if b & 1:
																		matrix *= a
												a *= a
												b >>= 1
						return matrix
def 					snake_case						(__lowercase					,			__lowercase					,			__lowercase						)       ->       Any:

						'''simple docstring'''



						if n == 1:
												return fa
						elif n == 2:
												return fa
						_snake_case						:     List[str]				=    Matrix([[1, 1], [1, 0]]						)
						_snake_case						:     List[str]				=    modular_exponentiation(__lowercase					,			n - 2						)
						return fa * matrix.t[0][0] + fa * matrix.t[0][1]
def 					snake_case						(__lowercase					,			__lowercase					,			__lowercase						)       ->       Union[str, Any]:

						'''simple docstring'''



						if n == 1:
												return fa
						elif n == 2:
												return fa

						_snake_case						:     Union[str, Any]				=    fa
						_snake_case						:     Optional[int]				=    fa
						n -= 2

						while n > 0:
												_snake_case				,_snake_case						:     Tuple				=    fn_a + fn_a, fn_a
												n -= 1

						return fn_a
def 					snake_case						()       ->       List[str]:

						'''simple docstring'''



						_snake_case						:     List[str]				=    "\nfrom random import randint\nfrom __main__ import fibonacci_with_matrix_exponentiation\n"
						_snake_case						:     Optional[Any]				=    "fibonacci_with_matrix_exponentiation(randint(1,70000), 1, 1)"
						_snake_case						:     str				=    timeit.timeit(setup=__lowercase					,			stmt=__lowercase					,			number=100						)
						print("With matrix exponentiation the average execution time is "					,			exec_time / 100						)
						return exec_time
def 					snake_case						()       ->       Optional[int]:

						'''simple docstring'''



						_snake_case						:     int				=    "\nfrom random import randint\nfrom __main__ import simple_fibonacci\n"
						_snake_case						:     Any				=    "simple_fibonacci(randint(1,70000), 1, 1)"
						_snake_case						:     List[str]				=    timeit.timeit(setup=__lowercase					,			stmt=__lowercase					,			number=100						)
						print(
						    "Without matrix exponentiation the average execution time is "					,			exec_time / 100						)
						return exec_time
def 					snake_case						()       ->       int:

						'''simple docstring'''



						matrix_exponentiation_time()
						simple_fibonacci_time()


if __name__ == "__main__":
				main()







"""simple docstring"""







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


lowerCAmelCase_		:			str				   =					logging.get_logger(__name__)

lowerCAmelCase_		:			Optional[int]				   =					{
    '''google/reformer-crime-and-punishment''': (
        '''https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/config.json'''
    ),
    '''google/reformer-enwik8''': '''https://huggingface.co/google/reformer-enwik8/resolve/main/config.json''',
}





class      UpperCamelCase_       (				a_     ):
  _A				:    int =		'reformer'
  _A				:    Any =		['past_buckets_states']
  _A				:    Optional[Any] =		{}



  def __init__(					self       ,						snake_case__=64       ,						snake_case__=["local", "lsh", "local", "lsh", "local", "lsh"]       ,						snake_case__=1.0       ,						snake_case__=True       ,						snake_case__=[64, 64]       ,						snake_case__=[64, 1_92]       ,						snake_case__=0       ,						snake_case__=2       ,						snake_case__=5_12       ,						snake_case__=None       ,						snake_case__="relu"       ,						snake_case__=0.05       ,						snake_case__=2_56       ,						snake_case__=0.02       ,						snake_case__=False       ,						snake_case__=1e-12       ,						snake_case__=1       ,						snake_case__=0       ,						snake_case__=0.05       ,						snake_case__=64       ,						snake_case__=64       ,						snake_case__=0.0       ,						snake_case__=1       ,						snake_case__=0       ,						snake_case__=40_96       ,						snake_case__=12       ,						snake_case__=None       ,						snake_case__=1       ,						snake_case__=0       ,						snake_case__=3_20       ,						snake_case__=False       ,						snake_case__=True       ,						snake_case__=None       ,						**snake_case__       ,						)	->	List[Any]:



         """simple docstring"""





         UpperCAmelCase					=	hash_seed
         UpperCAmelCase					=	vocab_size
         UpperCAmelCase					=	attention_head_size
         UpperCAmelCase					=	hidden_size
         UpperCAmelCase					=	num_attention_heads
         UpperCAmelCase					=	num_hashes
         UpperCAmelCase					=	len(snake_case__ )
         UpperCAmelCase					=	tuple(snake_case__ ) if isinstance(snake_case__       ,						snake_case__ ) else num_buckets
         UpperCAmelCase					=	lsh_attn_chunk_length
         UpperCAmelCase					=	local_attn_chunk_length
         UpperCAmelCase					=	lsh_num_chunks_after
         UpperCAmelCase					=	lsh_num_chunks_before
         UpperCAmelCase					=	local_num_chunks_after
         UpperCAmelCase					=	local_num_chunks_before
         UpperCAmelCase					=	hidden_act
         UpperCAmelCase					=	feed_forward_size
         UpperCAmelCase					=	hidden_dropout_prob
         UpperCAmelCase					=	lsh_attention_probs_dropout_prob
         UpperCAmelCase					=	local_attention_probs_dropout_prob
         UpperCAmelCase					=	max_position_embeddings
         UpperCAmelCase					=	initializer_range
         UpperCAmelCase					=	layer_norm_eps
         UpperCAmelCase					=	axial_pos_embds
         UpperCAmelCase					=	tuple(snake_case__ )
         UpperCAmelCase					=	tuple(snake_case__ )
         UpperCAmelCase					=	axial_norm_std
         UpperCAmelCase					=	chunk_size_lm_head
         UpperCAmelCase					=	attn_layers
         UpperCAmelCase					=	use_cache
         UpperCAmelCase					=	classifier_dropout
         super().__init__(
             pad_token_id=snake_case__       ,						eos_token_id=snake_case__       ,						is_decoder=snake_case__       ,						tie_word_embeddings=snake_case__       ,						**snake_case__       ,						)
