class_docstr: Small CNN module proposed for DQN in NeurIPS DL Workshop, 2013.
  
  See: https://arxiv.org/abs/1312.5602
class_docstr_tok: ["Small","CNN","module","proposed","for","DQN","in","NeurIPS","DL","Workshop",",","2013",".","See",":","https",":","\/\/arxiv.org\/abs\/1312.5602"]
code: def forward(self, state):
      h = state
      for layer in self.layers:
          h = self.activation(layer(h))
      h_flat = h.view(h.size(0), -1)
      return self.activation(self.output(h_flat))
  
file_path: pfrl/pfrl/nn/atari_cnn.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  from pfrl.initializers import init_chainer_default
label_desc: Use image node_id 2 for calling the SmallAtariCNN obj's underlying member method code with example usage: obj.forward(state) and returns: self