BUGFIX: Call n = convert_to_tensor(n).

Exponential.sample forgot to call n = convert_to_tensor(n), and
tensor_util.constant_value(n) only works with n a Tensor.
Change: 123248349

tensorflow/contrib/distributions/python/kernel_tests/exponential_test.py

@@ -105,10 +105,9 @@ class ExponentialTest(tf.test.TestCase):
 
       exponential = tf.contrib.distributions.Exponential(lam=lam)
 
-      n_v = 100000
-      n = tf.constant(n_v)
+      n = 100000
       samples = exponential.sample(n, seed=138)
-      self.assertEqual(samples.get_shape(), (n_v, batch_size, 2))
+      self.assertEqual(samples.get_shape(), (n, batch_size, 2))
 
       sample_values = samples.eval()
 

tensorflow/contrib/distributions/python/ops/exponential.py

@@ -70,6 +70,7 @@ class Exponential(gamma.Gamma):
     """
     broadcast_shape = self._lam.get_shape()
     with ops.op_scope([self.lam, n], name, "ExponentialSample"):
+      n = ops.convert_to_tensor(n, name="n")
       shape = array_ops.concat(
           0, [array_ops.pack([n]), array_ops.shape(self._lam)])
       sampled = random_ops.random_uniform(