class_docstr: Simple wrapper for ClassyVision Vision Transformer model.
  This model is defined on the fly from a Vision Transformer base class and
  a configuration file.
code: def __init__(self, model_config: AttrDict, model_name: str):
      super().__init__()
      self.model_config = model_config
  
      assert model_config.INPUT_TYPE in [
          "rgb",
          "bgr",
      ], "Input type not supported"
      trunk_config = copy.deepcopy(
          model_config.TRUNK.VISION_TRANSFORMERS
      )
  
      logging.info(
          "Building model: Vision Transformer from yaml config"
      )
      trunk_config = AttrDict(
          {k.lower(): v for k, v in trunk_config.items()}
      )
  
      self.model = ClassyVisionTransformer(
          image_size=trunk_config.image_size,
          patch_size=trunk_config.patch_size,
          num_layers=trunk_config.num_layers,
          num_heads=trunk_config.num_heads,
          hidden_dim=trunk_config.hidden_dim,
          mlp_dim=trunk_config.mlp_dim,
          dropout_rate=trunk_config.dropout_rate,
          attention_dropout_rate=trunk_config.attention_dropout_rate,
          classifier=trunk_config.classifier,
      )
  
file_path: vissl/vissl/models/trunks/classy_vision_transformer.py
imports: import copy
  import logging
  from typing import List
  import torch
  import torch.nn
  from classy_vision.models import VisionTransformer
  from vissl.config import AttrDict
  from vissl.models.trunks import register_model_trunk
label_desc: Use image node_id 1 to create a new ClassyViT object from inherited base classes: nn with example: obj = ClassyViT(model_config, model_name)