code: def conv_forward(self, input):
      x = input
      for i, _ in enumerate(self.conv_layers):
          x = self.conv_layers[i](x)
          if self.use_layer_norm:
              x = self.layer_norm_layers[i](x)
          x = F.relu(x)
          x = self.pool_layers[i](x)
      return x
  
file_path: ReAgent/reagent/models/convolutional_network.py
imports: import collections
  import logging
  import math
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.nn.init
  from reagent.models.fully_connected_network import FullyConnectedNetwork
label_desc: Use image node_id 2 for calling the ConvolutionalNetwork obj's underlying member method code with example usage: obj.conv_forward(input) and returns: x