'''simple docstring'''

from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCamelCase__     :	Any				=			logging.get_logger(__name__)

UpperCamelCase__     :	Optional[int]				=			{
    'camembert-base': 'https://huggingface.co/camembert-base/resolve/main/config.json',
    'umberto-commoncrawl-cased-v1': (
        'https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json'
    ),
    'umberto-wikipedia-uncased-v1': (
        'https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json'
    ),
}


class 				_lowercase	(      __lowerCAmelCase   ):
      '''simple docstring'''


      UpperCAmelCase_      :      List[str]      							=   '''camembert'''




      def __init__(				self					,lowerCamelCase_=30522					,lowerCamelCase_=768					,lowerCamelCase_=12					,lowerCamelCase_=12					,lowerCamelCase_=3072					,lowerCamelCase_="gelu"					,lowerCamelCase_=0.1					,lowerCamelCase_=0.1					,lowerCamelCase_=512					,lowerCamelCase_=2					,lowerCamelCase_=0.02					,lowerCamelCase_=1e-12					,lowerCamelCase_=1					,lowerCamelCase_=0					,lowerCamelCase_=2					,lowerCamelCase_="absolute"					,lowerCamelCase_=True					,lowerCamelCase_=None					,**lowerCamelCase_					,)			->			int:



         '''simple docstring'''



         super().__init__(pad_token_id=lowerCAmelCase_					,bos_token_id=lowerCAmelCase_					,eos_token_id=lowerCAmelCase_					,**lowerCAmelCase_							)

         UpperCAmelCase__							:				Optional[int]   				=  vocab_size
         UpperCAmelCase__							:				List[str]   				=  hidden_size
         UpperCAmelCase__							:				Tuple   				=  num_hidden_layers
         UpperCAmelCase__							:				str   				=  num_attention_heads
         UpperCAmelCase__							:				Union[str, Any]   				=  hidden_act
         UpperCAmelCase__							:				Optional[int]   				=  intermediate_size
         UpperCAmelCase__							:				Optional[Any]   				=  hidden_dropout_prob
         UpperCAmelCase__							:				List[Any]   				=  attention_probs_dropout_prob
         UpperCAmelCase__							:				Dict   				=  max_position_embeddings
         UpperCAmelCase__							:				Union[str, Any]   				=  type_vocab_size
         UpperCAmelCase__							:				Any   				=  initializer_range
         UpperCAmelCase__							:				Union[str, Any]   				=  layer_norm_eps
         UpperCAmelCase__							:				Dict   				=  position_embedding_type
         UpperCAmelCase__							:				Optional[int]   				=  use_cache
         UpperCAmelCase__							:				Union[str, Any]   				=  classifier_dropout




class 				_lowercase	(      __lowerCAmelCase   ):
      '''simple docstring'''


      @property
      def 		lowerCAmelCase__					(				self							)			->			Mapping[str, Mapping[int, str]]:



         '''simple docstring'''



         if self.task == "multiple-choice":
            UpperCAmelCase__							:				Union[str, Any]   				=  {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
         else:
            UpperCAmelCase__							:				List[Any]   				=  {0: '''batch''', 1: '''sequence'''}
         return OrderedDict(
             [
                 ('''input_ids''', dynamic_axis),
                 ('''attention_mask''', dynamic_axis),
             ]							)





'''simple docstring'''

import warnings

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


class 				_lowercase	(      lowerCAmelCase   ):
      '''simple docstring'''


      UpperCAmelCase_      :      Tuple      							=   ['''image_processor''', '''tokenizer''']
      UpperCAmelCase_      :      str      							=   '''CLIPImageProcessor'''
      UpperCAmelCase_      :      Dict      							=   ('''CLIPTokenizer''', '''CLIPTokenizerFast''')




      def __init__(				self					,lowerCamelCase_=None					,lowerCamelCase_=None					,**lowerCamelCase_							)			->			Any:



         '''simple docstring'''



         UpperCAmelCase__							:				Any   				=  None
         if "feature_extractor" in kwargs:
            warnings.warn(
                '''The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'''
                ''' instead.'''					,lowerCamelCase_					,)
            UpperCAmelCase__							:				str   				=  kwargs.pop('''feature_extractor'''							)

         UpperCAmelCase__							:				Optional[Any]   				=  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__(lowerCamelCase_					,lowerCamelCase_							)




      def __call__(				self					,lowerCamelCase_=None					,lowerCamelCase_=None					,lowerCamelCase_=None					,**lowerCamelCase_							)			->			Dict:



         '''simple docstring'''



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

         if text is not None:
            UpperCAmelCase__							:				Tuple   				=  self.tokenizer(lowerCamelCase_					,return_tensors=lowerCamelCase_					,**lowerCamelCase_							)

         if images is not None:
            UpperCAmelCase__							:				Optional[int]   				=  self.image_processor(lowerCamelCase_					,return_tensors=lowerCamelCase_					,**lowerCamelCase_							)

         if text is not None and images is not None:
            UpperCAmelCase__							:				str   				=  image_features.pixel_values
            return encoding
         elif text is not None:
            return encoding
         else:
            return BatchEncoding(data=dict(**lowerCamelCase_							)					,tensor_type=lowerCamelCase_							)




      def 		lowerCAmelCase__					(				self					,*lowerCamelCase_					,**lowerCamelCase_							)			->			Tuple:



         '''simple docstring'''



         return self.tokenizer.batch_decode(*lowerCamelCase_					,**lowerCamelCase_							)




      def 		lowerCAmelCase__					(				self					,*lowerCamelCase_					,**lowerCamelCase_							)			->			Tuple:



         '''simple docstring'''



         return self.tokenizer.decode(*lowerCamelCase_					,**lowerCamelCase_							)




      @property
      def 		lowerCAmelCase__					(				self							)			->			List[str]:



         '''simple docstring'''



         UpperCAmelCase__							:				Optional[Any]   				=  self.tokenizer.model_input_names
         UpperCAmelCase__							:				Optional[Any]   				=  self.image_processor.model_input_names
         return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names							)							)




      @property
      def 		lowerCAmelCase__					(				self							)			->			List[Any]:



         '''simple docstring'''



         warnings.warn(
             '''`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'''					,lowerCamelCase_					,)
         return self.image_processor_class




      @property
      def 		lowerCAmelCase__					(				self							)			->			List[str]:



         '''simple docstring'''



         warnings.warn(
             '''`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'''					,lowerCamelCase_					,)
         return self.image_processor




