in policy.py [0:0]
def dense(x, size, name, weight_init=None, bias=True):
w = tf.get_variable(name + "/w", [x.get_shape()[1], size], initializer=weight_init)
ret = tf.matmul(x, w)
if bias:
b = tf.get_variable(name + "/b", [size], initializer=tf.zeros_initializer())
return ret + b
else:
return ret