docstr: Forward pass for generic convnet DNNs. Assumes activation names
  are valid pytorch activation names.
  :param input image tensor
docstr_tok: ["Forward","pass","for","generic","convnet","DNNs",".","Assumes","activation","names","are","valid","pytorch","activation","names",".",":","param","input","image","tensor"]
code: def forward(self, input) -> torch.FloatTensor:
      """Forward pass for generic convnet DNNs. Assumes activation names
      are valid pytorch activation names.
      :param input image tensor
      """
      x = self.conv_forward(input)
      x = x.view(-1, self.fc_input_dim)
      # pyre-fixme[7]: Expected `FloatTensor` but got `Tensor`.
      return self.feed_forward.forward(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 3 for calling the ConvolutionalNetwork obj's underlying member method code with example usage: obj.forward(input) and returns: self