1 files changed, 47 insertions, 0 deletions
diff --git a/tensorflow/python/kernel_tests/softplus_op_test.py b/tensorflow/python/kernel_tests/softplus_op_test.py
new file mode 100644
index 0000000000..25b68aa659
--- /dev/null
+++ b/tensorflow/python/kernel_tests/softplus_op_test.py
@@ -0,0 +1,47 @@
+"""Tests for Softplus and SoftplusGrad."""
+import tensorflow.python.platform
+
+import numpy as np
+import tensorflow as tf
+
+from tensorflow.python.kernel_tests import gradient_checker as gc
+
+
+class SoftplusTest(tf.test.TestCase):
+
+  def _npSoftplus(self, np_features):
+    return np.log(1 + np.exp(np_features))
+
+  def _testSoftplus(self, np_features, use_gpu=False):
+    np_softplus = self._npSoftplus(np_features)
+    with self.test_session(use_gpu=use_gpu):
+      softplus = tf.nn.softplus(np_features)
+      tf_softplus = softplus.eval()
+    self.assertAllClose(np_softplus, tf_softplus)
+    self.assertShapeEqual(np_softplus, softplus)
+
+  def testNumbers(self):
+    for t in [np.float, np.double]:
+      self._testSoftplus(
+          np.array([[-9, 7, -5, 3, -1], [1, -3, 5, -7, 9]]).astype(t),
+          use_gpu=False)
+      self._testSoftplus(
+          np.array([[-9, 7, -5, 3, -1], [1, -3, 5, -7, 9]]).astype(t),
+          use_gpu=True)
+
+  def testGradient(self):
+    with self.test_session():
+      x = tf.constant(
+          [-0.9, -0.7, -0.5, -0.3, -0.1, 0.1, 0.3, 0.5, 0.7, 0.9],
+          shape=[2, 5], name="x")
+      y = tf.nn.softplus(x, name="softplus")
+      x_init = np.asarray(
+          [[-0.9, -0.7, -0.5, -0.3, -0.1], [0.1, 0.3, 0.5, 0.7, 0.9]],
+          dtype=np.float32, order="F")
+      err = gc.ComputeGradientError(x, [2, 5], y, [2, 5], x_init_value=x_init)
+    print "softplus (float) gradient err = ", err
+    self.assertLess(err, 1e-4)
+
+
+if __name__ == "__main__":
+  tf.test.main()