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"]
code: def initial_state(self, batch_size):
      return tf.zeros([batch_size, 1], dtype=self.dtype)
  
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 3 for calling the FeedForward obj's underlying member method code with example usage: obj.initial_state(batch_size) and returns: tf