class_docstr: This is the configuration class to store the vision configuration of a [`BridgeTowerModel`]. Instantiating a
  configuration with the defaults will yield a similar configuration to that of the bridgetower-base
  [BridgeTower/bridgetower-base](https://huggingface.co/BridgeTower/bridgetower-base/) architecture.
  
  Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
  documentation from [`PretrainedConfig`] for more information.
  
  Args:
      hidden_size (`int`, *optional*, defaults to 768):
          Dimensionality of the encoder layers and the pooler layer.
      num_hidden_layers (`int`, *optional*, defaults to 12):
          Number of hidden layers in visual encoder model.
      patch_size (`int`, *optional*, defaults to 16):
          The size (resolution) of each patch.
      image_size (`int`, *optional*, defaults to 288):
          The size (resolution) of each image.
      initializer_factor (`float`, *optional*, defaults to 1):
          A factor for initializing all weight matrices (should be kept to 1, used internally for initialization
          testing).
      layer_norm_eps (`float`, *optional*, defaults to 1e-05):
          The epsilon used by the layer normalization layers.
      stop_gradient (`bool`, *optional*, defaults to `False`):
          Whether to stop gradient for training.
      share_layernorm (`bool`, *optional*, defaults to `True`):
          Whether LayerNorm layers are shared.
      remove_last_layer (`bool`, *optional*, defaults to `False`):
          Whether to remove the last layer from the vision encoder.
  
  
  Example:
  
  ```python
  >>> from transformers import BridgeTowerVisionConfig
  
  >>> # Initializing a BridgeTower BridgeTower/bridgetower-base style configuration for the vision model
  >>> configuration = BridgeTowerVisionConfig()
  
  >>> # Accessing the configuration
  >>> configuration
  ```
code: def __init__(
      self,
      hidden_size=768,
      num_hidden_layers=12,
      num_channels=3,
      patch_size=16,
      image_size=288,
      initializer_factor=1,
      layer_norm_eps=1e-05,
      stop_gradient=False,
      share_layernorm=True,
      remove_last_layer=False,
      **kwargs,
  ):
      super().__init__(**kwargs)
      self.hidden_size = hidden_size
      self.num_hidden_layers = num_hidden_layers
      self.num_channels = num_channels
      self.patch_size = patch_size
      self.image_size = image_size
      self.initializer_factor = initializer_factor
      self.layer_norm_eps = layer_norm_eps
      self.stop_gradient = stop_gradient
      self.share_layernorm = share_layernorm
      self.remove_last_layer = remove_last_layer
  
file_path: transformers/src/transformers/models/bridgetower/configuration_bridgetower.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 BridgeTowerVisionConfig object from inherited base classes: PretrainedConfig with example: obj = BridgeTowerVisionConfig(hidden_size, num_hidden_layers, num_channels, patch_size, image_size, initializer_factor, layer_norm_eps, stop_gradient, share_layernorm, remove_last_layer)