e2c_seq.py 文件源码

def transition(h,share=None):
  # compute A,B,o linearization matrices
  with tf.variable_scope("trans",reuse=share):
    for l in range(2):
      h=ReLU(h,100,"aggregate_loss"+str(l))
    with tf.variable_scope("A"):
      v,r=tf.split(1,2,linear(h,z_dim*2))
      v1=tf.expand_dims(v,-1) # (batch, z_dim, 1)
      rT=tf.expand_dims(r,1) # batch, 1, z_dim
      I=tf.diag([1.]*z_dim)
      A=(I+tf.batch_matmul(v1,rT)) # (z_dim, z_dim) + (batch, z_dim, 1)*(batch, 1, z_dim) (I is broadcasted) 
    with tf.variable_scope("B"):
      B=linear(h,z_dim*u_dim)
      B=tf.reshape(B,[-1,z_dim,u_dim])
    with tf.variable_scope("o"):
      o=linear(h,z_dim)
    return A,B,o,v,r