1 files changed, 65 insertions, 0 deletions
diff --git a/tensorflow/python/kernel_tests/softmax_op_test.py b/tensorflow/python/kernel_tests/softmax_op_test.py
new file mode 100644
index 0000000000..fd25970093
--- /dev/null
+++ b/tensorflow/python/kernel_tests/softmax_op_test.py
@@ -0,0 +1,65 @@
+"""Tests for SoftmaxOp."""
+import tensorflow.python.platform
+
+import numpy as np
+import tensorflow as tf
+
+
+class SoftmaxTest(tf.test.TestCase):
+
+  def _npSoftmax(self, features):
+    batch_dim = 0
+    class_dim = 1
+    batch_size = features.shape[batch_dim]
+    e = np.exp(features -
+               np.reshape(np.amax(features, axis=class_dim), [batch_size, 1]))
+    return e / np.reshape(np.sum(e, axis=class_dim), [batch_size, 1])
+
+  def _testSoftmax(self, np_features, use_gpu=False):
+    np_softmax = self._npSoftmax(np_features)
+    with self.test_session(use_gpu=use_gpu):
+      tf_softmax = tf.nn.softmax(np_features)
+      out = tf_softmax.eval()
+    self.assertAllClose(np_softmax, out)
+    self.assertShapeEqual(np_softmax, tf_softmax)
+    # Bonus check: the softmaxes should add to one in each
+    # batch element.
+    self.assertAllClose(np.ones(out.shape[0]),
+                        np.sum(out, axis=1))
+
+  def _testAll(self, features):
+    self._testSoftmax(features, use_gpu=False)
+    self._testSoftmax(features, use_gpu=True)
+
+  def testNpSoftmax(self):
+    features = [[1., 1., 1., 1.], [1., 2., 3., 4.]]
+    # Batch 0: All exps are 1.  The expected result is
+    # [0.25, 0.25, 0.25, 0.25]
+    #
+    # Batch 1:
+    # exps = [1., 2.718, 7.389, 20.085]
+    # sum = 31.192
+    # Softmaxes = exps / sum = [0.0320586, 0.08714432, 0.23688282, 0.64391426]
+    np_sm = self._npSoftmax(np.array(features))
+    self.assertAllClose(
+        np.array([[0.25, 0.25, 0.25, 0.25],
+                  [0.0320586, 0.08714432, 0.23688282, 0.64391426]]),
+        np_sm,
+        rtol=1.e-5, atol=1.e-5)
+
+  def testShapeMismatch(self):
+    with self.assertRaises(ValueError):
+      tf.nn.softmax([0., 1., 2., 3.])
+
+  def testFloat(self):
+    self._testAll(
+        np.array([[1., 1., 1., 1.], [1., 2., 3., 4.]]).astype(np.float32))
+
+  def testDouble(self):
+    self._testSoftmax(
+        np.array([[1., 1., 1., 1.], [1., 2., 3., 4.]]).astype(np.float64),
+        use_gpu=False)
+
+
+if __name__ == "__main__":
+  tf.test.main()