

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__										=      {
    "MBZUAI/swiftformer-xs": "https://huggingface.co/MBZUAI/swiftformer-xs/resolve/main/config.json",
}







class  UpperCamelCase_      (	_snake_case      ):


  """simple docstring"""
  SCREAMING_SNAKE_CASE__					:			Union[str, Any]					    =   """swiftformer"""



  def __init__(						self     :					Dict  ,	A_     :					List[str]=3  ,	A_     :					int=[3, 3, 6, 4]  ,	A_     :					int=[48, 56, 112, 220]  ,	A_     :					str=4  ,	A_     :					List[Any]=[True, True, True, True]  ,	A_     :					Tuple="gelu"  ,	A_     :					List[Any]=3  ,	A_     :					Optional[int]=2  ,	A_     :					int=1  ,	A_     :					Optional[int]=0.0  ,	A_     :					Optional[int]=True  ,	A_     :					str=1E-5  ,	A_     :					List[Any]=1E-5  ,	**A_     :					List[Any]  ,	)       ->			List[str]:
      super().__init__(**A_						)
      SCREAMING_SNAKE_CASE__         =    num_channels
      SCREAMING_SNAKE_CASE__         =    depths
      SCREAMING_SNAKE_CASE__         =    embed_dims
      SCREAMING_SNAKE_CASE__         =    mlp_ratio
      SCREAMING_SNAKE_CASE__         =    downsamples
      SCREAMING_SNAKE_CASE__         =    hidden_act
      SCREAMING_SNAKE_CASE__         =    down_patch_size
      SCREAMING_SNAKE_CASE__         =    down_stride
      SCREAMING_SNAKE_CASE__         =    down_pad
      SCREAMING_SNAKE_CASE__         =    drop_path_rate
      SCREAMING_SNAKE_CASE__         =    use_layer_scale
      SCREAMING_SNAKE_CASE__         =    layer_scale_init_value
      SCREAMING_SNAKE_CASE__         =    batch_norm_eps







class  UpperCamelCase_      (	_snake_case      ):


  """simple docstring"""
  SCREAMING_SNAKE_CASE__					:			Any					    =   version.parse("""1.11"""      )



  @property
  def   _UpperCamelCase     (						self     :					Union[str, Any]						)       ->			Mapping[str, Mapping[int, str]]:
      return OrderedDict(
          [
              ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
          ]						)







  @property
  def   _UpperCamelCase     (						self     :					List[str]						)       ->			float:
      return 1E-4










import copy
from typing import Dict

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


__lowerCamelCase						= logging.get_logger(__name__)

class      UpperCamelCase_							(				UpperCamelCase       ):
						lowercase									=  '''semantic'''




						def __init__(    self		,	lowercase=10_000		,	lowercase=True		,	lowercase=768		,	lowercase=False		,	lowercase=False		,	lowercase=False		,	lowercase=False		,	lowercase=0.7		,	lowercase=True		,	lowercase=10_048		,	lowercase=129_595		,	lowercase=129_599		,	lowercase=10_000		,	lowercase=256		,	lowercase=49.9		,	**lowercase		,	)			->						int:
													super().__init__(
													    temperature=lowercase		,	do_sample=lowercase		,	eos_token_id=lowercase		,	renormalize_logits=lowercase		,	max_new_tokens=lowercase		,	output_scores=lowercase		,	return_dict_in_generate=lowercase		,	output_hidden_states=lowercase		,	output_attentions=lowercase		,	**lowercase		,	)

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

class      UpperCamelCase_							(				UpperCamelCase       ):
						lowercase									=  '''coarse_acoustics'''




						def __init__(    self		,	lowercase=True		,	lowercase=False		,	lowercase=False		,	lowercase=False		,	lowercase=False		,	lowercase=0.7		,	lowercase=True		,	lowercase=12_048		,	lowercase=75		,	lowercase=2		,	lowercase=12_050		,	lowercase=256		,	lowercase = 630		,	lowercase = 60		,	**lowercase		,	)			->						List[Any]:
													super().__init__(
													    temperature=lowercase		,	do_sample=lowercase		,	renormalize_logits=lowercase		,	output_scores=lowercase		,	return_dict_in_generate=lowercase		,	output_hidden_states=lowercase		,	output_attentions=lowercase		,	**lowercase		,	)

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

class      UpperCamelCase_							(				UpperCamelCase       ):
						lowercase									=  '''fine_acoustics'''




						def __init__(    self		,	lowercase=0.5		,	lowercase=512		,	lowercase=1_024		,	lowercase=8		,	**lowercase		,	)			->						str:
													super().__init__(temperature=lowercase       )

													_a  :    Tuple			=						max_fine_history_length
													_a  :    Tuple			=						max_fine_input_length
													_a  :    Any			=						n_fine_codebooks

class      UpperCamelCase_							(				UpperCamelCase       ):
						lowercase									=  '''bark'''
						lowercase									=  True




						def __init__(    self		,	lowercase = None		,	lowercase = None		,	lowercase = None		,	lowercase=24_000		,	lowercase=1_024		,	**lowercase		,	)			->						List[str]:
													if semantic_config is None:
																				_a  :    str			=						{}
																				logger.info('''semantic_config is None. initializing the semantic model with default values.'''       )

													if coarse_acoustics_config is None:
																				_a  :    Any			=						{}
																				logger.info('''coarse_acoustics_config is None. initializing the coarse model with default values.'''       )

													if fine_acoustics_config is None:
																				_a  :    int			=						{}
																				logger.info('''fine_acoustics_config is None. initializing the fine model with default values.'''       )

													_a  :    List[Any]			=						BarkSemanticGenerationConfig(**lowercase       )
													_a  :    Union[str, Any]			=						BarkCoarseGenerationConfig(**lowercase       )
													_a  :    str			=						BarkFineGenerationConfig(**lowercase       )

													_a  :    List[str]			=						sample_rate
													_a  :    str			=						codebook_size




						@classmethod
						def      snake_case__(    cls		,	lowercase		,	lowercase		,	lowercase		,	**lowercase		,	)			->						List[Any]:
													return cls(
													    semantic_config=semantic_config.to_dict()		,	coarse_acoustics_config=coarse_acoustics_config.to_dict()		,	fine_acoustics_config=fine_acoustics_config.to_dict()		,	**lowercase		,	)







						def      snake_case__(    self       )			->						List[str]:
													_a  :    Any			=						copy.deepcopy(self.__dict__       )

													_a  :    str			=						self.semantic_config.to_dict()
													_a  :    Any			=						self.coarse_acoustics_config.to_dict()
													_a  :    Union[str, Any]			=						self.fine_acoustics_config.to_dict()

													_a  :    List[str]			=						self.__class__.model_type
													return output