
'''simple docstring'''







import copy
from typing import Dict

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


_lowercase					:    str       				=			logging.get_logger(__name__)






class 					lowerCAmelCase__  (    lowerCamelCase_	):
					lowerCAmelCase_	  =	'''semantic'''






					def __init__(  self							,				__SCREAMING_SNAKE_CASE=1_00_00							,				__SCREAMING_SNAKE_CASE=True							,				__SCREAMING_SNAKE_CASE=7_68							,				__SCREAMING_SNAKE_CASE=False							,				__SCREAMING_SNAKE_CASE=False							,				__SCREAMING_SNAKE_CASE=False							,				__SCREAMING_SNAKE_CASE=False							,				__SCREAMING_SNAKE_CASE=0.7							,				__SCREAMING_SNAKE_CASE=True							,				__SCREAMING_SNAKE_CASE=1_00_48							,				__SCREAMING_SNAKE_CASE=12_95_95							,				__SCREAMING_SNAKE_CASE=12_95_99							,				__SCREAMING_SNAKE_CASE=1_00_00							,				__SCREAMING_SNAKE_CASE=2_56							,				__SCREAMING_SNAKE_CASE=49.9							,				**__SCREAMING_SNAKE_CASE							,				):


											"""simple docstring"""





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

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







class 					lowerCAmelCase__  (    lowerCamelCase_	):
					lowerCAmelCase_	  =	'''coarse_acoustics'''






					def __init__(  self							,				__SCREAMING_SNAKE_CASE=True							,				__SCREAMING_SNAKE_CASE=False							,				__SCREAMING_SNAKE_CASE=False							,				__SCREAMING_SNAKE_CASE=False							,				__SCREAMING_SNAKE_CASE=False							,				__SCREAMING_SNAKE_CASE=0.7							,				__SCREAMING_SNAKE_CASE=True							,				__SCREAMING_SNAKE_CASE=1_20_48							,				__SCREAMING_SNAKE_CASE=75							,				__SCREAMING_SNAKE_CASE=2							,				__SCREAMING_SNAKE_CASE=1_20_50							,				__SCREAMING_SNAKE_CASE=2_56							,				__SCREAMING_SNAKE_CASE = 6_30							,				__SCREAMING_SNAKE_CASE = 60							,				**__SCREAMING_SNAKE_CASE							,				):


											"""simple docstring"""





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

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







class 					lowerCAmelCase__  (    lowerCamelCase_	):
					lowerCAmelCase_	  =	'''fine_acoustics'''






					def __init__(  self							,				__SCREAMING_SNAKE_CASE=0.5							,				__SCREAMING_SNAKE_CASE=5_12							,				__SCREAMING_SNAKE_CASE=10_24							,				__SCREAMING_SNAKE_CASE=8							,				**__SCREAMING_SNAKE_CASE							,				):


											"""simple docstring"""





											super().__init__(temperature=__snake_case						)

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







class 					lowerCAmelCase__  (    lowerCamelCase_	):
					lowerCAmelCase_	  =	'''bark'''
					lowerCAmelCase_	  =	True






					def __init__(  self							,				__SCREAMING_SNAKE_CASE = None							,				__SCREAMING_SNAKE_CASE = None							,				__SCREAMING_SNAKE_CASE = None							,				__SCREAMING_SNAKE_CASE=2_40_00							,				__SCREAMING_SNAKE_CASE=10_24							,				**__SCREAMING_SNAKE_CASE							,				):


											"""simple docstring"""





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

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

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

											lowercase_      :	Tuple						=			BarkSemanticGenerationConfig(**__snake_case						)
											lowercase_      :	Tuple						=			BarkCoarseGenerationConfig(**__snake_case						)
											lowercase_      :	Union[str, Any]						=			BarkFineGenerationConfig(**__snake_case						)

											lowercase_      :	Optional[Any]						=			sample_rate
											lowercase_      :	Optional[Any]						=			codebook_size






					@classmethod
					def       _snake_case       (  cls							,				__SCREAMING_SNAKE_CASE							,				__SCREAMING_SNAKE_CASE							,				__SCREAMING_SNAKE_CASE							,				**__SCREAMING_SNAKE_CASE							,				):


											"""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()							,				**__snake_case							,				)






					def       _snake_case       (  self						):


											"""simple docstring"""





											lowercase_      :	List[str]						=			copy.deepcopy(self.__dict__						)

											lowercase_      :	Optional[Any]						=			self.semantic_config.to_dict()
											lowercase_      :	Tuple						=			self.coarse_acoustics_config.to_dict()
											lowercase_      :	int						=			self.fine_acoustics_config.to_dict()

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





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


snake_case_      :					Any				      =     {
    'configuration_imagegpt': ['IMAGEGPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ImageGPTConfig', 'ImageGPTOnnxConfig']
}

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	snake_case_      :					str				      =     ['ImageGPTFeatureExtractor']
	snake_case_      :					Optional[int]				      =     ['ImageGPTImageProcessor']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	snake_case_      :					List[str]				      =     [
	    'IMAGEGPT_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'ImageGPTForCausalImageModeling',
	    'ImageGPTForImageClassification',
	    'ImageGPTModel',
	    'ImageGPTPreTrainedModel',
	    'load_tf_weights_in_imagegpt',
	]


if TYPE_CHECKING:
	from .configuration_imagegpt import IMAGEGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, ImageGPTConfig, ImageGPTOnnxConfig

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .feature_extraction_imagegpt import ImageGPTFeatureExtractor
		from .image_processing_imagegpt import ImageGPTImageProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_imagegpt import (
		    IMAGEGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    ImageGPTForCausalImageModeling,
		    ImageGPTForImageClassification,
		    ImageGPTModel,
		    ImageGPTPreTrainedModel,
		    load_tf_weights_in_imagegpt,
		)

else:
	import sys

	snake_case_      :					Dict				      =     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
