





"""simple docstring"""


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

import pytest
import requests

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

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





def 							a__     (					_UpperCAmelCase		)      ->					ModuleType:

 '''simple docstring'''






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





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

 '''simple docstring'''






 snake_case__      							=			[]
 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 							a__     (					)      ->					str:

 '''simple docstring'''






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





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

 '''simple docstring'''






 snake_case__      							=			[]
 snake_case__      							=			{
     "Accept": "application/vnd.github.v3+json",
     "Authorization": "token " + os.environ["GITHUB_TOKEN"],
 }
 snake_case__      							=			requests.get(get_files_url()		,       headers=_UpperCAmelCase		).json()
 for file in files:
  snake_case__      							=			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 							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 _UpperCAmelCase		: f"{path.parent.name}/{path.name}"		,       )
def 							a__     (					_UpperCAmelCase		)      ->					None:

 '''simple docstring'''






 snake_case__      							=			solution_path.parent.name[8:].zfill(3		)
 snake_case__      							=			PROBLEM_ANSWERS[problem_number]
 snake_case__      							=			convert_path_to_module(_UpperCAmelCase		)
 snake_case__      							=			str(solution_module.solution()		)  # type: ignore
 snake_case__      							=			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


a__   :       Optional[Any]   						=			logging.get_logger(__name__)

a__   :       List[str]   						=			{}



class        lowercase_			(       __lowerCAmelCase							):
       snake_case__			:							List[str]										=       """fsmt_decoder"""

       def __init__(     self				,   __SCREAMING_SNAKE_CASE=0				,   __SCREAMING_SNAKE_CASE=0       ):






        '''simple docstring'''

        super().__init__()
        snake_case__      							=			vocab_size
        snake_case__      							=			bos_token_id



class        lowercase_			(       __lowerCAmelCase							):
       snake_case__			:							str										=       """fsmt"""
       snake_case__			:							List[Any]										=       {"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}

       def __init__(     self				,   __SCREAMING_SNAKE_CASE=["en", "de"]				,   __SCREAMING_SNAKE_CASE=4_2024				,   __SCREAMING_SNAKE_CASE=4_2024				,   __SCREAMING_SNAKE_CASE="relu"				,   __SCREAMING_SNAKE_CASE=1024				,   __SCREAMING_SNAKE_CASE=200				,   __SCREAMING_SNAKE_CASE=1024				,   __SCREAMING_SNAKE_CASE=4096				,   __SCREAMING_SNAKE_CASE=12				,   __SCREAMING_SNAKE_CASE=16				,   __SCREAMING_SNAKE_CASE=0.0				,   __SCREAMING_SNAKE_CASE=4096				,   __SCREAMING_SNAKE_CASE=12				,   __SCREAMING_SNAKE_CASE=16				,   __SCREAMING_SNAKE_CASE=0.0				,   __SCREAMING_SNAKE_CASE=0.0				,   __SCREAMING_SNAKE_CASE=0.1				,   __SCREAMING_SNAKE_CASE=0.0				,   __SCREAMING_SNAKE_CASE=0.02				,   __SCREAMING_SNAKE_CASE=2				,   __SCREAMING_SNAKE_CASE=True				,   __SCREAMING_SNAKE_CASE=True				,   __SCREAMING_SNAKE_CASE=False				,   __SCREAMING_SNAKE_CASE=5				,   __SCREAMING_SNAKE_CASE=1.0				,   __SCREAMING_SNAKE_CASE=False				,   __SCREAMING_SNAKE_CASE=True				,   __SCREAMING_SNAKE_CASE=1				,   __SCREAMING_SNAKE_CASE=0				,   __SCREAMING_SNAKE_CASE=2				,   __SCREAMING_SNAKE_CASE=2				,   **__SCREAMING_SNAKE_CASE				,   ):






        '''simple docstring'''

        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=__SCREAMING_SNAKE_CASE				,   bos_token_id=__SCREAMING_SNAKE_CASE       )
        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=__SCREAMING_SNAKE_CASE				,   bos_token_id=__SCREAMING_SNAKE_CASE				,   eos_token_id=__SCREAMING_SNAKE_CASE				,   decoder_start_token_id=__SCREAMING_SNAKE_CASE				,   is_encoder_decoder=__SCREAMING_SNAKE_CASE				,   tie_word_embeddings=__SCREAMING_SNAKE_CASE				,   forced_eos_token_id=__SCREAMING_SNAKE_CASE				,   max_length=__SCREAMING_SNAKE_CASE				,   num_beams=__SCREAMING_SNAKE_CASE				,   length_penalty=__SCREAMING_SNAKE_CASE				,   early_stopping=__SCREAMING_SNAKE_CASE				,   **__SCREAMING_SNAKE_CASE				,   )

       def 						_SCREAMING_SNAKE_CASE(     self       ):






        '''simple docstring'''

        snake_case__      							=			copy.deepcopy(self.__dict__       )
        snake_case__      							=			self.decoder.to_dict()
        snake_case__      							=			self.__class__.model_type
        return output

