code: def forward(self, x):
      x = self.conv(x)
      x = self.activation(x)
      x = self.max_pool(x)
      x = self.flatten(x)
      x = self.dense(x)
      x = self.softmax(x)
      return x
  
file_path: keras/benchmarks/torch_ctl_benchmark/conv_model_benchmark.py
imports: import numpy
  import torch
  import torch.nn
  import torch.optim
  import keras
  from benchmarks.torch_ctl_benchmark.benchmark_utils import train_loop
  from keras import layers
label_desc: Use image node_id 2 for calling the TorchModel obj's underlying member method code with example usage: obj.forward(x) and returns: x