1 files changed, 56 insertions, 0 deletions
diff --git a/tensorflow/python/kernel_tests/unpack_op_test.py b/tensorflow/python/kernel_tests/unpack_op_test.py
new file mode 100644
index 0000000000..4929af035f
--- /dev/null
+++ b/tensorflow/python/kernel_tests/unpack_op_test.py
@@ -0,0 +1,56 @@
+"""Functional tests for Unpack Op."""
+import tensorflow.python.platform
+
+import numpy as np
+import tensorflow as tf
+
+from tensorflow.python.kernel_tests import gradient_checker
+
+
+class UnpackOpTest(tf.test.TestCase):
+
+  def testSimple(self):
+    np.random.seed(7)
+    for use_gpu in False, True:
+      with self.test_session(use_gpu=use_gpu):
+        for shape in (2,), (3,), (2, 3), (3, 2), (4, 3, 2):
+          data = np.random.randn(*shape)
+          # Convert data to a single tensorflow tensor
+          x = tf.constant(data)
+          # Unpack into a list of tensors
+          cs = tf.unpack(x, num=shape[0])
+          self.assertEqual(type(cs), list)
+          self.assertEqual(len(cs), shape[0])
+          cs = [c.eval() for c in cs]
+          self.assertAllEqual(cs, data)
+
+  def testGradients(self):
+    for use_gpu in False, True:
+      for shape in (2,), (3,), (2, 3), (3, 2), (4, 3, 2):
+        data = np.random.randn(*shape)
+        shapes = [shape[1:]] * shape[0]
+        for i in xrange(shape[0]):
+          with self.test_session(use_gpu=use_gpu):
+            x = tf.constant(data)
+            cs = tf.unpack(x, num=shape[0])
+            err = gradient_checker.ComputeGradientError(x, shape, cs[i],
+                                                        shapes[i])
+            self.assertLess(err, 1e-6)
+
+  def testInferNum(self):
+    with self.test_session():
+      for shape in (2,), (3,), (2, 3), (3, 2), (4, 3, 2):
+        x = tf.placeholder(np.float32, shape=shape)
+        cs = tf.unpack(x)
+        self.assertEqual(type(cs), list)
+        self.assertEqual(len(cs), shape[0])
+
+  def testCannotInferNum(self):
+    x = tf.placeholder(np.float32)
+    with self.assertRaisesRegexp(
+        ValueError, r'Cannot infer num from shape TensorShape\(None\)'):
+      tf.unpack(x)
+
+
+if __name__ == '__main__':
+  tf.test.main()