--- a
+++ b/A3C/test.py
@@ -0,0 +1,14 @@
+import tensorflow as tf
+import numpy as np
+
+x = tf.placeholder(tf.float32, [batch_size, 10, 16])
+
+with tf.Session() as sess:
+    mu = tf.placeholder(shape=[3],dtype=tf.float32)
+    var = tf.placeholder(shape=[3],dtype=tf.float32)
+    normal = tf.distributions.Normal(mu,tf.sqrt(var))
+    act = tf.placeholder(shape=[3],dtype=tf.float32)
+    log_prob = normal.log_prob(act)
+    entropy = normal.entropy()
+    feed_dict={mu:np.zeros(3),var:np.ones(3)*20,act:np.array([0,-0.5,1])}
+    print sess.run([log_prob,entropy],feed_dict=feed_dict)