






import copy

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


a	: Any      =				logging.get_logger(__name__)

a	: 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					(				lowercase__     ):



      """simple docstring"""


      a						:				List[str]							 =			'musicgen_decoder'
      a						:				List[str]							 =			['past_key_values']
      def __init__(   self      :    List[Any]	,   __lowercase      :    List[str]=2048	,   __lowercase      :    Dict=2048	,   __lowercase      :    str=24	,   __lowercase      :    Tuple=4096	,   __lowercase      :    Tuple=16	,   __lowercase      :    Optional[Any]=0.0	,   __lowercase      :    Union[str, Any]=True	,   __lowercase      :    Tuple="gelu"	,   __lowercase      :    List[str]=1024	,   __lowercase      :    str=0.1	,   __lowercase      :    Union[str, Any]=0.0	,   __lowercase      :    List[str]=0.0	,   __lowercase      :    int=0.02	,   __lowercase      :    Optional[int]=False	,   __lowercase      :    List[str]=4	,   __lowercase      :    Tuple=2048	,   __lowercase      :    Dict=2048	,   __lowercase      :    Any=None	,   __lowercase      :    Any=False	,   **__lowercase      :    Dict	,   )							->   Optional[Any]:
        __UpperCAmelCase							:			Union[str, Any]     =						vocab_size
        __UpperCAmelCase							:			Dict     =						max_position_embeddings
        __UpperCAmelCase							:			int     =						hidden_size
        __UpperCAmelCase							:			Any     =						ffn_dim
        __UpperCAmelCase							:			Any     =						num_hidden_layers
        __UpperCAmelCase							:			List[Any]     =						num_attention_heads
        __UpperCAmelCase							:			Tuple     =						dropout
        __UpperCAmelCase							:			Union[str, Any]     =						attention_dropout
        __UpperCAmelCase							:			Optional[Any]     =						activation_dropout
        __UpperCAmelCase							:			Union[str, Any]     =						activation_function
        __UpperCAmelCase							:			List[Any]     =						initializer_factor
        __UpperCAmelCase							:			Tuple     =						layerdrop
        __UpperCAmelCase							:			Dict     =						use_cache
        __UpperCAmelCase							:			Any     =						scale_embedding  # scale factor will be sqrt(d_model) if True
        __UpperCAmelCase							:			str     =						num_codebooks
        super().__init__(
            pad_token_id=__lowerCamelCase	,   bos_token_id=__lowerCamelCase	,   eos_token_id=__lowerCamelCase	,   tie_word_embeddings=__lowerCamelCase	,   **__lowerCamelCase	,   )


class 					a					(				lowercase__     ):



      """simple docstring"""


      a						:				Optional[Any]							 =			'musicgen'
      a						:				List[Any]							 =			True
      def __init__(   self      :    Any	,   **__lowercase      :    List[str]      )							->   List[str]:
        super().__init__(**__lowerCamelCase      )
        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"""      )

        __UpperCAmelCase							:			int     =						kwargs.pop("""text_encoder"""      )
        __UpperCAmelCase							:			Optional[Any]     =						text_encoder_config.pop("""model_type"""      )

        __UpperCAmelCase							:			Dict     =						kwargs.pop("""audio_encoder"""      )
        __UpperCAmelCase							:			Tuple     =						audio_encoder_config.pop("""model_type"""      )

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

        __UpperCAmelCase							:			List[Any]     =						AutoConfig.for_model(__lowerCamelCase	,   **__lowerCamelCase      )
        __UpperCAmelCase							:			Union[str, Any]     =						AutoConfig.for_model(__lowerCamelCase	,   **__lowerCamelCase      )
        __UpperCAmelCase							:			Optional[int]     =						MusicgenDecoderConfig(**__lowerCamelCase      )
        __UpperCAmelCase							:			List[Any]     =						True
      @classmethod
      def 			UpperCAmelCase   (   cls      :    str	,   __lowercase      :    Union[str, Any]	,   __lowercase      :    Optional[int]	,   __lowercase      :    Optional[int]	,   **__lowercase      :    Dict	,   )							->   str:
        return cls(
            text_encoder=text_encoder_config.to_dict()	,   audio_encoder=audio_encoder_config.to_dict()	,   decoder=decoder_config.to_dict()	,   **__lowerCamelCase	,   )




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










from typing import TYPE_CHECKING

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


a	: Optional[int]      =				{
    "configuration_deformable_detr": ["DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP", "DeformableDetrConfig"],
}

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a	: Optional[int]      =				["DeformableDetrFeatureExtractor"]
       a	: List[str]      =				["DeformableDetrImageProcessor"]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a	: List[Any]      =				[
           "DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST",
           "DeformableDetrForObjectDetection",
           "DeformableDetrModel",
           "DeformableDetrPreTrainedModel",
       ]


if TYPE_CHECKING:
       from .configuration_deformable_detr import DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, DeformableDetrConfig

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .feature_extraction_deformable_detr import DeformableDetrFeatureExtractor
              from .image_processing_deformable_detr import DeformableDetrImageProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_deformable_detr import (
                  DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
                  DeformableDetrForObjectDetection,
                  DeformableDetrModel,
                  DeformableDetrPreTrainedModel,
              )

else:
       import sys

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


