class_docstr: [`SpeechEncoderDecoderConfig`] is the configuration class to store the configuration of a
  [`SpeechEncoderDecoderModel`]. It is used to instantiate an Encoder Decoder model according to the specified
  arguments, defining the encoder and decoder configs.
  
  Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
  documentation from [`PretrainedConfig`] for more information.
  
  Args:
      kwargs (*optional*):
          Dictionary of keyword arguments. Notably:
  
              - **encoder** ([`PretrainedConfig`], *optional*) -- An instance of a configuration object that defines
                the encoder config.
              - **decoder** ([`PretrainedConfig`], *optional*) -- An instance of a configuration object that defines
                the decoder config.
  
  Examples:
  
  ```python
  >>> from transformers import BertConfig, Wav2Vec2Config, SpeechEncoderDecoderConfig, SpeechEncoderDecoderModel
  
  >>> # Initializing a Wav2Vec2 & BERT style configuration
  >>> config_encoder = Wav2Vec2Config()
  >>> config_decoder = BertConfig()
  
  >>> config = SpeechEncoderDecoderConfig.from_encoder_decoder_configs(config_encoder, config_decoder)
  
  >>> # Initializing a Wav2Vec2Bert model from a Wav2Vec2 & bert-base-uncased style configurations
  >>> model = SpeechEncoderDecoderModel(config=config)
  
  >>> # Accessing the model configuration
  >>> config_encoder = model.config.encoder
  >>> config_decoder = model.config.decoder
  >>> # set decoder config to causal lm
  >>> config_decoder.is_decoder = True
  >>> config_decoder.add_cross_attention = True
  
  >>> # Saving the model, including its configuration
  >>> model.save_pretrained("my-model")
  
  >>> # loading model and config from pretrained folder
  >>> encoder_decoder_config = SpeechEncoderDecoderConfig.from_pretrained("my-model")
  >>> model = SpeechEncoderDecoderModel.from_pretrained("my-model", config=encoder_decoder_config)
  ```
docstr: Instantiate a [`SpeechEncoderDecoderConfig`] (or a derived class) from a pre-trained encoder model
  configuration and decoder model configuration.
  
  Returns:
      [`SpeechEncoderDecoderConfig`]: An instance of a configuration object
code: def from_encoder_decoder_configs(
      cls,
      encoder_config: PretrainedConfig,
      decoder_config: PretrainedConfig,
      **kwargs,
  ) -> PretrainedConfig:
      r"""
      Instantiate a [`SpeechEncoderDecoderConfig`] (or a derived class) from a pre-trained encoder model
      configuration and decoder model configuration.
  
      Returns:
          [`SpeechEncoderDecoderConfig`]: An instance of a configuration object
      """
      logger.info(
          "Setting `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config"
      )
      decoder_config.is_decoder = True
      decoder_config.add_cross_attention = True
  
      return cls(
          encoder=encoder_config.to_dict(),
          decoder=decoder_config.to_dict(),
          **kwargs,
      )
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/src/transformers/models/speech_encoder_decoder/configuration_speech_encoder_decoder.py
imports: import copy
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  from ..auto.configuration_auto import AutoConfig
label_desc: Use image node_id 2 for calling the SpeechEncoderDecoderConfig obj's underlying member method code with example usage: obj.from_encoder_decoder_configs(cls, encoder_config, decoder_config) and returns: cls