Add policy gradient example. (#344)

* add policy gradient example

* fix typos

* Minor changes plus some documentation.

* Minor fixes.

examples/policy_gradient/tests/test.py

@@ -0,0 +1,58 @@
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import unittest
+import numpy as np
+import tensorflow as tf
+from numpy.testing import assert_allclose
+
+from reinforce.distributions import Categorical
+from reinforce.utils import flatten, concatenate
+
+class DistibutionsTest(unittest.TestCase):
+
+  def testCategorical(self):
+    num_samples = 100000
+    logits = tf.placeholder(tf.float32, shape=(None, 10))
+    z = 8 * (np.random.rand(10) - 0.5)
+    data = np.tile(z, (num_samples, 1))
+    c = Categorical(logits)
+    sample_op = c.sample()
+    sess = tf.Session()
+    sess.run(tf.global_variables_initializer())
+    samples = sess.run(sample_op, feed_dict={logits: data})
+    counts = np.zeros(10)
+    for sample in samples:
+      counts[sample] += 1.0
+    probs = np.exp(z) / np.sum(np.exp(z))
+    self.assertTrue(np.sum(np.abs(probs - counts / num_samples)) <= 0.01)
+
+class UtilsTest(unittest.TestCase):
+
+  def testFlatten(self):
+    d = {"s": np.array([[[1, -1], [2, -2]], [[3, -3], [4, -4]]]),
+         "a": np.array([[[5], [-5]], [[6], [-6]]])}
+    flat = flatten(d.copy(), start=0, stop=2)
+    assert_allclose(d["s"][0][0][:], flat["s"][0][:])
+    assert_allclose(d["s"][0][1][:], flat["s"][1][:])
+    assert_allclose(d["s"][1][0][:], flat["s"][2][:])
+    assert_allclose(d["s"][1][1][:], flat["s"][3][:])
+    assert_allclose(d["a"][0][0], flat["a"][0])
+    assert_allclose(d["a"][0][1], flat["a"][1])
+    assert_allclose(d["a"][1][0], flat["a"][2])
+    assert_allclose(d["a"][1][1], flat["a"][3])
+
+  def testConcatenate(self):
+    d1 = {"s": np.array([0, 1]), "a": np.array([2, 3])}
+    d2 = {"s": np.array([4, 5]), "a": np.array([6, 7])}
+    d = concatenate([d1, d2])
+    assert_allclose(d["s"], np.array([0, 1, 4, 5]))
+    assert_allclose(d["a"], np.array([2, 3, 6, 7]))
+
+    D = concatenate([d])
+    assert_allclose(D["s"], np.array([0, 1, 4, 5]))
+    assert_allclose(D["a"], np.array([2, 3, 6, 7]))
+
+if __name__ == "__main__":
+  unittest.main(verbosity=2)