

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

import pytest
import requests

lowerCamelCase   					=  pathlib.Path.cwd().joinpath('''project_euler''')
lowerCamelCase   					=  pathlib.Path.cwd().joinpath(
    '''scripts''', '''project_euler_answers.json'''
)

with open(PROJECT_EULER_ANSWERS_PATH) as file_handle:
		lowerCamelCase   					=  json.load(file_handle)


def 							__lowercase     (	UpperCAmelCase__   ):

					"""simple docstring"""






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


def 							__lowercase     (	):

					"""simple docstring"""






					__lowerCAmelCase       =				[]
					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(UpperCAmelCase__   )
					return solution_file_paths


def 							__lowercase     (	):

					"""simple docstring"""






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


def 							__lowercase     (	):

					"""simple docstring"""






					__lowerCAmelCase       =				[]
					__lowerCAmelCase       =				{
					    'Accept': 'application/vnd.github.v3+json',
					    'Authorization': 'token ' + os.environ['GITHUB_TOKEN'],
					}
					__lowerCAmelCase       =				requests.get(get_files_url()		,       headers=UpperCAmelCase__   ).json()
					for file in files:
										__lowerCAmelCase       =				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(UpperCAmelCase__   )
					return solution_file_paths


def 							__lowercase     (	):

					"""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 UpperCAmelCase__   : F"""{path.parent.name}/{path.name}"""		,       )
def 							__lowercase     (	UpperCAmelCase__   ):

					"""simple docstring"""






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









import copy

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


lowerCamelCase   					=  logging.get_logger(__name__)

lowerCamelCase   					=  {}





class      snake_case_      (					_a				):


							"""simple docstring"""





							__UpperCAmelCase      ="""fsmt_decoder"""




							def __init__(			self       ,    _A=0       ,    _A=0				):
												super().__init__()
												__lowerCAmelCase       =				vocab_size
												__lowerCAmelCase       =				bos_token_id





class      snake_case_      (					_a				):


							"""simple docstring"""





							__UpperCAmelCase      ="""fsmt"""
							__UpperCAmelCase      ={"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}




							def __init__(			self       ,    _A=["en", "de"]       ,    _A=4_2_0_2_4       ,    _A=4_2_0_2_4       ,    _A="relu"       ,    _A=1_0_2_4       ,    _A=2_0_0       ,    _A=1_0_2_4       ,    _A=4_0_9_6       ,    _A=1_2       ,    _A=1_6       ,    _A=0.0       ,    _A=4_0_9_6       ,    _A=1_2       ,    _A=1_6       ,    _A=0.0       ,    _A=0.0       ,    _A=0.1       ,    _A=0.0       ,    _A=0.02       ,    _A=2       ,    _A=True       ,    _A=True       ,    _A=False       ,    _A=5       ,    _A=1.0       ,    _A=False       ,    _A=True       ,    _A=1       ,    _A=0       ,    _A=2       ,    _A=2       ,    **_A       ,    ):
												__lowerCAmelCase       =				langs
												__lowerCAmelCase       =				src_vocab_size
												__lowerCAmelCase       =				tgt_vocab_size
												__lowerCAmelCase       =				d_model  # encoder_embed_dim and decoder_embed_dim

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

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

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

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

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




							def 							A__	(			self				):
												__lowerCAmelCase       =				copy.deepcopy(self.__dict__				)
												__lowerCAmelCase       =				self.decoder.to_dict()
												__lowerCAmelCase       =				self.__class__.model_type
												return output






