
'''simple docstring'''





import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig


UpperCAmelCase            = logging.get_logger(__name__)

UpperCAmelCase            = {
    "facebook/musicgen-small": "https://huggingface.co/facebook/musicgen-small/resolve/main/config.json",
    # See all Musicgen models at https://huggingface.co/models?filter=musicgen
}

class     a (					__magic_name__     ):
				_snake_case		     =			'''musicgen_decoder'''
				_snake_case		     =			['''past_key_values''']




				def __init__(				self						:					Optional[int],     SCREAMING_SNAKE_CASE_						:					Dict=20_48,     SCREAMING_SNAKE_CASE_						:					List[str]=20_48,     SCREAMING_SNAKE_CASE_						:					int=24,     SCREAMING_SNAKE_CASE_						:					Dict=40_96,     SCREAMING_SNAKE_CASE_						:					str=16,     SCREAMING_SNAKE_CASE_						:					int=0.0,     SCREAMING_SNAKE_CASE_						:					Optional[Any]=True,     SCREAMING_SNAKE_CASE_						:					str="gelu",     SCREAMING_SNAKE_CASE_						:					List[Any]=10_24,     SCREAMING_SNAKE_CASE_						:					int=0.1,     SCREAMING_SNAKE_CASE_						:					List[Any]=0.0,     SCREAMING_SNAKE_CASE_						:					int=0.0,     SCREAMING_SNAKE_CASE_						:					str=0.02,     SCREAMING_SNAKE_CASE_						:					Any=False,     SCREAMING_SNAKE_CASE_						:					List[str]=4,     SCREAMING_SNAKE_CASE_						:					str=20_48,     SCREAMING_SNAKE_CASE_						:					int=20_48,     SCREAMING_SNAKE_CASE_						:					Union[str, Any]=None,     SCREAMING_SNAKE_CASE_						:					Union[str, Any]=False,     **SCREAMING_SNAKE_CASE_						:					Tuple,     ):
										snake_case							:  Optional[int]			=     vocab_size
										snake_case							:  Optional[int]			=     max_position_embeddings
										snake_case							:  Dict			=     hidden_size
										snake_case							:  Any			=     ffn_dim
										snake_case							:  Optional[Any]			=     num_hidden_layers
										snake_case							:  Tuple			=     num_attention_heads
										snake_case							:  int			=     dropout
										snake_case							:  Union[str, Any]			=     attention_dropout
										snake_case							:  Optional[int]			=     activation_dropout
										snake_case							:  Union[str, Any]			=     activation_function
										snake_case							:  Tuple			=     initializer_factor
										snake_case							:  List[Any]			=     layerdrop
										snake_case							:  Optional[int]			=     use_cache
										snake_case							:  Dict			=     scale_embedding  # scale factor will be sqrt(d_model) if True
										snake_case							:  Tuple			=     num_codebooks
										super().__init__(
										    pad_token_id=SCREAMING_SNAKE_CASE_,     bos_token_id=SCREAMING_SNAKE_CASE_,     eos_token_id=SCREAMING_SNAKE_CASE_,     tie_word_embeddings=SCREAMING_SNAKE_CASE_,     **SCREAMING_SNAKE_CASE_,     )




class     a (					__magic_name__     ):
				_snake_case		     =			'''musicgen'''
				_snake_case		     =			True




				def __init__(				self						:					Dict,     **SCREAMING_SNAKE_CASE_						:					Optional[int]   ):
										super().__init__(**SCREAMING_SNAKE_CASE_   )
										if "text_encoder" not in kwargs or "audio_encoder" not in kwargs or "decoder" not in kwargs:
																raise ValueError('''Config has to be initialized with text_encoder, audio_encoder and decoder config'''   )

										snake_case							:  Any			=     kwargs.pop('''text_encoder'''   )
										snake_case							:  List[Any]			=     text_encoder_config.pop('''model_type'''   )

										snake_case							:  Union[str, Any]			=     kwargs.pop('''audio_encoder'''   )
										snake_case							:  Tuple			=     audio_encoder_config.pop('''model_type'''   )

										snake_case							:  List[str]			=     kwargs.pop('''decoder'''   )

										snake_case							:  List[str]			=     AutoConfig.for_model(SCREAMING_SNAKE_CASE_,     **SCREAMING_SNAKE_CASE_   )
										snake_case							:  List[Any]			=     AutoConfig.for_model(SCREAMING_SNAKE_CASE_,     **SCREAMING_SNAKE_CASE_   )
										snake_case							:  Optional[Any]			=     MusicgenDecoderConfig(**SCREAMING_SNAKE_CASE_   )
										snake_case							:  Any			=     True




				@classmethod
				def 						__snake_case				(				cls						:					Tuple,     SCREAMING_SNAKE_CASE_						:					PretrainedConfig,     SCREAMING_SNAKE_CASE_						:					PretrainedConfig,     SCREAMING_SNAKE_CASE_						:					MusicgenDecoderConfig,     **SCREAMING_SNAKE_CASE_						:					Optional[Any],     ):
										return cls(
										    text_encoder=text_encoder_config.to_dict(),     audio_encoder=audio_encoder_config.to_dict(),     decoder=decoder_config.to_dict(),     **SCREAMING_SNAKE_CASE_,     )




				def 						__snake_case				(				self						:					Optional[Any]   ):
										snake_case							:  Dict			=     copy.deepcopy(self.__dict__   )
										snake_case							:  Tuple			=     self.text_encoder.to_dict()
										snake_case							:  str			=     self.audio_encoder.to_dict()
										snake_case							:  Dict			=     self.decoder.to_dict()
										snake_case							:  Optional[int]			=     self.__class__.model_type
										return output


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

import pytest
import requests

__lowerCamelCase     :					Optional[Any]				  =						pathlib.Path.cwd().joinpath('''project_euler''')
__lowerCamelCase     :					Dict				  =						pathlib.Path.cwd().joinpath(
    '''scripts''', '''project_euler_answers.json'''
)

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



def       __SCREAMING_SNAKE_CASE    (   __UpperCamelCase       :			pathlib.Path      )				->   ModuleType:







  """simple docstring"""





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



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







  """simple docstring"""





  SCREAMING_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       __SCREAMING_SNAKE_CASE    (   )				->   str:







  """simple docstring"""





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



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







  """simple docstring"""





  SCREAMING_SNAKE_CASE__     				= []
  SCREAMING_SNAKE_CASE__     				= {
      """Accept""": """application/vnd.github.v3+json""",
      """Authorization""": """token """ + os.environ["""GITHUB_TOKEN"""],
  }
  SCREAMING_SNAKE_CASE__     				= requests.get(get_files_url()					,	headers=__UpperCamelCase      ).json()
  for file in files:
    SCREAMING_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       __SCREAMING_SNAKE_CASE    (   )				->   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       __SCREAMING_SNAKE_CASE    (   __UpperCamelCase       :			pathlib.Path      )				->   None:







  """simple docstring"""





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