class_docstr: [`ClapConfig`] is the configuration class to store the configuration of a [`ClapModel`]. It is used to instantiate
  a CLAP model according to the specified arguments, defining the text model and audio model configs. Instantiating a
  configuration with the defaults will yield a similar configuration to that of the CLAP
  [laion/clap-htsat-fused](https://huggingface.co/laion/clap-htsat-fused) architecture.
  
  Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
  documentation from [`PretrainedConfig`] for more information.
  
  Args:
      text_config (`dict`, *optional*):
          Dictionary of configuration options used to initialize [`ClapTextConfig`].
      audio_config (`dict`, *optional*):
          Dictionary of configuration options used to initialize [`ClapAudioConfig`].
      logit_scale_init_value (`float`, *optional*, defaults to 14.29):
          The inital value of the *logit_scale* paramter. Default is used as per the original CLAP implementation.
      projection_dim (`int`, *optional*, defaults to 512):
          Dimentionality of text and audio projection layers.
      projection_hidden_act (`str`, *optional*, defaults to `"relu"`):
          Activation function for the projection layers.
      initializer_factor (`float`, *optional*, defaults to 1.0):
          Factor to scale the initialization of the model weights.
      kwargs (*optional*):
          Dictionary of keyword arguments.
  
  Example:
  
  ```python
  >>> from transformers import ClapConfig, ClapModel
  
  >>> # Initializing a ClapConfig with laion-ai/base style configuration
  >>> configuration = ClapConfig()
  
  >>> # Initializing a ClapModel (with random weights) from the laion-ai/base style configuration
  >>> model = ClapModel(configuration)
  
  >>> # Accessing the model configuration
  >>> configuration = model.config
  
  >>> # We can also initialize a ClapConfig from a ClapTextConfig and a ClapAudioConfig
  >>> from transformers import ClapTextConfig, ClapAudioConfig
  
  >>> # Initializing a ClapText and ClapAudioConfig configuration
  >>> config_text = ClapTextConfig()
  >>> config_audio = ClapAudioConfig()
  
  >>> config = ClapConfig.from_text_audio_configs(config_text, config_audio)
  ```
code: def __init__(
      self,
      text_config=None,
      audio_config=None,
      logit_scale_init_value=(1 / 0.07),
      projection_dim=512,
      projection_hidden_act="relu",
      initializer_factor=1.0,
      **kwargs,
  ):
      super().__init__(**kwargs)
  
      if text_config is None:
          text_config = {}
          logger.info(
              "text_config is None. Initializing the ClapTextConfig with default values."
          )
  
      if audio_config is None:
          audio_config = {}
          logger.info(
              "audio_config is None. initializing the ClapAudioConfig with default values."
          )
  
      self.text_config = ClapTextConfig(**text_config)
      self.audio_config = ClapAudioConfig(**audio_config)
      self.text_config.projection_dim = projection_dim
      self.audio_config.projection_dim = projection_dim
  
      self.text_config.projection_hidden_act = projection_hidden_act
      self.audio_config.projection_hidden_act = projection_hidden_act
  
      self.projection_dim = projection_dim
      self.projection_hidden_act = projection_hidden_act
      self.hidden_size = self.text_config.hidden_size
  
      self.logit_scale_init_value = logit_scale_init_value
      self.initializer_factor = initializer_factor
      self.num_hidden_layers = self.text_config.num_hidden_layers + len(
          self.audio_config.depths
      )
  
file_path: transformers/src/transformers/models/clap/configuration_clap.py
imports: import os
  from typing import Union
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
label_desc: Use image node_id 1 to create a new ClapConfig object from inherited base classes: PretrainedConfig with example: obj = ClapConfig(text_config, audio_config, logit_scale_init_value, projection_dim, projection_hidden_act, initializer_factor)