






import copy
from typing import Dict

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


_a				     =  logging.get_logger(__name__)





class __lowerCamelCase			(				UpperCAmelCase__):





	"""simple docstring"""






	UpperCamelCase__								=				"semantic"

	def __init__(							self	,   UpperCAmelCase=1_0000	,   UpperCAmelCase=True	,   UpperCAmelCase=768	,   UpperCAmelCase=False	,   UpperCAmelCase=False	,   UpperCAmelCase=False	,   UpperCAmelCase=False	,   UpperCAmelCase=0.7	,   UpperCAmelCase=True	,   UpperCAmelCase=1_0048	,   UpperCAmelCase=12_9595	,   UpperCAmelCase=12_9599	,   UpperCAmelCase=1_0000	,   UpperCAmelCase=256	,   UpperCAmelCase=49.9	,   **UpperCAmelCase	,   ):
							"""simple docstring"""







							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	,   )

							_UpperCAmelCase     =      text_encoding_offset
							_UpperCAmelCase     =      text_pad_token
							_UpperCAmelCase     =      eos_token_id
							_UpperCAmelCase     =      semantic_infer_token
							_UpperCAmelCase     =      semantic_vocab_size
							_UpperCAmelCase     =      max_input_semantic_length
							_UpperCAmelCase     =      semantic_rate_hz





class __lowerCamelCase			(				UpperCAmelCase__):





	"""simple docstring"""






	UpperCamelCase__								=				"coarse_acoustics"

	def __init__(							self	,   UpperCAmelCase=True	,   UpperCAmelCase=False	,   UpperCAmelCase=False	,   UpperCAmelCase=False	,   UpperCAmelCase=False	,   UpperCAmelCase=0.7	,   UpperCAmelCase=True	,   UpperCAmelCase=1_2048	,   UpperCAmelCase=75	,   UpperCAmelCase=2	,   UpperCAmelCase=1_2050	,   UpperCAmelCase=256	,   UpperCAmelCase = 630	,   UpperCAmelCase = 60	,   **UpperCAmelCase	,   ):
							"""simple docstring"""







							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	,   )

							_UpperCAmelCase     =      coarse_semantic_pad_token
							_UpperCAmelCase     =      coarse_rate_hz
							_UpperCAmelCase     =      n_coarse_codebooks
							_UpperCAmelCase     =      coarse_infer_token
							_UpperCAmelCase     =      max_coarse_input_length
							_UpperCAmelCase     =      max_coarse_history
							_UpperCAmelCase     =      sliding_window_len





class __lowerCamelCase			(				UpperCAmelCase__):





	"""simple docstring"""






	UpperCamelCase__								=				"fine_acoustics"

	def __init__(							self	,   UpperCAmelCase=0.5	,   UpperCAmelCase=512	,   UpperCAmelCase=1024	,   UpperCAmelCase=8	,   **UpperCAmelCase	,   ):
							"""simple docstring"""







							super().__init__(temperature=__lowercase   )

							_UpperCAmelCase     =      max_fine_history_length
							_UpperCAmelCase     =      max_fine_input_length
							_UpperCAmelCase     =      n_fine_codebooks





class __lowerCamelCase			(				UpperCAmelCase__):





	"""simple docstring"""






	UpperCamelCase__								=				"bark"
	UpperCamelCase__								=				True

	def __init__(							self	,   UpperCAmelCase = None	,   UpperCAmelCase = None	,   UpperCAmelCase = None	,   UpperCAmelCase=2_4000	,   UpperCAmelCase=1024	,   **UpperCAmelCase	,   ):
							"""simple docstring"""







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

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

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

							_UpperCAmelCase     =      BarkSemanticGenerationConfig(**__lowercase   )
							_UpperCAmelCase     =      BarkCoarseGenerationConfig(**__lowercase   )
							_UpperCAmelCase     =      BarkFineGenerationConfig(**__lowercase   )

							_UpperCAmelCase     =      sample_rate
							_UpperCAmelCase     =      codebook_size

	@classmethod
	def 	UpperCamelCase   (							cls	,   UpperCAmelCase	,   UpperCAmelCase	,   UpperCAmelCase	,   **UpperCAmelCase	,   ):
							"""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()	,   **__lowercase	,   )

	def 	UpperCamelCase   (							self   ):
							"""simple docstring"""







							_UpperCAmelCase     =      copy.deepcopy(self.__dict__   )

							_UpperCAmelCase     =      self.semantic_config.to_dict()
							_UpperCAmelCase     =      self.coarse_acoustics_config.to_dict()
							_UpperCAmelCase     =      self.fine_acoustics_config.to_dict()

							_UpperCAmelCase     =      self.__class__.model_type
							return output








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


_a				     =  logging.get_logger(__name__)

_a				     =  {
    '''facebook/regnet-y-040''': '''https://huggingface.co/facebook/regnet-y-040/blob/main/config.json''',
}





class __lowerCamelCase			(				snake_case__):





	"""simple docstring"""






	UpperCamelCase__								=				"regnet"
	UpperCamelCase__								=				["x", "y"]

	def __init__(							self	,   UpperCAmelCase=3	,   UpperCAmelCase=32	,   UpperCAmelCase=[128, 192, 512, 1088]	,   UpperCAmelCase=[2, 6, 12, 2]	,   UpperCAmelCase=64	,   UpperCAmelCase="y"	,   UpperCAmelCase="relu"	,   **UpperCAmelCase	,   ):
							"""simple docstring"""







							super().__init__(**UpperCAmelCase   )
							if layer_type not in self.layer_types:
													raise ValueError(F"""layer_type={layer_type} is not one of {",".join(self.layer_types   )}"""   )
							_UpperCAmelCase     =      num_channels
							_UpperCAmelCase     =      embedding_size
							_UpperCAmelCase     =      hidden_sizes
							_UpperCAmelCase     =      depths
							_UpperCAmelCase     =      groups_width
							_UpperCAmelCase     =      layer_type
							_UpperCAmelCase     =      hidden_act
							# always downsample in the first stage
							_UpperCAmelCase     =      True
