Merge changes from github.

PiperOrigin-RevId: 183100142

4 files changed, 72 insertions, 15 deletions

diff --git a/tensorflow/contrib/periodic_resample/BUILD b/tensorflow/contrib/periodic_resample/BUILD
index 71582f9c9a..bd9078ae76 100644
--- a/tensorflow/contrib/periodic_resample/BUILD
+++ b/tensorflow/contrib/periodic_resample/BUILD
@@ -6,6 +6,7 @@ exports_files(["LICENSE"])
 
 load(
     "//tensorflow:tensorflow.bzl",
+    "py_test",
     "tf_gen_op_libs",
     "tf_custom_op_library",
     "tf_custom_op_py_library",
@@ -64,11 +65,28 @@ py_library(
         "python/__init__.py",
     ],
     srcs_version = "PY2AND3",
+    tags = [
+        "notap",
+    ],
     deps = [
         ":periodic_resample_op_py",
     ],
 )
 
+py_test(
+    name = "periodic_resample_op_test",
+    srcs = ["python/kernel_tests/periodic_resample_op_test.py"],
+    srcs_version = "PY2AND3",
+    tags = [
+        "notap",
+    ],
+    deps = [
+        ":init_py",
+        "//tensorflow/contrib/util:util_py",
+        "//tensorflow/python:framework_test_lib",
+    ],
+)
+
 # py_library(
 #     name = "periodic_resample_op_py",
 #     srcs = ["python/ops/periodic_resample_op.py"],
diff --git a/tensorflow/contrib/periodic_resample/kernels/periodic_resample_op.h b/tensorflow/contrib/periodic_resample/kernels/periodic_resample_op.h
index bef21f7a5c..ba410f025d 100644
--- a/tensorflow/contrib/periodic_resample/kernels/periodic_resample_op.h
+++ b/tensorflow/contrib/periodic_resample/kernels/periodic_resample_op.h
@@ -100,6 +100,8 @@ template <class InputDataT,
                   desired_shape.size(), "."));
 
   bool found = false;
+  const auto& input_tensor_shape = input_tensor.shape();
+
   for (int i = 0; i < rank; ++i) {
     // if (desired_shape(i) < 1) {
     if (desired_shape[i] < 1) {
@@ -111,6 +113,15 @@ template <class InputDataT,
       adjustable_dimension = i;
       found = true;
     } else {
+      OP_REQUIRES(
+          context, desired_shape[i] >= input_tensor_shape.dim_size(i),
+          tensorflow::errors::InvalidArgument(
+              "periodic_resample expects the size of non-adjustable "
+              "dimensions be at least as large as size of input tensor."
+              " Dimension ", i, " input tensor has size ",
+              input_tensor_shape.dim_size(i), ", desired shape has size ",
+              desired_shape[i], "."));
+
       // target_dimensions[i] = desired_shape(i);
       target_dimensions[i] = desired_shape[i];
       new_sliced_size *= target_dimensions[i];
diff --git a/tensorflow/contrib/periodic_resample/ops/array_ops.cc b/tensorflow/contrib/periodic_resample/ops/array_ops.cc
index c90fc06c7f..82bd796956 100644
--- a/tensorflow/contrib/periodic_resample/ops/array_ops.cc
+++ b/tensorflow/contrib/periodic_resample/ops/array_ops.cc
@@ -34,26 +34,40 @@ This function implements a slightly more generic version of the subpixel
 convolutions found in this [paper](https://arxiv.org/abs/1609.05158).
 
 The formula for computing the elements in the `output` tensor is as follows:
+
   `T` = `values` tensor of rank `R`
+
   `S` = desired `shape` of output tensor (vector of length `R`)
+
   `P` = `output` tensor of rank `R`
-  \((T_1,\ldots,T_R)\) = shape(`T`)
-  \([S_1,\ldots,S_q,\ldots,S_R]\) = elements of vector `S`
 
-  A single element in `S` is left unspecified (denoted \(S_q=-1\)).
-  Let \(f_i\) denote the (possibly non-integer) factor that relates the original
-  dimension to the desired dimensions, \(S_i=f_i T_i\), for \(i\neq q\) where
-  \(f_i>0\).
+  \\((T_1,\\ldots,T_R)\\) = shape(`T`)
+
+  \\([S_1,\\ldots,S_q,\\ldots,S_R]\\) = elements of vector `S`
+
+  A single element in `S` is left unspecified (denoted \\(S_q=-1\\)).
+
+  Let \\(f_i\\) denote the (possibly non-integer) factor that relates the original
+  dimension to the desired dimensions, \\(S_i=f_i T_i\\), for \\(i\\neq q\\) where
+  \\(f_i>0\\).
+
   Define the following:
-    \(g_i=\lceil f_i\rceil\)
-    \(t=\prod_i T_i\)
-    \(s=\prod_{i\neq q} S_i\)
-  \(S_q\) can then be defined as by \(S_q=\lfloor t/s\rfloor\).
+
+  \\(g_i=\\lceil f_i\\rceil\\)
+
+  \\(t=\\prod_i T_i\\)
+
+  \\(s=\\prod_{i\\neq q} S_i\\)
+
+  \\(S_q\\) can then be defined by \\(S_q=\\lfloor t/s\\rfloor\\).
   The elements of the resulting tensor are defined as
-  \(P_{s_1,\ldots,s_R}=T_{h_1,\ldots,h_q,\ldots,h_R}\).
-  The \(h_i\) (\(i\neq q\)) are defined by \(h_i=\lfloor s_i/g_i\rfloor\).
-  \(h_q=S_q\sum_{j\neq q}^{q-1}G_j \mathrm{mod}(s_j,g_j) + s_q\), where
-  \(G_j=\prod_{i}^{j-1}g_i\) (\(G_0=1\)).
+
+  \\(P_{s_1,\\ldots,s_R}=T_{h_1,\\ldots,h_q,\\ldots,h_R}\\).
+
+  The \\(h_i\\) (\\(i\\neq q\\)) are defined by \\(h_i=\\lfloor s_i/g_i\\rfloor\\).
+
+  \\(h_q=S_q\\sum_{j\\neq q}^{q-1}G_j \\mathrm{mod}(s_j,g_j) + s_q\\), where
+  \\(G_j=\\prod_{i}^{j-1}g_i\\) (\\(G_0=1\\)).
 
 One drawback of this method is that whenever the output dimensions are slightly
 less than integer multiples of the input dimensions, many of the tensor elements
diff --git a/tensorflow/contrib/periodic_resample/python/kernel_tests/periodic_resample_op_test.py b/tensorflow/contrib/periodic_resample/python/kernel_tests/periodic_resample_op_test.py
index 1d727870f6..30a2077570 100644
--- a/tensorflow/contrib/periodic_resample/python/kernel_tests/periodic_resample_op_test.py
+++ b/tensorflow/contrib/periodic_resample/python/kernel_tests/periodic_resample_op_test.py
@@ -19,8 +19,9 @@ from __future__ import division
 from __future__ import print_function
 
 import numpy
-import tensorflow
+
 from tensorflow.contrib.periodic_resample import periodic_resample
+from tensorflow.python.framework import errors_impl
 from tensorflow.python.framework import test_util
 from tensorflow.python.ops import variables
 from tensorflow.python.platform import googletest
@@ -96,6 +97,19 @@ class PeriodicResampleTest(test_util.TensorFlowTestCase):
       result = periodic_resample(input_tensor, desired_shape).eval()
       self.assertAllEqual(result, output_tensor)
 
+  def testPeriodicResampleErrors(self):
+    input_tensor = numpy.zeros(shape=[1, 2, 2, 4])
+    with self.test_session():
+      variables.global_variables_initializer().run()
+      with self.assertRaisesWithPredicateMatch(
+          errors_impl.InvalidArgumentError,
+          'Dimension 3 input tensor has size 4, desired shape has size 1'):
+        periodic_resample(input_tensor, [None, 4, 4, 1]).eval()
+      with self.assertRaisesWithPredicateMatch(
+          errors_impl.InvalidArgumentError,
+          '4, to be the same as the length of the desired shape, 3'):
+        periodic_resample(input_tensor, [None, 4, 4]).eval()
+
 
 if __name__ == "__main__":
   googletest.main()