
import hashlib
import importlib.util
import json
import os
import pathlib
from types import ModuleType

import pytest
import requests

lowercase__				:				List[Any]						=      pathlib.Path.cwd().joinpath("project_euler")
lowercase__				:				List[str]						=      pathlib.Path.cwd().joinpath(
    "scripts", "project_euler_answers.json"
)

with open(PROJECT_EULER_ANSWERS_PATH) as file_handle:
				lowercase__				:				dict[str, str]						=      json.load(file_handle)




def 						A_			(				snake_case				: pathlib.Path			)   ->     ModuleType:



						'''simple docstring'''

						__UpperCamelCase  	=      importlib.util.spec_from_file_location(file_path.name			,   str(snake_case			)			)
						__UpperCamelCase  	=      importlib.util.module_from_spec(snake_case			)  # type: ignore
						spec.loader.exec_module(snake_case			)  # type: ignore
						return module




def 						A_			(				)   ->     list[pathlib.Path]:



						'''simple docstring'''

						__UpperCamelCase  	=      []
						for problem_dir_path in PROJECT_EULER_DIR_PATH.iterdir():
												if problem_dir_path.is_file() or problem_dir_path.name.startswith('''_'''			):
																		continue
												for file_path in problem_dir_path.iterdir():
																		if file_path.suffix != ".py" or file_path.name.startswith(('''_''', '''test''')			):
																								continue
																		solution_file_paths.append(snake_case			)
						return solution_file_paths




def 						A_			(				)   ->     str:



						'''simple docstring'''

						with open(os.environ['''GITHUB_EVENT_PATH''']			) as file:
												__UpperCamelCase  	=      json.load(snake_case			)
						return event["pull_request"]["url"] + "/files"




def 						A_			(				)   ->     list[pathlib.Path]:



						'''simple docstring'''

						__UpperCamelCase  	=      []
						__UpperCamelCase  	=      {
						    '''Accept''': '''application/vnd.github.v3+json''',
						    '''Authorization''': '''token ''' + os.environ['''GITHUB_TOKEN'''],
						}
						__UpperCamelCase  	=      requests.get(get_files_url()			,   headers=snake_case			).json()
						for file in files:
												__UpperCamelCase  	=      pathlib.Path.cwd().joinpath(file['''filename''']			)
												if (
												    filepath.suffix != ".py"
												    or filepath.name.startswith(('''_''', '''test''')			)
												    or not filepath.name.startswith('''sol'''			)
												):
																		continue
												solution_file_paths.append(snake_case			)
						return solution_file_paths




def 						A_			(				)   ->     list[pathlib.Path]:



						'''simple docstring'''

						if os.environ.get('''CI'''			) and os.environ.get('''GITHUB_EVENT_NAME'''			) == "pull_request":
												# Return only if there are any, otherwise default to all solutions
												if filepaths := added_solution_file_path():
																		return filepaths
						return all_solution_file_paths()




@pytest.mark.parametrize(
    '''solution_path'''			,   collect_solution_file_paths()			,   ids=lambda snake_case			: f"{path.parent.name}/{path.name}"			,   )
def 						A_			(				snake_case				: pathlib.Path			)   ->     None:



						'''simple docstring'''

						__UpperCamelCase  	=      solution_path.parent.name[8:].zfill(3			)
						__UpperCamelCase  	=      PROBLEM_ANSWERS[problem_number]
						__UpperCamelCase  	=      convert_path_to_module(snake_case			)
						__UpperCamelCase  	=      str(solution_module.solution()			)  # type: ignore
						__UpperCamelCase  	=      hashlib.shaaaa(answer.encode()			).hexdigest()
						assert (
						    answer == expected
						), f"Expected solution to {problem_number} to have hash {expected}, got {answer}"










"""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


