




'''simple docstring'''




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

import pytest
import requests

snake_case__          =						pathlib.Path.cwd().joinpath("""project_euler""")
snake_case__          =						pathlib.Path.cwd().joinpath(
    """scripts""", """project_euler_answers.json"""
)

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




def 						snake_case__    ( lowerCamelCase__				:   pathlib.Path			)   ->   ModuleType:
					A_ :     Union[str, Any] =							importlib.util.spec_from_file_location(file_path.name			,		str(lowerCamelCase__			)			)
					A_ :     Dict =							importlib.util.module_from_spec(lowerCamelCase__			)  # type: ignore
					spec.loader.exec_module(lowerCamelCase__			)  # type: ignore
					return module




def 						snake_case__    ( )   ->   list[pathlib.Path]:
					A_ :     Optional[Any] =							[]
					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(lowerCamelCase__			)
					return solution_file_paths




def 						snake_case__    ( )   ->   str:
					with open(os.environ['''GITHUB_EVENT_PATH''']			) as file:
										A_ :     Dict =							json.load(lowerCamelCase__			)
					return event["pull_request"]["url"] + "/files"




def 						snake_case__    ( )   ->   list[pathlib.Path]:
					A_ :     int =							[]
					A_ :     int =							{
					    '''Accept''': '''application/vnd.github.v3+json''',
					    '''Authorization''': '''token ''' + os.environ['''GITHUB_TOKEN'''],
					}
					A_ :     Tuple =							requests.get(get_files_url()			,		headers=lowerCamelCase__			).json()
					for file in files:
										A_ :     str =							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(lowerCamelCase__			)
					return solution_file_paths




def 						snake_case__    ( )   ->   list[pathlib.Path]:
					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 lowerCamelCase__			: f'{path.parent.name}/{path.name}'			,		)
def 						snake_case__    ( lowerCamelCase__				:   pathlib.Path			)   ->   None:
					A_ :     str =							solution_path.parent.name[8:].zfill(3			)
					A_ :     str =							PROBLEM_ANSWERS[problem_number]
					A_ :     Tuple =							convert_path_to_module(lowerCamelCase__			)
					A_ :     Any =							str(solution_module.solution()			)  # type: ignore
					A_ :     Dict =							hashlib.shaaaa(answer.encode()			).hexdigest()
					assert (
					    answer == expected
					), f'Expected solution to {problem_number} to have hash {expected}, got {answer}'









'''simple docstring'''




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


snake_case__          =						logging.get_logger(__name__)

snake_case__          =						{
    """bert-base-uncased""": """https://huggingface.co/bert-base-uncased/resolve/main/config.json""",
    # QDQBERT models can be loaded from any BERT checkpoint, available at https://huggingface.co/models?filter=bert
}






class     UpperCamelCase_     (a__     ):







						"""simple docstring"""


						_lowerCAmelCase    						=					'qdqbert'







						def __init__(     self      :       Union[str, Any]							, _lowerCamelCase      :       List[Any]=30522							, _lowerCamelCase      :       str=768							, _lowerCamelCase      :       Optional[Any]=12							, _lowerCamelCase      :       str=12							, _lowerCamelCase      :       List[Any]=3072							, _lowerCamelCase      :       Union[str, Any]="gelu"							, _lowerCamelCase      :       Dict=0.1							, _lowerCamelCase      :       Union[str, Any]=0.1							, _lowerCamelCase      :       Optional[int]=512							, _lowerCamelCase      :       Dict=2							, _lowerCamelCase      :       Optional[Any]=0.02							, _lowerCamelCase      :       List[Any]=1E-12							, _lowerCamelCase      :       Tuple=True							, _lowerCamelCase      :       Tuple=1							, _lowerCamelCase      :       Optional[Any]=0							, _lowerCamelCase      :       Optional[int]=2							, **_lowerCamelCase      :       List[str]							, ):





											"""simple docstring"""







											super().__init__(pad_token_id=_lowerCamelCase							, bos_token_id=_lowerCamelCase							, eos_token_id=_lowerCamelCase							, **_lowerCamelCase    )

											A_ :     Optional[Any] =							vocab_size
											A_ :     str =							max_position_embeddings
											A_ :     List[str] =							hidden_size
											A_ :     str =							num_hidden_layers
											A_ :     List[str] =							num_attention_heads
											A_ :     List[str] =							intermediate_size
											A_ :     int =							hidden_act
											A_ :     Tuple =							hidden_dropout_prob
											A_ :     Optional[Any] =							attention_probs_dropout_prob
											A_ :     Dict =							initializer_range
											A_ :     Optional[int] =							type_vocab_size
											A_ :     Any =							layer_norm_eps
											A_ :     Optional[int] =							use_cache



