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"""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()
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