docstr: inputs : tensor
      Shape [None, 224, 224, 3], value range [0, 1].
docstr_tok: ["inputs",":","tensor","Shape","[","None",",","224",",","224",",","3","]",",","value","range","[","0",",","1","]","."]
code: def forward(self, inputs):
      """
      inputs : tensor
          Shape [None, 224, 224, 3], value range [0, 1].
      """
  
      inputs = inputs * 255 - np.array(
          [123.68, 116.779, 103.939], dtype=np.float32
      ).reshape([1, 1, 1, 3])
  
      out = self.layers.forward(inputs)
      return out
  
file_path: TensorLayer/tensorlayer/models/vgg.py
imports: import os
  import numpy
  import tensorflow
  import tensorlayer
  from tensorlayer import logging
  from tensorlayer.files import assign_weights, maybe_download_and_extract
  from tensorlayer.layers import BatchNorm, Conv2d, Dense, Flatten, Input, Lambda, LayerList, MaxPool2d
  from tensorlayer.models import Model
label_desc: Use image node_id 2 for calling the VGG obj's underlying member method code with example usage: obj.forward(inputs) and returns: out