


"""simple docstring"""


import unittest
from timeit import timeit






def   a__			(					__lowercase  ,      __lowercase )						->						Union[str, Any]:
				_A       	=      first_num if first_num >= second_num else second_num
				_A       	=      max_num
				while (common_mult % first_num > 0) or (common_mult % second_num > 0):
								common_mult += max_num
				return common_mult






def   a__			(					__lowercase  ,      __lowercase )						->						str:
				return b if a == 0 else greatest_common_divisor(b % a  ,      __lowercase )






def   a__			(					__lowercase  ,      __lowercase )						->						List[str]:
				return first_num // greatest_common_divisor(__lowercase  ,      __lowercase ) * second_num






def   a__			(					)						->						Dict:
				_A       	=      (
				    "from __main__ import least_common_multiple_slow, least_common_multiple_fast"
				)
				print(
				    "least_common_multiple_slow():"  ,      timeit("least_common_multiple_slow(1000, 999)"  ,      setup=__lowercase )  ,      )
				print(
				    "least_common_multiple_fast():"  ,      timeit("least_common_multiple_fast(1000, 999)"  ,      setup=__lowercase )  ,      )
class snake_case   (	unittest.TestCase):
		__UpperCamelCase							     =      (
		    (10, 20),
		    (13, 15),
		    (4, 31),
		    (10, 42),
		    (43, 34),
		    (5, 12),
		    (12, 25),
		    (10, 25),
		    (6, 9),
		)
		__UpperCamelCase							     =      (20, 195, 124, 210, 1462, 60, 300, 50, 18)







		def 			a_			(       self   :							Optional[Any]		)							->    Tuple:





						'''simple docstring'''







						for i, (first_num, second_num) in enumerate(self.test_inputs		):
										_A       	=      least_common_multiple_slow(a__     , a__		)
										_A       	=      least_common_multiple_fast(a__     , a__		)
										with self.subTest(i=a__		):
														self.assertEqual(a__     , self.expected_results[i]		)
														self.assertEqual(a__     , self.expected_results[i]		)


if __name__ == "__main__":
		benchmark()
		unittest.main()





"""simple docstring"""

import copy

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


UpperCamelCase__			:     List[Any]			       =				logging.get_logger(__name__)

UpperCamelCase__			:     List[str]			       =				{}
class      A__   (   lowercase_  ):
	A_				:					Dict      =   """fsmt_decoder"""




	def __init__( self	:						List[Any]   ,     lowercase	:						Any=0   ,     lowercase	:						Dict=0						)       ->			str:
						super().__init__()
						__snake_case        =						vocab_size
						__snake_case        =						bos_token_id

class      A__   (   lowercase_  ):
	A_				:					Union[str, Any]      =   """fsmt"""
	A_				:					int      =   {"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}




	def __init__( self	:						Optional[Any]   ,     lowercase	:						Any=["en", "de"]   ,     lowercase	:						Optional[int]=42_024   ,     lowercase	:						Optional[int]=42_024   ,     lowercase	:						Tuple="relu"   ,     lowercase	:						Tuple=1_024   ,     lowercase	:						Union[str, Any]=200   ,     lowercase	:						List[str]=1_024   ,     lowercase	:						Tuple=4_096   ,     lowercase	:						int=12   ,     lowercase	:						Any=16   ,     lowercase	:						List[Any]=0.0   ,     lowercase	:						str=4_096   ,     lowercase	:						str=12   ,     lowercase	:						Optional[int]=16   ,     lowercase	:						Dict=0.0   ,     lowercase	:						Any=0.0   ,     lowercase	:						Union[str, Any]=0.1   ,     lowercase	:						Tuple=0.0   ,     lowercase	:						List[str]=0.02   ,     lowercase	:						int=2   ,     lowercase	:						Any=True   ,     lowercase	:						int=True   ,     lowercase	:						int=False   ,     lowercase	:						List[str]=5   ,     lowercase	:						List[Any]=1.0   ,     lowercase	:						Union[str, Any]=False   ,     lowercase	:						Optional[Any]=True   ,     lowercase	:						int=1   ,     lowercase	:						Any=0   ,     lowercase	:						Optional[Any]=2   ,     lowercase	:						Any=2   ,     **lowercase	:						List[Any]   ,     )       ->			Union[str, Any]:
						__snake_case        =						langs
						__snake_case        =						src_vocab_size
						__snake_case        =						tgt_vocab_size
						__snake_case        =						d_model  # encoder_embed_dim and decoder_embed_dim

						__snake_case        =						encoder_ffn_dim
						__snake_case        =						__snake_case        =						encoder_layers
						__snake_case        =						encoder_attention_heads
						__snake_case        =						encoder_layerdrop
						__snake_case        =						decoder_layerdrop
						__snake_case        =						decoder_ffn_dim
						__snake_case        =						decoder_layers
						__snake_case        =						decoder_attention_heads
						__snake_case        =						max_position_embeddings
						__snake_case        =						init_std  # Normal(0, this parameter)
						__snake_case        =						activation_function

						__snake_case        =						DecoderConfig(vocab_size=lowercase   ,     bos_token_id=lowercase						)
						if "decoder" in common_kwargs:
											del common_kwargs["decoder"]

						__snake_case        =						scale_embedding  # scale factor will be sqrt(d_model) if True

						# 3 Types of Dropout
						__snake_case        =						attention_dropout
						__snake_case        =						activation_dropout
						__snake_case        =						dropout

						__snake_case        =						use_cache
						super().__init__(
						    pad_token_id=lowercase   ,     bos_token_id=lowercase   ,     eos_token_id=lowercase   ,     decoder_start_token_id=lowercase   ,     is_encoder_decoder=lowercase   ,     tie_word_embeddings=lowercase   ,     forced_eos_token_id=lowercase   ,     max_length=lowercase   ,     num_beams=lowercase   ,     length_penalty=lowercase   ,     early_stopping=lowercase   ,     **lowercase   ,     )




	def 				a_		( self	:						Union[str, Any]						)       ->			Dict:
						__snake_case        =						copy.deepcopy(self.__dict__						)
						__snake_case        =						self.decoder.to_dict()
						__snake_case        =						self.__class__.model_type
						return output


