

'''simple docstring'''

import os
import warnings
from pathlib import Path
from typing import Optional, Union

from .dynamic_module_utils import custom_object_save
from .tokenization_utils_base import PreTrainedTokenizerBase
from .utils import PushToHubMixin, copy_func, direct_transformers_import, logging


UpperCAmelCase				   =  logging.get_logger(__name__)

# Dynamically import the Transformers module to grab the attribute classes of the processor form their names.
UpperCAmelCase				   =  direct_transformers_import(Path(__file__).parent)


UpperCAmelCase				   =  {
    '''AutoTokenizer''': '''PreTrainedTokenizerBase''',
    '''AutoFeatureExtractor''': '''FeatureExtractionMixin''',
    '''AutoImageProcessor''': '''ImageProcessingMixin''',
}


class   lowerCAmelCase     (      A   ):
       lowerCAmelCase_		= ["feature_extractor", "tokenizer"]
       # Names need to be attr_class for attr in attributes
       lowerCAmelCase_		= None
       lowerCAmelCase_		= None
       lowerCAmelCase_		= None







       def __init__(							self			: List[str]						,      *__lowercase			: List[str]						,      **__lowercase			: Dict      ):







            """simple docstring"""







            for key in kwargs:
                 if key not in self.attributes:
                      raise TypeError(f'''Unexpected keyword argument {key}.'''      )
            for arg, attribute_name in zip(__lowercase						,      self.attributes      ):
                 if attribute_name in kwargs:
                      raise TypeError(f'''Got multiple values for argument {attribute_name}.'''      )
                 else:
                      __lowercase					=arg

            if len(__lowercase      ) != len(self.attributes      ):
                 raise ValueError(
                     f'''This processor requires {len(self.attributes      )} arguments: {", ".join(self.attributes      )}. Got '''
                     f'''{len(__lowercase      )} arguments instead.'''      )

            # Check each arg is of the proper class (this will also catch a user initializing in the wrong order)
            for attribute_name, arg in kwargs.items():
                 __lowercase					=getattr(self						,      f'''{attribute_name}_class'''      )
                 # Nothing is ever going to be an instance of "AutoXxx", in that case we check the base class.
                 __lowercase					=AUTO_TO_BASE_CLASS_MAPPING.get(__lowercase						,      __lowercase      )
                 if isinstance(__lowercase						,      __lowercase      ):
                      __lowercase					=tuple(getattr(__lowercase						,      __lowercase      ) for n in class_name if n is not None      )
                 else:
                      __lowercase					=getattr(__lowercase						,      __lowercase      )

                 if not isinstance(__lowercase						,      __lowercase      ):
                      raise ValueError(
                          f'''Received a {type(__lowercase      ).__name__} for argument {attribute_name}, but a {class_name} was expected.'''      )

                 setattr(self						,      __lowercase						,      __lowercase      )







       def __repr__(							self			: Optional[Any]      ):







            """simple docstring"""







            __lowercase					=[f'''- {name}: {repr(getattr(self						,      __lowercase      )      )}''' for name in self.attributes]
            __lowercase					='\n'.join(__lowercase      )
            return f'''{self.__class__.__name__}:\n{attributes_repr}'''







       def 			snake_case   (							self			: Dict						,      __lowercase			: Union[str, Any]						,      __lowercase			: bool = False						,      **__lowercase			: str      ):







            """simple docstring"""







            os.makedirs(__lowercase						,      exist_ok=__lowercase      )

            if push_to_hub:
                 __lowercase					=kwargs.pop('commit_message'						,      __lowercase      )
                 __lowercase					=kwargs.pop('repo_id'						,      save_directory.split(os.path.sep      )[-1]      )
                 __lowercase					=self._create_repo(__lowercase						,      **__lowercase      )
                 __lowercase					=self._get_files_timestamps(__lowercase      )
            # If we have a custom config, we copy the file defining it in the folder and set the attributes so it can be
            # loaded from the Hub.
            if self._auto_class is not None:
                 __lowercase					=[getattr(self						,      __lowercase      ) for attribute_name in self.attributes]
                 __lowercase					=[(a.init_kwargs if isinstance(__lowercase						,      __lowercase      ) else a) for a in attrs]
                 custom_object_save(self						,      __lowercase						,      config=__lowercase      )

            for attribute_name in self.attributes:
                 __lowercase					=getattr(self						,      __lowercase      )
                 # Include the processor class in the attribute config so this processor can then be reloaded with the
                 # `AutoProcessor` API.
                 if hasattr(__lowercase						,      '_set_processor_class'      ):
                      attribute._set_processor_class(self.__class__.__name__      )
                 attribute.save_pretrained(__lowercase      )

            if self._auto_class is not None:
                 # We added an attribute to the init_kwargs of the tokenizers, which needs to be cleaned up.
                 for attribute_name in self.attributes:
                      __lowercase					=getattr(self						,      __lowercase      )
                      if isinstance(__lowercase						,      __lowercase      ):
                           del attribute.init_kwargs["auto_map"]

            if push_to_hub:
                 self._upload_modified_files(
                     __lowercase						,      __lowercase						,      __lowercase						,      commit_message=__lowercase						,      token=kwargs.get('use_auth_token'      )						,      )







       @classmethod
       def 			snake_case   (							cls			: Optional[int]						,      __lowercase			: Union[str, os.PathLike]						,      __lowercase			: Optional[Union[str, os.PathLike]] = None						,      __lowercase			: bool = False						,      __lowercase			: bool = False						,      __lowercase			: Optional[Union[str, bool]] = None						,      __lowercase			: str = "main"						,      **__lowercase			: Union[str, Any]						,      ):







            """simple docstring"""







            __lowercase					=cache_dir
            __lowercase					=force_download
            __lowercase					=local_files_only
            __lowercase					=revision

            __lowercase					=kwargs.pop('use_auth_token'						,      __lowercase      )
            if use_auth_token is not None:
                 warnings.warn(
                     'The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers.'						,      __lowercase      )
                 if token is not None:
                      raise ValueError(
                          '`token` and `use_auth_token` are both specified. Please set only the argument `token`.'      )
                 __lowercase					=use_auth_token

            if token is not None:
                 # change to `token` in a follow-up PR
                 __lowercase					=token

            __lowercase					=cls._get_arguments_from_pretrained(__lowercase						,      **__lowercase      )
            return cls(*__lowercase      )







       @classmethod
       def 			snake_case   (							cls			: Any						,      __lowercase			: Tuple="AutoProcessor"      ):







            """simple docstring"""







            if not isinstance(__lowercase						,      __lowercase      ):
                 __lowercase					=auto_class.__name__

            import transformers.models.auto as auto_module

            if not hasattr(__lowercase						,      __lowercase      ):
                 raise ValueError(f'''{auto_class} is not a valid auto class.'''      )

            __lowercase					=auto_class







       @classmethod
       def 			snake_case   (							cls			: Tuple						,      __lowercase			: List[Any]						,      **__lowercase			: Tuple      ):







            """simple docstring"""







            __lowercase					=[]
            for attribute_name in cls.attributes:
                 __lowercase					=getattr(cls						,      f'''{attribute_name}_class'''      )
                 if isinstance(__lowercase						,      __lowercase      ):
                      __lowercase					=tuple(getattr(__lowercase						,      __lowercase      ) if n is not None else None for n in class_name      )
                      __lowercase					=kwargs.get('use_fast'						,      __lowercase      )
                      if use_fast and classes[1] is not None:
                           __lowercase					=classes[1]
                      else:
                           __lowercase					=classes[0]
                 else:
                      __lowercase					=getattr(__lowercase						,      __lowercase      )

                 args.append(attribute_class.from_pretrained(__lowercase						,      **__lowercase      )      )
            return args







       @property
       def 			snake_case   (							self			: str      ):







            """simple docstring"""







            __lowercase					=getattr(self						,      self.attributes[0]      )
            return getattr(__lowercase						,      'model_input_names'						,      __lowercase      )






UpperCAmelCase				   =  copy_func(ProcessorMixin.push_to_hub)
if ProcessorMixin.push_to_hub.__doc__ is not None:
       UpperCAmelCase				   =  ProcessorMixin.push_to_hub.__doc__.format(
           object='''processor''', object_class='''AutoProcessor''', object_files='''processor files'''
       )





'''simple docstring'''

from __future__ import annotations

from pathlib import Path

def 				__UpperCamelCase							(	lowercase__						:  tuple[int, int],					lowercase__						:  tuple[int, int] ):






     '''simple docstring'''





     return pointa[0] * pointa[1] - pointa[1] * pointa[0]

def 				__UpperCamelCase							(	lowercase__						:  int,					lowercase__						:  int,					lowercase__						:  int,					lowercase__						:  int,					lowercase__						:  int,					lowercase__						:  int ):






     '''simple docstring'''





     __lowercase					=(xa, ya)
     __lowercase					=(xa - xa, ya - ya)
     __lowercase					=(xa - xa, ya - ya)
     __lowercase					=-vector_product(lowercase__,					lowercase__ ) / vector_product(
         lowercase__,					lowercase__ )
     __lowercase					=+vector_product(lowercase__,					lowercase__ ) / vector_product(
         lowercase__,					lowercase__ )

     return a > 0 and b > 0 and a + b < 1

def 				__UpperCamelCase							(	lowercase__						:  str = "p102_triangles.txt" ):






     '''simple docstring'''





     __lowercase					=Path(lowercase__ ).parent.joinpath(lowercase__ ).read_text(encoding='utf-8' )

     __lowercase					=[]
     for line in data.strip().split('\n' ):
          triangles.append([int(lowercase__ ) for number in line.split(',' )] )

     __lowercase					=0
     __lowercase					=42

     for triangle in triangles:
          ret += contains_origin(*lowercase__ )

     return ret


if __name__ == "__main__":
       print(F'''{solution() = }''')


