
'''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=__SCREAMING_SNAKE_CASE							,				do_sample=__SCREAMING_SNAKE_CASE							,				eos_token_id=__SCREAMING_SNAKE_CASE							,				renormalize_logits=__SCREAMING_SNAKE_CASE							,				max_new_tokens=__SCREAMING_SNAKE_CASE							,				output_scores=__SCREAMING_SNAKE_CASE							,				return_dict_in_generate=__SCREAMING_SNAKE_CASE							,				output_hidden_states=__SCREAMING_SNAKE_CASE							,				output_attentions=__SCREAMING_SNAKE_CASE							,				**__SCREAMING_SNAKE_CASE							,				)

											lowercase_      :	str						=			text_encoding_offset
											lowercase_      :	str						=			text_pad_token
											lowercase_      :	Tuple						=			eos_token_id
											lowercase_      :	Any						=			semantic_infer_token
											lowercase_      :	Tuple						=			semantic_vocab_size
											lowercase_      :	Union[str, Any]						=			max_input_semantic_length
											lowercase_      :	Dict						=			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=__SCREAMING_SNAKE_CASE							,				do_sample=__SCREAMING_SNAKE_CASE							,				renormalize_logits=__SCREAMING_SNAKE_CASE							,				output_scores=__SCREAMING_SNAKE_CASE							,				return_dict_in_generate=__SCREAMING_SNAKE_CASE							,				output_hidden_states=__SCREAMING_SNAKE_CASE							,				output_attentions=__SCREAMING_SNAKE_CASE							,				**__SCREAMING_SNAKE_CASE							,				)

											lowercase_      :	List[str]						=			coarse_semantic_pad_token
											lowercase_      :	List[Any]						=			coarse_rate_hz
											lowercase_      :	Union[str, Any]						=			n_coarse_codebooks
											lowercase_      :	Dict						=			coarse_infer_token
											lowercase_      :	str						=			max_coarse_input_length
											lowercase_      :	List[str]						=			max_coarse_history
											lowercase_      :	int						=			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=__SCREAMING_SNAKE_CASE						)

											lowercase_      :	Any						=			max_fine_history_length
											lowercase_      :	Union[str, Any]						=			max_fine_input_length
											lowercase_      :	List[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_      :	Optional[int]						=			{}
																	logger.info('''coarse_acoustics_config is None. initializing the coarse model with default values.'''						)

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

											lowercase_      :	Optional[Any]						=			BarkSemanticGenerationConfig(**__SCREAMING_SNAKE_CASE						)
											lowercase_      :	int						=			BarkCoarseGenerationConfig(**__SCREAMING_SNAKE_CASE						)
											lowercase_      :	List[Any]						=			BarkFineGenerationConfig(**__SCREAMING_SNAKE_CASE						)

											lowercase_      :	str						=			sample_rate
											lowercase_      :	Tuple						=			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()							,				**__SCREAMING_SNAKE_CASE							,				)






					def       _snake_case       (  self						):


											"""simple docstring"""





											lowercase_      :	Dict						=			copy.deepcopy(self.__dict__						)

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

											lowercase_      :	int						=			self.__class__.model_type
											return output





'''simple docstring'''







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






class 					lowerCAmelCase__  (    lowerCamelCase_	):
					lowerCAmelCase_	  =	['''image_processor''', '''tokenizer''']
					lowerCAmelCase_	  =	'''EfficientNetImageProcessor'''
					lowerCAmelCase_	  =	('''BertTokenizer''', '''BertTokenizerFast''')






					def __init__(  self							,				__SCREAMING_SNAKE_CASE							,				__SCREAMING_SNAKE_CASE						):


											"""simple docstring"""





											super().__init__(__SCREAMING_SNAKE_CASE							,				__SCREAMING_SNAKE_CASE						)






					def __call__(  self							,				__SCREAMING_SNAKE_CASE=None							,				__SCREAMING_SNAKE_CASE=None							,				__SCREAMING_SNAKE_CASE="max_length"							,				__SCREAMING_SNAKE_CASE=64							,				__SCREAMING_SNAKE_CASE=None							,				**__SCREAMING_SNAKE_CASE						):


											"""simple docstring"""





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

											if text is not None:
																	lowercase_      :	str						=			self.tokenizer(
																	    __SCREAMING_SNAKE_CASE							,				padding=__SCREAMING_SNAKE_CASE							,				max_length=__SCREAMING_SNAKE_CASE							,				return_tensors=__SCREAMING_SNAKE_CASE							,				**__SCREAMING_SNAKE_CASE						)

											if images is not None:
																	lowercase_      :	int						=			self.image_processor(__SCREAMING_SNAKE_CASE							,				return_tensors=__SCREAMING_SNAKE_CASE							,				**__SCREAMING_SNAKE_CASE						)

											if text is not None and images is not None:
																	lowercase_      :	Any						=			image_features.pixel_values
																	return encoding
											elif text is not None:
																	return encoding
											else:
																	return BatchEncoding(data=dict(**__SCREAMING_SNAKE_CASE						)							,				tensor_type=__SCREAMING_SNAKE_CASE						)






					def       _snake_case       (  self							,				*__SCREAMING_SNAKE_CASE							,				**__SCREAMING_SNAKE_CASE						):


											"""simple docstring"""





											return self.tokenizer.batch_decode(*__SCREAMING_SNAKE_CASE							,				**__SCREAMING_SNAKE_CASE						)






					def       _snake_case       (  self							,				*__SCREAMING_SNAKE_CASE							,				**__SCREAMING_SNAKE_CASE						):


											"""simple docstring"""





											return self.tokenizer.decode(*__SCREAMING_SNAKE_CASE							,				**__SCREAMING_SNAKE_CASE						)






					@property
					def       _snake_case       (  self						):


											"""simple docstring"""





											lowercase_      :	Dict						=			self.tokenizer.model_input_names
											lowercase_      :	Optional[int]						=			self.image_processor.model_input_names
											return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names						)						)



