code: import hashlib
  import importlib.util
  import json
  import os
  import pathlib
  from types import ModuleType
  
  import pytest
  import requests
  
  A_:      Tuple        =			pathlib.Path.cwd().joinpath('project_euler')
  A_:      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 					__lowerCAmelCase			(  _A					):
  
  
  
  							"""simple docstring"""
  
  
  							_lowercase				=	importlib.util.spec_from_file_location(file_path.name ,str(_A					)					)
  							_lowercase				=	importlib.util.module_from_spec(_A					)  # type: ignore
  							spec.loader.exec_module(_A					)  # type: ignore
  							return module
  
  
  def 					__lowerCAmelCase			(  ):
  
  
  
  							"""simple docstring"""
  
  
  							_lowercase				=	[]
  							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(_A					)
  							return solution_file_paths
  
  
  def 					__lowerCAmelCase			(  ):
  
  
  
  							"""simple docstring"""
  
  
  							with open(os.environ["""GITHUB_EVENT_PATH"""]					) as file:
  														_lowercase				=	json.load(_A					)
  							return event["pull_request"]["url"] + "/files"
  
  
  def 					__lowerCAmelCase			(  ):
  
  
  
  							"""simple docstring"""
  
  
  							_lowercase				=	[]
  							_lowercase				=	{
  							    """Accept""": """application/vnd.github.v3+json""",
  							    """Authorization""": """token """ + os.environ["""GITHUB_TOKEN"""],
  							}
  							_lowercase				=	requests.get(get_files_url() ,headers=_A					).json()
  							for file in files:
  														_lowercase				=	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(_A					)
  							return solution_file_paths
  
  
  def 					__lowerCAmelCase			(  ):
  
  
  
  							"""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 _A					: f'''{path.parent.name}/{path.name}''' ,)
  def 					__lowerCAmelCase			(  _A					):
  
  
  
  							"""simple docstring"""
  
  
  							_lowercase				=	solution_path.parent.name[8:].zfill(3					)
  							_lowercase				=	PROBLEM_ANSWERS[problem_number]
  							_lowercase				=	convert_path_to_module(_A					)
  							_lowercase				=	str(solution_module.solution()					)  # type: ignore
  							_lowercase				=	hashlib.shaaaa(answer.encode()					).hexdigest()
  							assert (
  							    answer == expected
  							), f'''Expected solution to {problem_number} to have hash {expected}, got {answer}'''
  
  
  
style_context: import shutil
  import tempfile
  import unittest
  
  import numpy as np
  import pytest
  
  from transformers.testing_utils import require_vision
  from transformers.utils import is_vision_available
  
  
  if is_vision_available():
  				from PIL import Image
  
  				from transformers import AutoProcessor, BertTokenizer, CLIPImageProcessor, GitProcessor, PreTrainedTokenizerFast
  
  
  @require_vision
  class _lowercase					(       unittest.TestCase						):
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  							def     _UpperCAmelCase       (    self  ):
  
  
  
  
  
  
  
  														'''simple docstring'''
  
  
  
  
  
  
  														_lowercase				=	tempfile.mkdtemp()
  
  														_lowercase				=	CLIPImageProcessor()
  														_lowercase				=	BertTokenizer.from_pretrained(
  														    """hf-internal-testing/tiny-random-BertModel"""     ,   model_input_names=["""input_ids""", """attention_mask"""]  )
  
  														_lowercase				=	GitProcessor(UpperCAmelCase     ,   UpperCAmelCase  )
  
  														processor.save_pretrained(self.tmpdirname  )
  
  
  
  							def     _UpperCAmelCase       (    self     ,   **UpperCAmelCase  ):
  
  
  
  
  
  
  
  														'''simple docstring'''
  
  
  
  
  
  
  														return AutoProcessor.from_pretrained(self.tmpdirname     ,   **UpperCAmelCase  ).tokenizer
  
  
  
  							def     _UpperCAmelCase       (    self     ,   **UpperCAmelCase  ):
  
  
  
  
  
  
  
  														'''simple docstring'''
  
  
  
  
  
  
  														return AutoProcessor.from_pretrained(self.tmpdirname     ,   **UpperCAmelCase  ).image_processor
  
  
  
  							def     _UpperCAmelCase       (    self  ):
  
  
  
  
  
  
  
  														'''simple docstring'''
  
  
  
  
  
  
  														shutil.rmtree(self.tmpdirname  )
  
  
  
  							def     _UpperCAmelCase       (    self  ):
  
  
  
  
  
  
  
  														'''simple docstring'''
  
  
  
  
  
  
  														_lowercase				=	[np.random.randint(255     ,   size=(3, 30, 400)     ,   dtype=np.uinta  )]
  
  														_lowercase				=	[Image.fromarray(np.moveaxis(UpperCAmelCase     ,   0     ,   -1  )  ) for x in image_inputs]
  
  														return image_inputs
  
  
  
  							def     _UpperCAmelCase       (    self  ):
  
  
  
  
  
  
  
  														'''simple docstring'''
  
  
  
  
  
  
  														_lowercase				=	GitProcessor(tokenizer=self.get_tokenizer()     ,   image_processor=self.get_image_processor()  )
  														processor.save_pretrained(self.tmpdirname  )
  
  														_lowercase				=	self.get_tokenizer(bos_token="""(BOS)"""     ,   eos_token="""(EOS)"""  )
  														_lowercase				=	self.get_image_processor(do_normalize=UpperCAmelCase     ,   padding_value=1.0  )
  
  														_lowercase				=	GitProcessor.from_pretrained(
  														    self.tmpdirname     ,   bos_token="""(BOS)"""     ,   eos_token="""(EOS)"""     ,   do_normalize=UpperCAmelCase     ,   padding_value=1.0  )
  
  														self.assertEqual(processor.tokenizer.get_vocab()     ,   tokenizer_add_kwargs.get_vocab()  )
  														self.assertIsInstance(processor.tokenizer     ,   UpperCAmelCase  )
  
  														self.assertEqual(processor.image_processor.to_json_string()     ,   image_processor_add_kwargs.to_json_string()  )
  														self.assertIsInstance(processor.image_processor     ,   UpperCAmelCase  )
  
  
  
  							def     _UpperCAmelCase       (    self  ):
  
  
  
  
  
  
  
  														'''simple docstring'''
  
  
  
  
  
  
  														_lowercase				=	self.get_image_processor()
  														_lowercase				=	self.get_tokenizer()
  
  														_lowercase				=	GitProcessor(tokenizer=UpperCAmelCase     ,   image_processor=UpperCAmelCase  )
  
  														_lowercase				=	self.prepare_image_inputs()
  
  														_lowercase				=	image_processor(UpperCAmelCase     ,   return_tensors="""np"""  )
  														_lowercase				=	processor(images=UpperCAmelCase     ,   return_tensors="""np"""  )
  
  														for key in input_feat_extract.keys():
  																					self.assertAlmostEqual(input_feat_extract[key].sum()     ,   input_processor[key].sum()     ,   delta=1e-2  )
  
  
  
  							def     _UpperCAmelCase       (    self  ):
  
  
  
  
  
  
  
  														'''simple docstring'''
  
  
  
  
  
  
  														_lowercase				=	self.get_image_processor()
  														_lowercase				=	self.get_tokenizer()
  
  														_lowercase				=	GitProcessor(tokenizer=UpperCAmelCase     ,   image_processor=UpperCAmelCase  )
  
  														_lowercase				=	"""lower newer"""
  
  														_lowercase				=	processor(text=UpperCAmelCase  )
  
  														_lowercase				=	tokenizer(UpperCAmelCase     ,   return_token_type_ids=UpperCAmelCase  )
  
  														for key in encoded_tok.keys():
  																					self.assertListEqual(encoded_tok[key]     ,   encoded_processor[key]  )
  
  
  
  							def     _UpperCAmelCase       (    self  ):
  
  
  
  
  
  
  
  														'''simple docstring'''
  
  
  
  
  
  
  														_lowercase				=	self.get_image_processor()
  														_lowercase				=	self.get_tokenizer()
  
  														_lowercase				=	GitProcessor(tokenizer=UpperCAmelCase     ,   image_processor=UpperCAmelCase  )
  
  														_lowercase				=	"""lower newer"""
  														_lowercase				=	self.prepare_image_inputs()
  
  														_lowercase				=	processor(text=UpperCAmelCase     ,   images=UpperCAmelCase  )
  
  														self.assertListEqual(list(inputs.keys()  )     ,   ["""input_ids""", """attention_mask""", """pixel_values"""]  )
  
  														# test if it raises when no input is passed
  														with pytest.raises(UpperCAmelCase  ):
  																					processor()
  
  
  
  							def     _UpperCAmelCase       (    self  ):
  
  
  
  
  
  
  
  														'''simple docstring'''
  
  
  
  
  
  
  														_lowercase				=	self.get_image_processor()
  														_lowercase				=	self.get_tokenizer()
  
  														_lowercase				=	GitProcessor(tokenizer=UpperCAmelCase     ,   image_processor=UpperCAmelCase  )
  
  														_lowercase				=	[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]
  
  														_lowercase				=	processor.batch_decode(UpperCAmelCase  )
  														_lowercase				=	tokenizer.batch_decode(UpperCAmelCase  )
  
  														self.assertListEqual(UpperCAmelCase     ,   UpperCAmelCase  )
  
  
  
  							def     _UpperCAmelCase       (    self  ):
  
  
  
  
  
  
  
  														'''simple docstring'''
  
  
  
  
  
  
  														_lowercase				=	self.get_image_processor()
  														_lowercase				=	self.get_tokenizer()
  
  														_lowercase				=	GitProcessor(tokenizer=UpperCAmelCase     ,   image_processor=UpperCAmelCase  )
  
  														_lowercase				=	"""lower newer"""
  														_lowercase				=	self.prepare_image_inputs()
  
  														_lowercase				=	processor(text=UpperCAmelCase     ,   images=UpperCAmelCase  )
  
  														# For now the processor supports only ['input_ids', 'attention_mask', 'pixel_values']
  														self.assertListEqual(list(inputs.keys()  )     ,   ["""input_ids""", """attention_mask""", """pixel_values"""]  )
  
  
  