



"""simple docstring"""

import warnings

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




class SCREAMING_SNAKE_CASE__					(		__snake_case      ):
						_lowerCAmelCase							=					["image_processor", "tokenizer"]
						_lowerCAmelCase							=					"ChineseCLIPImageProcessor"
						_lowerCAmelCase							=					("BertTokenizer", "BertTokenizerFast")



						def __init__(self						,     _lowercase=None						,     _lowercase=None						,     **_lowercase							):





													'''simple docstring'''

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

													__a		:		Tuple									=       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__(_lowercase						,     _lowercase							)
													__a		:		Optional[Any]									=       self.image_processor



						def __call__(self						,     _lowercase=None						,     _lowercase=None						,     _lowercase=None						,     **_lowercase							):





													'''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:
																				__a		:		Optional[int]									=       self.tokenizer(_lowercase						,     return_tensors=_lowercase						,     **_lowercase							)

													if images is not None:
																				__a		:		Tuple									=       self.image_processor(_lowercase						,     return_tensors=_lowercase						,     **_lowercase							)

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



						def     lowerCAmelCase__(self						,     *_lowercase						,     **_lowercase							):





													'''simple docstring'''

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



						def     lowerCAmelCase__(self						,     *_lowercase						,     **_lowercase							):





													'''simple docstring'''

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



						@property
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		Dict									=       self.tokenizer.model_input_names
													__a		:		Optional[int]									=       self.image_processor.model_input_names
													return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names							)							)





						@property
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

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






"""simple docstring"""

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


lowercase__			   =  logging.get_logger(__name__)

lowercase__			   =  {
    "sayakpaul/vit-msn-base": "https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json",
    # See all ViT MSN models at https://huggingface.co/models?filter=vit_msn
}




class SCREAMING_SNAKE_CASE__					(		__snake_case      ):
						_lowerCAmelCase							=					"vit_msn"



						def __init__(self						,     _lowercase=768						,     _lowercase=12						,     _lowercase=12						,     _lowercase=3072						,     _lowercase="gelu"						,     _lowercase=0.0						,     _lowercase=0.0						,     _lowercase=0.02						,     _lowercase=1e-06						,     _lowercase=224						,     _lowercase=16						,     _lowercase=3						,     _lowercase=True						,     **_lowercase						,     ):





													'''simple docstring'''

													super().__init__(**_lowercase							)

													__a		:		int									=       hidden_size
													__a		:		str									=       num_hidden_layers
													__a		:		str									=       num_attention_heads
													__a		:		Optional[Any]									=       intermediate_size
													__a		:		Union[str, Any]									=       hidden_act
													__a		:		Tuple									=       hidden_dropout_prob
													__a		:		Any									=       attention_probs_dropout_prob
													__a		:		List[Any]									=       initializer_range
													__a		:		Any									=       layer_norm_eps
													__a		:		Dict									=       image_size
													__a		:		List[Any]									=       patch_size
													__a		:		Dict									=       num_channels
													__a		:		Optional[Any]									=       qkv_bias

