




import copy
from typing import Dict

from ...generation.configuration_utils import GenerationConfig
from ...utils import logging


a__		    =    logging.get_logger(__name__)


class       SCREAMING_SNAKE_CASE_							(					_UpperCamelCase      ):



 """simple docstring"""


 __magic_name__      :					str			  =		'semantic'






 def __init__(				self		:	Tuple				,    lowerCAmelCase		:	Tuple=10000				,    lowerCAmelCase		:	List[str]=True				,    lowerCAmelCase		:	str=768				,    lowerCAmelCase		:	Union[str, Any]=False				,    lowerCAmelCase		:	Optional[Any]=False				,    lowerCAmelCase		:	Dict=False				,    lowerCAmelCase		:	Any=False				,    lowerCAmelCase		:	int=0.7				,    lowerCAmelCase		:	Any=True				,    lowerCAmelCase		:	Optional[int]=10048				,    lowerCAmelCase		:	Any=129595				,    lowerCAmelCase		:	Optional[int]=129599				,    lowerCAmelCase		:	Tuple=10000				,    lowerCAmelCase		:	List[str]=256				,    lowerCAmelCase		:	Union[str, Any]=49.9				,    **lowerCAmelCase		:	List[str]				,    )  ->					str:







      """simple docstring"""







      super().__init__(
          temperature=lowerCAmelCase				,    do_sample=lowerCAmelCase				,    eos_token_id=lowerCAmelCase				,    renormalize_logits=lowerCAmelCase				,    max_new_tokens=lowerCAmelCase				,    output_scores=lowerCAmelCase				,    return_dict_in_generate=lowerCAmelCase				,    output_hidden_states=lowerCAmelCase				,    output_attentions=lowerCAmelCase				,    **lowerCAmelCase				,    )

      __UpperCamelCase				:  str								=			text_encoding_offset
      __UpperCamelCase				:  Optional[int]								=			text_pad_token
      __UpperCamelCase				:  Dict								=			eos_token_id
      __UpperCamelCase				:  Union[str, Any]								=			semantic_infer_token
      __UpperCamelCase				:  Tuple								=			semantic_vocab_size
      __UpperCamelCase				:  int								=			max_input_semantic_length
      __UpperCamelCase				:  Any								=			semantic_rate_hz






class       SCREAMING_SNAKE_CASE_							(					_UpperCamelCase      ):



 """simple docstring"""


 __magic_name__      :					Any			  =		'coarse_acoustics'






 def __init__(				self		:	List[str]				,    lowerCAmelCase		:	int=True				,    lowerCAmelCase		:	str=False				,    lowerCAmelCase		:	Optional[int]=False				,    lowerCAmelCase		:	List[str]=False				,    lowerCAmelCase		:	Tuple=False				,    lowerCAmelCase		:	int=0.7				,    lowerCAmelCase		:	List[Any]=True				,    lowerCAmelCase		:	Union[str, Any]=12048				,    lowerCAmelCase		:	List[str]=75				,    lowerCAmelCase		:	List[Any]=2				,    lowerCAmelCase		:	Union[str, Any]=12050				,    lowerCAmelCase		:	List[str]=256				,    lowerCAmelCase		:	int = 630				,    lowerCAmelCase		:	int = 60				,    **lowerCAmelCase		:	List[str]				,    )  ->					Tuple:







      """simple docstring"""







      super().__init__(
          temperature=lowerCAmelCase				,    do_sample=lowerCAmelCase				,    renormalize_logits=lowerCAmelCase				,    output_scores=lowerCAmelCase				,    return_dict_in_generate=lowerCAmelCase				,    output_hidden_states=lowerCAmelCase				,    output_attentions=lowerCAmelCase				,    **lowerCAmelCase				,    )

      __UpperCamelCase				:  Any								=			coarse_semantic_pad_token
      __UpperCamelCase				:  Optional[int]								=			coarse_rate_hz
      __UpperCamelCase				:  str								=			n_coarse_codebooks
      __UpperCamelCase				:  List[str]								=			coarse_infer_token
      __UpperCamelCase				:  Dict								=			max_coarse_input_length
      __UpperCamelCase				:  Union[str, Any]								=			max_coarse_history
      __UpperCamelCase				:  Optional[Any]								=			sliding_window_len






class       SCREAMING_SNAKE_CASE_							(					_UpperCamelCase      ):



 """simple docstring"""


 __magic_name__      :					Union[str, Any]			  =		'fine_acoustics'






 def __init__(				self		:	int				,    lowerCAmelCase		:	Dict=0.5				,    lowerCAmelCase		:	List[str]=512				,    lowerCAmelCase		:	Union[str, Any]=1024				,    lowerCAmelCase		:	Tuple=8				,    **lowerCAmelCase		:	Tuple				,    )  ->					List[Any]:







      """simple docstring"""







      super().__init__(temperature=lowerCAmelCase  )

      __UpperCamelCase				:  List[str]								=			max_fine_history_length
      __UpperCamelCase				:  List[str]								=			max_fine_input_length
      __UpperCamelCase				:  Union[str, Any]								=			n_fine_codebooks






class       SCREAMING_SNAKE_CASE_							(					_UpperCamelCase      ):



 """simple docstring"""


 __magic_name__      :					Any			  =		'bark'
 __magic_name__      :					int			  =		True






 def __init__(				self		:	Optional[int]				,    lowerCAmelCase		:	Dict = None				,    lowerCAmelCase		:	Dict = None				,    lowerCAmelCase		:	Dict = None				,    lowerCAmelCase		:	int=24000				,    lowerCAmelCase		:	Tuple=1024				,    **lowerCAmelCase		:	int				,    )  ->					str:







      """simple docstring"""







      if semantic_config is None:
           __UpperCamelCase				:  Dict								=			{}
           logger.info("""semantic_config is None. initializing the semantic model with default values."""  )

      if coarse_acoustics_config is None:
           __UpperCamelCase				:  List[Any]								=			{}
           logger.info("""coarse_acoustics_config is None. initializing the coarse model with default values."""  )

      if fine_acoustics_config is None:
           __UpperCamelCase				:  Union[str, Any]								=			{}
           logger.info("""fine_acoustics_config is None. initializing the fine model with default values."""  )

      __UpperCamelCase				:  List[str]								=			BarkSemanticGenerationConfig(**lowerCAmelCase  )
      __UpperCamelCase				:  int								=			BarkCoarseGenerationConfig(**lowerCAmelCase  )
      __UpperCamelCase				:  List[str]								=			BarkFineGenerationConfig(**lowerCAmelCase  )

      __UpperCamelCase				:  int								=			sample_rate
      __UpperCamelCase				:  List[str]								=			codebook_size






 @classmethod
 def 				lowerCamelCase__    (				cls		:	str				,    lowerCAmelCase		:	BarkSemanticGenerationConfig				,    lowerCAmelCase		:	BarkCoarseGenerationConfig				,    lowerCAmelCase		:	BarkFineGenerationConfig				,    **lowerCAmelCase		:	List[Any]				,    )  ->					List[Any]:







      """simple docstring"""







      return cls(
          semantic_config=semantic_config.to_dict()				,    coarse_acoustics_config=coarse_acoustics_config.to_dict()				,    fine_acoustics_config=fine_acoustics_config.to_dict()				,    **lowerCAmelCase				,    )






 def 				lowerCamelCase__    (				self		:	Optional[int]  )  ->					Tuple:







      """simple docstring"""







      __UpperCamelCase				:  str								=			copy.deepcopy(self.__dict__  )

      __UpperCamelCase				:  int								=			self.semantic_config.to_dict()
      __UpperCamelCase				:  Optional[Any]								=			self.coarse_acoustics_config.to_dict()
      __UpperCamelCase				:  List[Any]								=			self.fine_acoustics_config.to_dict()

      __UpperCamelCase				:  Optional[int]								=			self.__class__.model_type
      return output












from collections import OrderedDict
from typing import Mapping

from packaging import version

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


a__		    =    logging.get_logger(__name__)

a__		    =    {
    '''apple/mobilevit-small''': '''https://huggingface.co/apple/mobilevit-small/resolve/main/config.json''',
    '''apple/mobilevit-x-small''': '''https://huggingface.co/apple/mobilevit-x-small/resolve/main/config.json''',
    '''apple/mobilevit-xx-small''': '''https://huggingface.co/apple/mobilevit-xx-small/resolve/main/config.json''',
    '''apple/deeplabv3-mobilevit-small''': (
        '''https://huggingface.co/apple/deeplabv3-mobilevit-small/resolve/main/config.json'''
    ),
    '''apple/deeplabv3-mobilevit-x-small''': (
        '''https://huggingface.co/apple/deeplabv3-mobilevit-x-small/resolve/main/config.json'''
    ),
    '''apple/deeplabv3-mobilevit-xx-small''': (
        '''https://huggingface.co/apple/deeplabv3-mobilevit-xx-small/resolve/main/config.json'''
    ),
    # See all MobileViT models at https://huggingface.co/models?filter=mobilevit
}


class       SCREAMING_SNAKE_CASE_							(					_UpperCamelCase      ):



	"""simple docstring"""


	__magic_name__      :					Any			  =		'mobilevit'






	def __init__(				self		:	int				,    lowerCAmelCase		:	Dict=3				,    lowerCAmelCase		:	Dict=256				,    lowerCAmelCase		:	Any=2				,    lowerCAmelCase		:	Any=[144, 192, 240]				,    lowerCAmelCase		:	int=[16, 32, 64, 96, 128, 160, 640]				,    lowerCAmelCase		:	List[Any]=4				,    lowerCAmelCase		:	Tuple=2.0				,    lowerCAmelCase		:	Tuple=4.0				,    lowerCAmelCase		:	List[str]="silu"				,    lowerCAmelCase		:	Tuple=3				,    lowerCAmelCase		:	Tuple=32				,    lowerCAmelCase		:	Any=0.1				,    lowerCAmelCase		:	List[str]=0.0				,    lowerCAmelCase		:	Union[str, Any]=0.1				,    lowerCAmelCase		:	List[str]=0.02				,    lowerCAmelCase		:	Optional[Any]=1E-5				,    lowerCAmelCase		:	Union[str, Any]=True				,    lowerCAmelCase		:	List[str]=256				,    lowerCAmelCase		:	List[Any]=[6, 12, 18]				,    lowerCAmelCase		:	Tuple=0.1				,    lowerCAmelCase		:	List[str]=255				,    **lowerCAmelCase		:	Union[str, Any]				,    )  ->					Optional[Any]:







						"""simple docstring"""







						super().__init__(**lowerCAmelCase  )

						__UpperCamelCase				:  Tuple								=			num_channels
						__UpperCamelCase				:  Union[str, Any]								=			image_size
						__UpperCamelCase				:  List[Any]								=			patch_size
						__UpperCamelCase				:  Optional[int]								=			hidden_sizes
						__UpperCamelCase				:  Union[str, Any]								=			neck_hidden_sizes
						__UpperCamelCase				:  List[str]								=			num_attention_heads
						__UpperCamelCase				:  Union[str, Any]								=			mlp_ratio
						__UpperCamelCase				:  Tuple								=			expand_ratio
						__UpperCamelCase				:  Optional[Any]								=			hidden_act
						__UpperCamelCase				:  int								=			conv_kernel_size
						__UpperCamelCase				:  Any								=			output_stride
						__UpperCamelCase				:  int								=			hidden_dropout_prob
						__UpperCamelCase				:  Union[str, Any]								=			attention_probs_dropout_prob
						__UpperCamelCase				:  Dict								=			classifier_dropout_prob
						__UpperCamelCase				:  Any								=			initializer_range
						__UpperCamelCase				:  List[str]								=			layer_norm_eps
						__UpperCamelCase				:  Union[str, Any]								=			qkv_bias

						# decode head attributes for semantic segmentation
						__UpperCamelCase				:  Any								=			aspp_out_channels
						__UpperCamelCase				:  Union[str, Any]								=			atrous_rates
						__UpperCamelCase				:  Union[str, Any]								=			aspp_dropout_prob
						__UpperCamelCase				:  List[str]								=			semantic_loss_ignore_index






class       SCREAMING_SNAKE_CASE_							(					_UpperCamelCase      ):



	"""simple docstring"""


	__magic_name__      :					Optional[Any]			  =		version.parse('1.11'      )






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







						"""simple docstring"""







						return OrderedDict([("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""})]  )






	@property
	def 				lowerCamelCase__    (				self		:	List[Any]  )  ->					Mapping[str, Mapping[int, str]]:







						"""simple docstring"""







						if self.task == "image-classification":
											return OrderedDict([("""logits""", {0: """batch"""})]  )
						else:
											return OrderedDict([("""last_hidden_state""", {0: """batch"""}), ("""pooler_output""", {0: """batch"""})]  )






	@property
	def 				lowerCamelCase__    (				self		:	Optional[int]  )  ->					float:







						"""simple docstring"""







						return 1E-4






