

import warnings

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



class 					__snake_case     (			lowerCAmelCase__				):
  __lowerCAmelCase   :		Union[str, Any]         =     ['image_processor', 'tokenizer']
  __lowerCAmelCase   :		Tuple         =     'VideoMAEImageProcessor'
  __lowerCAmelCase   :		Optional[Any]         =     ('CLIPTokenizer', 'CLIPTokenizerFast')

  def __init__(    self  ,						_A=None  ,						_A=None  ,						**_A):
      SCREAMING_SNAKE_CASE_													=  None
      if "feature_extractor" in kwargs:
          warnings.warn(
              'The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'
              ' instead.'  ,						_A  ,						)
          SCREAMING_SNAKE_CASE_													=  kwargs.pop('feature_extractor')

      SCREAMING_SNAKE_CASE_													=  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__(_A  ,						_A)
      SCREAMING_SNAKE_CASE_													=  self.image_processor

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

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

      if text is not None:
          SCREAMING_SNAKE_CASE_													=  self.tokenizer(_A  ,						return_tensors=_A  ,						**_A)

      if videos is not None:
          SCREAMING_SNAKE_CASE_													=  self.image_processor(_A  ,						return_tensors=_A  ,						**_A)

      if text is not None and videos is not None:
          SCREAMING_SNAKE_CASE_													=  image_features.pixel_values
          return encoding
      elif text is not None:
          return encoding
      else:
          return BatchEncoding(data=dict(**_A)  ,						tensor_type=_A)

  def   lowerCAmelCase__   (    self  ,						*_A  ,						**_A):
      return self.tokenizer.batch_decode(*_A  ,						**_A)

  def   lowerCAmelCase__   (    self  ,						*_A  ,						**_A):
      return self.tokenizer.decode(*_A  ,						**_A)

  @property
  def   lowerCAmelCase__   (    self):
      return ["input_ids", "attention_mask", "position_ids", "pixel_values"]

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


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





import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig


UpperCamelCase__     :					Optional[Any]								=			logging.get_logger(__name__)

UpperCamelCase__     :					List[Any]								=			{
    "facebook/musicgen-small": "https://huggingface.co/facebook/musicgen-small/resolve/main/config.json",
    # See all Musicgen models at https://huggingface.co/models?filter=musicgen
}



class 					__snake_case     (			lowerCAmelCase__				):
  __lowerCAmelCase   :		Any         =     'musicgen_decoder'
  __lowerCAmelCase   :		Optional[Any]         =     ['past_key_values']

  def __init__(    self  ,						_A=2048  ,						_A=2048  ,						_A=24  ,						_A=4096  ,						_A=16  ,						_A=0.0  ,						_A=True  ,						_A="gelu"  ,						_A=1024  ,						_A=0.1  ,						_A=0.0  ,						_A=0.0  ,						_A=0.0_2  ,						_A=False  ,						_A=4  ,						_A=2048  ,						_A=2048  ,						_A=None  ,						_A=False  ,						**_A  ,						):
      SCREAMING_SNAKE_CASE_													=  vocab_size
      SCREAMING_SNAKE_CASE_													=  max_position_embeddings
      SCREAMING_SNAKE_CASE_													=  hidden_size
      SCREAMING_SNAKE_CASE_													=  ffn_dim
      SCREAMING_SNAKE_CASE_													=  num_hidden_layers
      SCREAMING_SNAKE_CASE_													=  num_attention_heads
      SCREAMING_SNAKE_CASE_													=  dropout
      SCREAMING_SNAKE_CASE_													=  attention_dropout
      SCREAMING_SNAKE_CASE_													=  activation_dropout
      SCREAMING_SNAKE_CASE_													=  activation_function
      SCREAMING_SNAKE_CASE_													=  initializer_factor
      SCREAMING_SNAKE_CASE_													=  layerdrop
      SCREAMING_SNAKE_CASE_													=  use_cache
      SCREAMING_SNAKE_CASE_													=  scale_embedding  # scale factor will be sqrt(d_model) if True
      SCREAMING_SNAKE_CASE_													=  num_codebooks
      super().__init__(
          pad_token_id=_A  ,						bos_token_id=_A  ,						eos_token_id=_A  ,						tie_word_embeddings=_A  ,						**_A  ,						)






class 					__snake_case     (			lowerCAmelCase__				):
  __lowerCAmelCase   :		int         =     'musicgen'
  __lowerCAmelCase   :		Optional[Any]         =     True

  def __init__(    self  ,						**_A):
      super().__init__(**_A)
      if "text_encoder" not in kwargs or "audio_encoder" not in kwargs or "decoder" not in kwargs:
          raise ValueError('Config has to be initialized with text_encoder, audio_encoder and decoder config')

      SCREAMING_SNAKE_CASE_													=  kwargs.pop('text_encoder')
      SCREAMING_SNAKE_CASE_													=  text_encoder_config.pop('model_type')

      SCREAMING_SNAKE_CASE_													=  kwargs.pop('audio_encoder')
      SCREAMING_SNAKE_CASE_													=  audio_encoder_config.pop('model_type')

      SCREAMING_SNAKE_CASE_													=  kwargs.pop('decoder')

      SCREAMING_SNAKE_CASE_													=  AutoConfig.for_model(_A  ,						**_A)
      SCREAMING_SNAKE_CASE_													=  AutoConfig.for_model(_A  ,						**_A)
      SCREAMING_SNAKE_CASE_													=  MusicgenDecoderConfig(**_A)
      SCREAMING_SNAKE_CASE_													=  True

  @classmethod
  def   lowerCAmelCase__   (    cls  ,						_A  ,						_A  ,						_A  ,						**_A  ,						):
      return cls(
          text_encoder=text_encoder_config.to_dict()  ,						audio_encoder=audio_encoder_config.to_dict()  ,						decoder=decoder_config.to_dict()  ,						**_A  ,						)


  def   lowerCAmelCase__   (    self):
      SCREAMING_SNAKE_CASE_													=  copy.deepcopy(self.__dict__)
      SCREAMING_SNAKE_CASE_													=  self.text_encoder.to_dict()
      SCREAMING_SNAKE_CASE_													=  self.audio_encoder.to_dict()
      SCREAMING_SNAKE_CASE_													=  self.decoder.to_dict()
      SCREAMING_SNAKE_CASE_													=  self.__class__.model_type
      return output


