class_docstr: FeedForward controller module.
  
  
  Single feedforward linear layer, wrapped as an RNN core for convenience. There
  is no computation performed on the state.
  
      y <- activation(linear(x))
      s_t+1 <- s_t
class_docstr_tok: ["FeedForward","controller","module",".","Single","feedforward","linear","layer",",","wrapped","as","an","RNN","core","for","convenience",".","There","is","no","computation","performed","on","the","state",".","y","<","-","activation","(","linear","(","x",")",")","s_t+1","<","-","s_t"]
docstr: Connects the FeedForward controller to the graph.
  
  Args:
    inputs: 2D Tensor [batch_size, input_size] input_size needs to be
      specified at construction time.
    prev_state: dummy state, 2D tensor of size [batch_size, 1]
  
  Returns:
    output: 2D Tensor [batch_size, hidden_size].
    next_state: the same dummy state passed in as an argument.
docstr_tok: ["Connects","the","FeedForward","controller","to","the","graph",".","Args",":","inputs",":","2D","Tensor","[","batch_size",",","input_size","]","input_size","needs","to","be","specified","at","construction","time",".","prev_state",":","dummy","state",",","2D","tensor","of","size","[","batch_size",",","1","]","Returns",":","output",":","2D","Tensor","[","batch_size",",","hidden_size","]",".","next_state",":","the","same","dummy","state","passed","in","as","an","argument","."]
code: def __call__(self, inputs, prev_state):
      """Connects the FeedForward controller to the graph.
  
      Args:
        inputs: 2D Tensor [batch_size, input_size] input_size needs to be
          specified at construction time.
        prev_state: dummy state, 2D tensor of size [batch_size, 1]
  
      Returns:
        output: 2D Tensor [batch_size, hidden_size].
        next_state: the same dummy state passed in as an argument.
      """
      output = self.linear(inputs)
      if self._activation is not None:
          output = self._activation(output)
      return output, prev_state
  
file_path: sonnet/sonnet/src/nets/dnc/control.py
imports: import sys
  from sonnet.src import linear
  from sonnet.src import recurrent
  import tensorflow
label_desc: Use image node_id 2 for calling the FeedForward obj's underlying member method code with example usage: obj.__call__(inputs, prev_state) and returns: output,  prev_state