code: def call(self, inputs, training=None):
      # [B, H, W, C] -> [B, num_patches, embed_dim]
      x = self.patch_embed(inputs)  # [B, 196, 768]
      x = self.cls_token_pos_embed(x)  # [B, 176, 768]
      x = self.pos_drop(x, training=training)
  
      for block in self.blocks:
          x = block(x, training=training)
  
      x = self.norm(x)
      x = self.pre_logits(x[:, 0])
      x = self.head(x)
  
      return x
  
imports: import tensorflow
  from tensorflow.keras import Model, layers, initializers
  import numpy
label_desc: Use image node_id 2 for calling the VisionTransformer obj's underlying member method code with example usage: obj.call(inputs, training) and returns: x