1 files changed, 50 insertions, 0 deletions
diff --git a/tensorflow/python/kernel_tests/logging_ops_test.py b/tensorflow/python/kernel_tests/logging_ops_test.py
new file mode 100644
index 0000000000..18ca441b23
--- /dev/null
+++ b/tensorflow/python/kernel_tests/logging_ops_test.py
@@ -0,0 +1,50 @@
+"""Tests for tensorflow.kernels.logging_ops."""
+
+import tensorflow.python.platform
+
+import tensorflow as tf
+
+
+class LoggingOpsTest(tf.test.TestCase):
+
+  def testAssertDivideByZero(self):
+    with self.test_session() as sess:
+      epsilon = tf.convert_to_tensor(1e-20)
+      x = tf.convert_to_tensor(0.0)
+      y = tf.convert_to_tensor(1.0)
+      z = tf.convert_to_tensor(2.0)
+      # assert(epsilon < y)
+      # z / y
+      with sess.graph.control_dependencies(
+          [tf.Assert(tf.less(epsilon, y), ["Divide-by-zero"])]):
+        out = tf.div(z, y)
+      self.assertAllEqual(2.0, out.eval())
+      # assert(epsilon < x)
+      # z / x
+      #
+      # This tests printing out multiple tensors
+      with sess.graph.control_dependencies(
+          [tf.Assert(tf.less(epsilon, x),
+                     ["Divide-by-zero", "less than x"])]):
+        out = tf.div(z, x)
+      with self.assertRaisesOpError("less than x"):
+        out.eval()
+
+
+class PrintGradientTest(tf.test.TestCase):
+
+  def testPrintGradient(self):
+    with self.test_session():
+      inp = tf.constant(2.0, shape=[100, 32], name="in")
+      w = tf.constant(4.0, shape=[10, 100], name="w")
+      wx = tf.matmul(w, inp, name="wx")
+      wx_print = tf.Print(wx, [w, w, w])
+      wx_grad = tf.gradients(wx, w)[0]
+      wx_print_grad = tf.gradients(wx_print, w)[0]
+      wxg = wx_grad.eval()
+      wxpg = wx_print_grad.eval()
+    self.assertAllEqual(wxg, wxpg)
+
+
+if __name__ == "__main__":
+  tf.test.main()