





import warnings
from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class        snake_case_		(			_A):
  lowerCamelCase    :List[str]						=     ["image_processor", "tokenizer"]
  lowerCamelCase    :Any						=     "ViltImageProcessor"
  lowerCamelCase    :Optional[int]						=     ("BertTokenizer", "BertTokenizerFast")







  def __init__(		self			,     __lowercase=None			,     __lowercase=None			,     **__lowercase   )				->   Tuple:
    lowerCamelCase   : 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			,     )
      lowerCamelCase   : List[Any]								=kwargs.pop('''feature_extractor'''   )

    lowerCamelCase   : List[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__(__lowercase			,     __lowercase   )
    lowerCamelCase   : Optional[int]								=self.image_processor







  def __call__(		self			,     __lowercase			,     __lowercase = None			,     __lowercase = True			,     __lowercase = False			,     __lowercase = None			,     __lowercase = None			,     __lowercase = 0			,     __lowercase = None			,     __lowercase = None			,     __lowercase = None			,     __lowercase = False			,     __lowercase = False			,     __lowercase = False			,     __lowercase = False			,     __lowercase = True			,     __lowercase = None			,     **__lowercase			,     )				->   BatchEncoding:
    lowerCamelCase   : Tuple								=self.tokenizer(
        text=__lowercase			,     add_special_tokens=__lowercase			,     padding=__lowercase			,     truncation=__lowercase			,     max_length=__lowercase			,     stride=__lowercase			,     pad_to_multiple_of=__lowercase			,     return_token_type_ids=__lowercase			,     return_attention_mask=__lowercase			,     return_overflowing_tokens=__lowercase			,     return_special_tokens_mask=__lowercase			,     return_offsets_mapping=__lowercase			,     return_length=__lowercase			,     verbose=__lowercase			,     return_tensors=__lowercase			,     **__lowercase			,     )
    # add pixel_values + pixel_mask
    lowerCamelCase   : List[str]								=self.image_processor(__lowercase			,     return_tensors=__lowercase   )
    encoding.update(__lowercase   )

    return encoding







  def 			__lowercase   (		self			,     *__lowercase			,     **__lowercase   )				->   Any:
    return self.tokenizer.batch_decode(*__lowercase			,     **__lowercase   )







  def 			__lowercase   (		self			,     *__lowercase			,     **__lowercase   )				->   Dict:
    return self.tokenizer.decode(*__lowercase			,     **__lowercase   )







  @property
  def 			__lowercase   (		self   )				->   Dict:
    lowerCamelCase   : Tuple								=self.tokenizer.model_input_names
    lowerCamelCase   : Optional[Any]								=self.image_processor.model_input_names
    return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names   )   )







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







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








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


snake_case_							=			logging.get_logger(__name__)

snake_case_							=			{
    '''facebook/timesformer''': '''https://huggingface.co/facebook/timesformer/resolve/main/config.json''',
}
class        snake_case_		(			_A):
		lowerCamelCase    :Union[str, Any]						=     "timesformer"







		def __init__(		self			,     __lowercase=2_2_4			,     __lowercase=1_6			,     __lowercase=3			,     __lowercase=8			,     __lowercase=7_6_8			,     __lowercase=1_2			,     __lowercase=1_2			,     __lowercase=3_0_7_2			,     __lowercase="gelu"			,     __lowercase=0.0			,     __lowercase=0.0			,     __lowercase=0.0_2			,     __lowercase=1e-6			,     __lowercase=True			,     __lowercase="divided_space_time"			,     __lowercase=0			,     **__lowercase			,     )				->   List[Any]:
				super().__init__(**__lowercase   )

				lowerCamelCase   : int								=image_size
				lowerCamelCase   : List[str]								=patch_size
				lowerCamelCase   : Union[str, Any]								=num_channels
				lowerCamelCase   : str								=num_frames

				lowerCamelCase   : Dict								=hidden_size
				lowerCamelCase   : int								=num_hidden_layers
				lowerCamelCase   : Dict								=num_attention_heads
				lowerCamelCase   : Dict								=intermediate_size
				lowerCamelCase   : Union[str, Any]								=hidden_act
				lowerCamelCase   : str								=hidden_dropout_prob
				lowerCamelCase   : Union[str, Any]								=attention_probs_dropout_prob
				lowerCamelCase   : List[Any]								=initializer_range
				lowerCamelCase   : List[Any]								=layer_norm_eps
				lowerCamelCase   : List[str]								=qkv_bias

				lowerCamelCase   : Tuple								=attention_type
				lowerCamelCase   : List[Any]								=drop_path_rate

