1 files changed, 140 insertions, 0 deletions
diff --git a/tensorflow/python/kernel_tests/pad_op_test.py b/tensorflow/python/kernel_tests/pad_op_test.py
new file mode 100644
index 0000000000..113aeb1ccf
--- /dev/null
+++ b/tensorflow/python/kernel_tests/pad_op_test.py
@@ -0,0 +1,140 @@
+"""Tests for tensorflow.ops.nn_ops.Pad."""
+
+import tensorflow.python.platform
+
+import numpy as np
+import tensorflow as tf
+
+from tensorflow.python.kernel_tests import gradient_checker as gc
+
+
+class PadOpTest(tf.test.TestCase):
+
+  def _npPad(self, inp, paddings):
+    return np.pad(inp, paddings, mode="constant")
+
+  def testNpPad(self):
+    self.assertAllClose(
+        np.array([[0, 0, 0, 0, 0, 0],
+                  [0, 3, 3, 0, 0, 0],
+                  [0, 4, 4, 0, 0, 0],
+                  [0, 5, 5, 0, 0, 0],
+                  [0, 0, 0, 0, 0, 0],
+                  [0, 0, 0, 0, 0, 0]]),
+        self._npPad(np.array([[3, 3], [4, 4], [5, 5]]), [[1, 2], [1, 3]]))
+
+  def _testPad(self, np_inputs, paddings, use_gpu=False):
+    np_val = self._npPad(np_inputs, paddings)
+    with self.test_session(use_gpu=use_gpu):
+      tf_val = tf.pad(np_inputs, paddings)
+      out = tf_val.eval()
+    self.assertAllClose(np_val, out)
+    self.assertShapeEqual(np_val, tf_val)
+
+  def _testGradient(self, x, a):
+    with self.test_session():
+      inx = tf.convert_to_tensor(x)
+      xs = list(x.shape)
+      ina = tf.convert_to_tensor(a)
+      y = tf.pad(inx, ina)
+      # Expected y's shape to be:
+      ys = list(np.array(x.shape) + np.sum(np.array(a), axis=1))
+      jacob_t, jacob_n = gc.ComputeGradient(inx, xs, y, ys, x_init_value=x)
+    self.assertAllClose(jacob_t, jacob_n, rtol=1e-5, atol=1e-5)
+
+  def _testAll(self, np_inputs, paddings):
+    self._testPad(np_inputs, paddings, use_gpu=False)
+    self._testPad(np_inputs, paddings, use_gpu=True)
+    if np_inputs.dtype == np.float32:
+      self._testGradient(np_inputs, paddings)
+
+  def testInputDims(self):
+    with self.test_session():
+      with self.assertRaises(ValueError):
+        tf.pad(
+            tf.reshape([1, 2], shape=[1, 2, 1, 1, 1, 1]),
+            tf.reshape([1, 2], shape=[1, 2]))
+
+  def testPaddingsDim(self):
+    with self.test_session():
+      with self.assertRaises(ValueError):
+        tf.pad(
+            tf.reshape([1, 2], shape=[1, 2]),
+            tf.reshape([1, 2], shape=[2]))
+
+  def testPaddingsDim2(self):
+    with self.test_session():
+      with self.assertRaises(ValueError):
+        tf.pad(
+            tf.reshape([1, 2], shape=[1, 2]),
+            tf.reshape([1, 2], shape=[2, 1]))
+
+  def testPaddingsDim3(self):
+    with self.test_session():
+      with self.assertRaises(ValueError):
+        tf.pad(
+            tf.reshape([1, 2], shape=[1, 2]),
+            tf.reshape([1, 2], shape=[1, 2]))
+
+  def testPaddingsDim4(self):
+    with self.test_session():
+      with self.assertRaises(ValueError):
+        tf.pad(
+            tf.reshape([1, 2], shape=[1, 2]),
+            tf.reshape([1, 2, 3, 4, 5, 6], shape=[3, 2]))
+
+  def testPaddingsNonNegative(self):
+    with self.test_session():
+      with self.assertRaisesRegexp(ValueError, "must be non-negative"):
+        tf.pad(
+            tf.constant([1], shape=[1]),
+            tf.constant([-1, 0], shape=[1, 2]))
+
+  def testPaddingsNonNegative2(self):
+    with self.test_session():
+      with self.assertRaisesRegexp(ValueError, "must be non-negative"):
+        tf.pad(
+            tf.constant([1], shape=[1]),
+            tf.constant([-1, 0], shape=[1, 2]))
+
+  def testIntTypes(self):
+    # TODO(mdevin): Figure out why the padding tests do not work on GPU
+    # for int types and rank > 2.
+    for t in [np.int32, np.int64]:
+      self._testPad((np.random.rand(4, 3, 3) * 100).astype(t),
+                    [[1, 0], [2, 3], [0, 2]])
+
+  def testFloatTypes(self):
+    for t in [np.float32, np.float64]:
+      self._testAll(np.random.rand(2, 5).astype(t),
+                    [[1, 0], [2, 0]])
+
+  def testShapeFunctionEdgeCases(self):
+    # Unknown paddings shape.
+    inp = tf.constant(0.0, shape=[4, 4, 4, 4])
+    padded = tf.pad(inp, tf.placeholder(tf.int32))
+    self.assertEqual([None, None, None, None], padded.get_shape().as_list())
+
+    # Unknown input shape.
+    inp = tf.placeholder(tf.float32)
+    padded = tf.pad(inp, [[2, 2], [2, 2]])
+    self.assertEqual([None, None], padded.get_shape().as_list())
+
+    # Unknown input and paddings shape.
+    inp = tf.placeholder(tf.float32)
+    padded = tf.pad(inp, tf.placeholder(tf.int32))
+    self.assertAllEqual(None, padded.get_shape().ndims)
+
+  def testScalars(self):
+    paddings = np.zeros((0, 2), dtype=np.int32)
+    inp = np.asarray(7)
+    for use_gpu in False, True:
+      with self.test_session(use_gpu=use_gpu):
+        tf_val = tf.pad(inp, paddings)
+        out = tf_val.eval()
+      self.assertAllClose(inp, out)
+      self.assertShapeEqual(inp, tf_val)
+
+
+if __name__ == "__main__":
+  tf.test.main()