






"""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


_SCREAMING_SNAKE_CASE :    Tuple    =						logging.get_logger(__name__)

# Dynamically import the Transformers module to grab the attribute classes of the processor form their names.
_SCREAMING_SNAKE_CASE :    List[str]    =						direct_transformers_import(Path(__file__).parent)


_SCREAMING_SNAKE_CASE :    Union[str, Any]    =						{
    '''AutoTokenizer''': '''PreTrainedTokenizerBase''',
    '''AutoFeatureExtractor''': '''FeatureExtractionMixin''',
    '''AutoImageProcessor''': '''ImageProcessingMixin''',
}






class 					a						( __snake_case		):
    SCREAMING_SNAKE_CASE						:					int						=			["""feature_extractor""", """tokenizer"""]
    # Names need to be attr_class for attr in attributes
    SCREAMING_SNAKE_CASE						:					Optional[int]						=			None
    SCREAMING_SNAKE_CASE						:					Tuple						=			None
    SCREAMING_SNAKE_CASE						:					Optional[Any]						=			None






    def __init__(	self					:							int	,						*__SCREAMING_SNAKE_CASE					:							Optional[int]	,						**__SCREAMING_SNAKE_CASE					:							str )					->		Dict:
      # Sanitize args and kwargs
      for key in kwargs:
        if key not in self.attributes:
          raise TypeError(F'''Unexpected keyword argument {key}.''' )
      for arg, attribute_name in zip(__SCREAMING_SNAKE_CASE	,						self.attributes ):
        if attribute_name in kwargs:
          raise TypeError(F'''Got multiple values for argument {attribute_name}.''' )
        else:
          lowerCamelCase_   					=						arg

      if len(__SCREAMING_SNAKE_CASE ) != len(self.attributes ):
        raise ValueError(
            F'''This processor requires {len(self.attributes )} arguments: {", ".join(self.attributes )}. Got '''
            F'''{len(__SCREAMING_SNAKE_CASE )} 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():
        lowerCamelCase_   					=						getattr(self	,						F'''{attribute_name}_class''' )
        # Nothing is ever going to be an instance of "AutoXxx", in that case we check the base class.
        lowerCamelCase_   					=						AUTO_TO_BASE_CLASS_MAPPING.get(__SCREAMING_SNAKE_CASE	,						__SCREAMING_SNAKE_CASE )
        if isinstance(__SCREAMING_SNAKE_CASE	,						__SCREAMING_SNAKE_CASE ):
          lowerCamelCase_   					=						tuple(getattr(__SCREAMING_SNAKE_CASE	,						__SCREAMING_SNAKE_CASE ) for n in class_name if n is not None )
        else:
          lowerCamelCase_   					=						getattr(__SCREAMING_SNAKE_CASE	,						__SCREAMING_SNAKE_CASE )

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

        setattr(self	,						__SCREAMING_SNAKE_CASE	,						__SCREAMING_SNAKE_CASE )






    def __repr__(	self					:							Optional[int] )					->		List[str]:
      lowerCamelCase_   					=						[F'''- {name}: {repr(getattr(self	,						__SCREAMING_SNAKE_CASE ) )}''' for name in self.attributes]
      lowerCamelCase_   					=						'\n'.join(__SCREAMING_SNAKE_CASE )
      return F'''{self.__class__.__name__}:\n{attributes_repr}'''






    def        UpperCamelCase	(	self					:							Union[str, Any]	,						__SCREAMING_SNAKE_CASE					:							List[str]	,						__SCREAMING_SNAKE_CASE					:							bool = False	,						**__SCREAMING_SNAKE_CASE					:							Union[str, Any] )					->		Union[str, Any]:
      os.makedirs(__SCREAMING_SNAKE_CASE	,						exist_ok=__SCREAMING_SNAKE_CASE )

      if push_to_hub:
        lowerCamelCase_   					=						kwargs.pop('commit_message'	,						__SCREAMING_SNAKE_CASE )
        lowerCamelCase_   					=						kwargs.pop('repo_id'	,						save_directory.split(os.path.sep )[-1] )
        lowerCamelCase_   					=						self._create_repo(__SCREAMING_SNAKE_CASE	,						**__SCREAMING_SNAKE_CASE )
        lowerCamelCase_   					=						self._get_files_timestamps(__SCREAMING_SNAKE_CASE )
      # 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:
        lowerCamelCase_   					=						[getattr(self	,						__SCREAMING_SNAKE_CASE ) for attribute_name in self.attributes]
        lowerCamelCase_   					=						[(a.init_kwargs if isinstance(__SCREAMING_SNAKE_CASE	,						__SCREAMING_SNAKE_CASE ) else a) for a in attrs]
        custom_object_save(self	,						__SCREAMING_SNAKE_CASE	,						config=__SCREAMING_SNAKE_CASE )

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

      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:
          lowerCamelCase_   					=						getattr(self	,						__SCREAMING_SNAKE_CASE )
          if isinstance(__SCREAMING_SNAKE_CASE	,						__SCREAMING_SNAKE_CASE ):
            del attribute.init_kwargs["auto_map"]

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






    @classmethod
    def        UpperCamelCase	(	cls					:							Dict	,						__SCREAMING_SNAKE_CASE					:							Union[str, os.PathLike]	,						__SCREAMING_SNAKE_CASE					:							Optional[Union[str, os.PathLike]] = None	,						__SCREAMING_SNAKE_CASE					:							bool = False	,						__SCREAMING_SNAKE_CASE					:							bool = False	,						__SCREAMING_SNAKE_CASE					:							Optional[Union[str, bool]] = None	,						__SCREAMING_SNAKE_CASE					:							str = "main"	,						**__SCREAMING_SNAKE_CASE					:							Optional[int]	,						)					->		Optional[int]:
      lowerCamelCase_   					=						cache_dir
      lowerCamelCase_   					=						force_download
      lowerCamelCase_   					=						local_files_only
      lowerCamelCase_   					=						revision

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

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

      lowerCamelCase_   					=						cls._get_arguments_from_pretrained(__SCREAMING_SNAKE_CASE	,						**__SCREAMING_SNAKE_CASE )
      return cls(*__SCREAMING_SNAKE_CASE )






    @classmethod
    def        UpperCamelCase	(	cls					:							Optional[Any]	,						__SCREAMING_SNAKE_CASE					:							Dict="AutoProcessor" )					->		Dict:
      if not isinstance(__SCREAMING_SNAKE_CASE	,						__SCREAMING_SNAKE_CASE ):
        lowerCamelCase_   					=						auto_class.__name__

      import transformers.models.auto as auto_module

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

      lowerCamelCase_   					=						auto_class






    @classmethod
    def        UpperCamelCase	(	cls					:							Any	,						__SCREAMING_SNAKE_CASE					:							List[Any]	,						**__SCREAMING_SNAKE_CASE					:							Optional[int] )					->		Optional[int]:
      lowerCamelCase_   					=						[]
      for attribute_name in cls.attributes:
        lowerCamelCase_   					=						getattr(cls	,						F'''{attribute_name}_class''' )
        if isinstance(__SCREAMING_SNAKE_CASE	,						__SCREAMING_SNAKE_CASE ):
          lowerCamelCase_   					=						tuple(getattr(__SCREAMING_SNAKE_CASE	,						__SCREAMING_SNAKE_CASE ) if n is not None else None for n in class_name )
          lowerCamelCase_   					=						kwargs.get('use_fast'	,						__SCREAMING_SNAKE_CASE )
          if use_fast and classes[1] is not None:
            lowerCamelCase_   					=						classes[1]
          else:
            lowerCamelCase_   					=						classes[0]
        else:
          lowerCamelCase_   					=						getattr(__SCREAMING_SNAKE_CASE	,						__SCREAMING_SNAKE_CASE )

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






    @property
    def        UpperCamelCase	(	self					:							List[str] )					->		Optional[Any]:
      lowerCamelCase_   					=						getattr(self	,						self.attributes[0] )
      return getattr(__SCREAMING_SNAKE_CASE	,						'model_input_names'	,						__SCREAMING_SNAKE_CASE )
_SCREAMING_SNAKE_CASE :    Any    =						copy_func(ProcessorMixin.push_to_hub)
if ProcessorMixin.push_to_hub.__doc__ is not None:
  _SCREAMING_SNAKE_CASE :    List[Any]    =						ProcessorMixin.push_to_hub.__doc__.format(
      object='''processor''', object_class='''AutoProcessor''', object_files='''processor files'''
  )












"""simple docstring"""





from ...configuration_utils import PretrainedConfig
from ...utils import logging


_SCREAMING_SNAKE_CASE :    List[Any]    =						logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE :    str    =						{
    '''facebook/regnet-y-040''': '''https://huggingface.co/facebook/regnet-y-040/blob/main/config.json''',
}






class 					a						( __snake_case		):
    SCREAMING_SNAKE_CASE						:					str						=			"""regnet"""
    SCREAMING_SNAKE_CASE						:					List[Any]						=			["""x""", """y"""]






    def __init__(	self					:							int	,						__SCREAMING_SNAKE_CASE					:							Any=3	,						__SCREAMING_SNAKE_CASE					:							Any=32	,						__SCREAMING_SNAKE_CASE					:							List[str]=[128, 192, 512, 1088]	,						__SCREAMING_SNAKE_CASE					:							Union[str, Any]=[2, 6, 12, 2]	,						__SCREAMING_SNAKE_CASE					:							str=64	,						__SCREAMING_SNAKE_CASE					:							List[Any]="y"	,						__SCREAMING_SNAKE_CASE					:							Optional[int]="relu"	,						**__SCREAMING_SNAKE_CASE					:							Union[str, Any]	,						)					->		Union[str, Any]:
      super().__init__(**__SCREAMING_SNAKE_CASE )
      if layer_type not in self.layer_types:
        raise ValueError(F'''layer_type={layer_type} is not one of {",".join(self.layer_types )}''' )
      lowerCamelCase_   					=						num_channels
      lowerCamelCase_   					=						embedding_size
      lowerCamelCase_   					=						hidden_sizes
      lowerCamelCase_   					=						depths
      lowerCamelCase_   					=						groups_width
      lowerCamelCase_   					=						layer_type
      lowerCamelCase_   					=						hidden_act
      # always downsample in the first stage
      lowerCamelCase_   					=						True




