



'''simple docstring'''






import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding



class 				lowercase			(    _lowerCamelCase							):


 """simple docstring"""


 UpperCAmelCase		      =    ["""image_processor""", """tokenizer"""]
 UpperCAmelCase		      =    """VideoMAEImageProcessor"""
 UpperCAmelCase		      =    ("""CLIPTokenizer""", """CLIPTokenizerFast""")







 def __init__(				self    ,a_=None    ,a_=None    ,**a_				)						->  int:
        _UpperCAmelCase    :		int     	=					None
        if "feature_extractor" in kwargs:
               warnings.warn(
                   """The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"""
                   """ instead."""    ,a_    ,)
               _UpperCAmelCase    :		Tuple     	=					kwargs.pop("""feature_extractor"""				)

        _UpperCAmelCase    :		str     	=					image_processor if image_processor is not None else feature_extractor
        if image_processor is None:
               raise ValueError("""You need to specify an `image_processor`."""				)
        if tokenizer is None:
               raise ValueError("""You need to specify a `tokenizer`."""				)

        super().__init__(a_    ,a_				)
        _UpperCAmelCase    :		Tuple     	=					self.image_processor







 def __call__(				self    ,a_=None    ,a_=None    ,a_=None    ,**a_				)						->  str:

        if text is None and videos is None:
               raise ValueError("""You have to specify either text or videos. Both cannot be none."""				)

        if text is not None:
               _UpperCAmelCase    :		Union[str, Any]     	=					self.tokenizer(a_    ,return_tensors=a_    ,**a_				)

        if videos is not None:
               _UpperCAmelCase    :		Optional[Any]     	=					self.image_processor(a_    ,return_tensors=a_    ,**a_				)

        if text is not None and videos is not None:
               _UpperCAmelCase    :		Union[str, Any]     	=					image_features.pixel_values
               return encoding
        elif text is not None:
               return encoding
        else:
               return BatchEncoding(data=dict(**a_				)    ,tensor_type=a_				)







 def _snake_case					(				self    ,*a_    ,**a_				)						->  Optional[int]:
        return self.tokenizer.batch_decode(*a_    ,**a_				)







 def _snake_case					(				self    ,*a_    ,**a_				)						->  Optional[Any]:
        return self.tokenizer.decode(*a_    ,**a_				)







 @property
 def _snake_case					(				self				)						->  Tuple:
        return ["input_ids", "attention_mask", "position_ids", "pixel_values"]







 @property
 def _snake_case					(				self				)						->  Tuple:
        warnings.warn(
            """`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."""    ,a_    ,)
        return self.image_processor_class







 @property
 def _snake_case					(				self				)						->  Dict:
        warnings.warn(
            """`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead."""    ,a_    ,)
        return self.image_processor











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   snake_case		(				UpperCAmelCase						:							pathlib.Path ):
				A									=   importlib.util.spec_from_file_location(file_path.name,    str(UpperCAmelCase ) )
				A									=   importlib.util.module_from_spec(UpperCAmelCase )  # type: ignore
				spec.loader.exec_module(UpperCAmelCase )  # type: ignore
				return module







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







def   snake_case		(				):
				A									=   []
				A									=   {
				    'Accept': 'application/vnd.github.v3+json',
				    'Authorization': 'token ' + os.environ['GITHUB_TOKEN'],
				}
				A									=   requests.get(get_files_url(),    headers=UpperCAmelCase ).json()
				for file in files:
								A									=   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   snake_case		(				):
				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   snake_case		(				UpperCAmelCase						:							pathlib.Path ):
				A									=   solution_path.parent.name[8:].zfill(3 )
				A									=   PROBLEM_ANSWERS[problem_number]
				A									=   convert_path_to_module(UpperCAmelCase )
				A									=   str(solution_module.solution() )  # type: ignore
				A									=   hashlib.shaaaa(answer.encode() ).hexdigest()
				assert (
				    answer == expected
				), f'Expected solution to {problem_number} to have hash {expected}, got {answer}'





