





'''simple docstring'''







import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig


lowercase			:      List[str]			=					logging.get_logger(__name__)

lowercase			:      Any			=					{
    """facebook/musicgen-small""": """https://huggingface.co/facebook/musicgen-small/resolve/main/config.json""",
    # See all Musicgen models at https://huggingface.co/models?filter=musicgen
}







class 				_a   (snake_case__  ):





     '''simple docstring'''



     lowerCAmelCase_     :    Optional[Any]									=				'musicgen_decoder'
     lowerCAmelCase_     :    Any									=				['past_key_values']







     def __init__(							self       ,__a=2_048       ,__a=2_048       ,__a=24       ,__a=4_096       ,__a=16       ,__a=0.0       ,__a=True       ,__a="gelu"       ,__a=1_024       ,__a=0.1       ,__a=0.0       ,__a=0.0       ,__a=0.02       ,__a=False       ,__a=4       ,__a=2_048       ,__a=2_048       ,__a=None       ,__a=False       ,**__a       ,)			->							Optional[int]:
          snake_case :			List[Any]					   = vocab_size
          snake_case :			str					   = max_position_embeddings
          snake_case :			Optional[Any]					   = hidden_size
          snake_case :			str					   = ffn_dim
          snake_case :			int					   = num_hidden_layers
          snake_case :			Union[str, Any]					   = num_attention_heads
          snake_case :			List[str]					   = dropout
          snake_case :			List[str]					   = attention_dropout
          snake_case :			Optional[int]					   = activation_dropout
          snake_case :			Dict					   = activation_function
          snake_case :			Optional[int]					   = initializer_factor
          snake_case :			Union[str, Any]					   = layerdrop
          snake_case :			List[Any]					   = use_cache
          snake_case :			List[Any]					   = scale_embedding  # scale factor will be sqrt(d_model) if True
          snake_case :			List[str]					   = num_codebooks
          super().__init__(
              pad_token_id=__a       ,bos_token_id=__a       ,eos_token_id=__a       ,tie_word_embeddings=__a       ,**__a       ,)







class 				_a   (snake_case__  ):





     '''simple docstring'''



     lowerCAmelCase_     :    Tuple									=				'musicgen'
     lowerCAmelCase_     :    int									=				True







     def __init__(							self       ,**__a       )			->							Optional[Any]:
          super().__init__(**__a       )
          if "text_encoder" not in kwargs or "audio_encoder" not in kwargs or "decoder" not in kwargs:
               raise ValueError("""Config has to be initialized with text_encoder, audio_encoder and decoder config"""       )

          snake_case :			List[Any]					   = kwargs.pop("""text_encoder"""       )
          snake_case :			Any					   = text_encoder_config.pop("""model_type"""       )

          snake_case :			Optional[int]					   = kwargs.pop("""audio_encoder"""       )
          snake_case :			str					   = audio_encoder_config.pop("""model_type"""       )

          snake_case :			List[str]					   = kwargs.pop("""decoder"""       )

          snake_case :			int					   = AutoConfig.for_model(__a       ,**__a       )
          snake_case :			Dict					   = AutoConfig.for_model(__a       ,**__a       )
          snake_case :			Dict					   = MusicgenDecoderConfig(**__a       )
          snake_case :			Optional[Any]					   = True







     @classmethod
     def  snake_case_			(							cls       ,__a       ,__a       ,__a       ,**__a       ,)			->							List[Any]:
          return cls(
              text_encoder=text_encoder_config.to_dict()       ,audio_encoder=audio_encoder_config.to_dict()       ,decoder=decoder_config.to_dict()       ,**__a       ,)







     def  snake_case_			(							self       )			->							Optional[int]:
          snake_case :			Tuple					   = copy.deepcopy(self.__dict__       )
          snake_case :			List[Any]					   = self.text_encoder.to_dict()
          snake_case :			Union[str, Any]					   = self.audio_encoder.to_dict()
          snake_case :			Any					   = self.decoder.to_dict()
          snake_case :			Any					   = self.__class__.model_type
          return output









'''simple docstring'''







from typing import TYPE_CHECKING

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


lowercase			:      Tuple			=					{"""configuration_bert_generation""": ["""BertGenerationConfig"""]}

try:
      if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase			:      Tuple			=					["""BertGenerationTokenizer"""]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase			:      List[Any]			=					[
          """BertGenerationDecoder""",
          """BertGenerationEncoder""",
          """BertGenerationPreTrainedModel""",
          """load_tf_weights_in_bert_generation""",
      ]


if TYPE_CHECKING:
      from .configuration_bert_generation import BertGenerationConfig

      try:
            if not is_sentencepiece_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_bert_generation import BertGenerationTokenizer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_bert_generation import (
                BertGenerationDecoder,
                BertGenerationEncoder,
                BertGenerationPreTrainedModel,
                load_tf_weights_in_bert_generation,
            )

else:
      import sys

      lowercase			:      Optional[Any]			=					_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



