1 files changed, 91 insertions, 0 deletions
diff --git a/tensorflow/python/kernel_tests/numerics_test.py b/tensorflow/python/kernel_tests/numerics_test.py
new file mode 100644
index 0000000000..8cb2fe2f8b
--- /dev/null
+++ b/tensorflow/python/kernel_tests/numerics_test.py
@@ -0,0 +1,91 @@
+"""Tests for tensorflow.ops.numerics."""
+import tensorflow.python.platform
+
+import numpy as np
+import tensorflow as tf
+
+from tensorflow.python.ops import control_flow_ops
+
+
+class VerifyTensorAllFiniteTest(tf.test.TestCase):
+
+  def testVerifyTensorAllFiniteSucceeds(self):
+    x_shape = [5, 4]
+    x = np.random.random_sample(x_shape).astype(np.float32)
+    for use_gpu in [False, True]:
+      with self.test_session(use_gpu=use_gpu):
+        t = tf.constant(x, shape=x_shape, dtype=tf.float32)
+        t_verified = tf.verify_tensor_all_finite(t, "Input is not a number.")
+        self.assertAllClose(x, t_verified.eval())
+
+  def testVerifyTensorAllFiniteFails(self):
+    x_shape = [5, 4]
+    x = np.random.random_sample(x_shape).astype(np.float32)
+    my_msg = "Input is not a number."
+
+    # Test NaN.
+    x[0] = np.nan
+    for use_gpu in [False, True]:
+      with self.test_session(use_gpu=use_gpu):
+        with self.assertRaisesOpError(my_msg):
+          t = tf.constant(x, shape=x_shape, dtype=tf.float32)
+          t_verified = tf.verify_tensor_all_finite(t, my_msg)
+          t_verified.eval()
+
+    # Test Inf.
+    x[0] = np.inf
+    for use_gpu in [False, True]:
+      with self.test_session(use_gpu=use_gpu):
+        with self.assertRaisesOpError(my_msg):
+          t = tf.constant(x, shape=x_shape, dtype=tf.float32)
+          t_verified = tf.verify_tensor_all_finite(t, my_msg)
+          t_verified.eval()
+
+
+class NumericsTest(tf.test.TestCase):
+
+  def testInf(self):
+    for use_gpu in [True, False]:
+      with self.test_session(use_gpu=use_gpu, graph=tf.Graph()):
+        t1 = tf.constant(1.0)
+        t2 = tf.constant(0.0)
+        a = tf.div(t1, t2)
+        check = tf.add_check_numerics_ops()
+        a = control_flow_ops.with_dependencies([check], a)
+        with self.assertRaisesOpError("Inf"):
+          a.eval()
+
+  def testNaN(self):
+    for use_gpu in [True, False]:
+      with self.test_session(use_gpu=use_gpu, graph=tf.Graph()):
+        t1 = tf.constant(0.0)
+        t2 = tf.constant(0.0)
+        a = tf.div(t1, t2)
+        check = tf.add_check_numerics_ops()
+        a = control_flow_ops.with_dependencies([check], a)
+        with self.assertRaisesOpError("NaN"):
+          a.eval()
+
+  def testBoth(self):
+    for use_gpu in [True, False]:
+      with self.test_session(use_gpu=use_gpu, graph=tf.Graph()):
+        t1 = tf.constant([1.0, 0.0])
+        t2 = tf.constant([0.0, 0.0])
+        a = tf.div(t1, t2)
+        check = tf.add_check_numerics_ops()
+        a = control_flow_ops.with_dependencies([check], a)
+        with self.assertRaisesOpError("Inf and NaN"):
+          a.eval()
+
+  def testPassThrough(self):
+    for use_gpu in [True, False]:
+      with self.test_session(use_gpu=use_gpu, graph=tf.Graph()):
+        t1 = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3])
+        checked = tf.check_numerics(t1, message="pass through test")
+        value = checked.eval()
+        self.assertAllEqual(np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]), value)
+        self.assertEqual([2, 3], checked.get_shape())
+
+
+if __name__ == "__main__":
+  tf.test.main()