class_docstr: Vgg16 implementation.
class_docstr_tok: ["Vgg16","implementation","."]
docstr: Process input.
code: def forward(self, x: Tensor) -> NamedTuple:
      """Process input."""
      h = self.slice1(x)
      h_relu1_2 = h
      h = self.slice2(h)
      h_relu2_2 = h
      h = self.slice3(h)
      h_relu3_3 = h
      h = self.slice4(h)
      h_relu4_3 = h
      h = self.slice5(h)
      h_relu5_3 = h
  
      class _VGGOutputs(NamedTuple):
          relu1_2: Tensor
          relu2_2: Tensor
          relu3_3: Tensor
          relu4_3: Tensor
          relu5_3: Tensor
  
      return _VGGOutputs(
          h_relu1_2, h_relu2_2, h_relu3_3, h_relu4_3, h_relu5_3
      )
  
imports: import inspect
  import os
  from typing import List, NamedTuple, Optional, Tuple, Union
  import torch
  from torch import Tensor, nn
  from typing_extensions import Literal
  from torchmetrics.utilities.imports import _TORCHVISION_AVAILABLE, _TORCHVISION_GREATER_EQUAL_0_13
label_desc: Use image node_id 2 for calling the Vgg16 obj's underlying member method code with example usage: obj.forward(x) and returns: _VGGOutputs