Added minimum op, better type support in maximum.

PiperOrigin-RevId: 192292693

1 files changed, 143 insertions, 0 deletions

diff --git a/tensorflow/contrib/lite/kernels/maximum_minimum_test.cc b/tensorflow/contrib/lite/kernels/maximum_minimum_test.cc
new file mode 100644
index 0000000000..0752aa1804
--- /dev/null
+++ b/tensorflow/contrib/lite/kernels/maximum_minimum_test.cc
@@ -0,0 +1,143 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include <gtest/gtest.h>
+#include "tensorflow/contrib/lite/interpreter.h"
+#include "tensorflow/contrib/lite/kernels/register.h"
+#include "tensorflow/contrib/lite/kernels/test_util.h"
+#include "tensorflow/contrib/lite/model.h"
+
+namespace tflite {
+namespace {
+
+using ::testing::ElementsAreArray;
+
+class MaxMinOpModel : public SingleOpModel {
+ public:
+  MaxMinOpModel(tflite::BuiltinOperator op, const TensorData& input1,
+                const TensorData& input2, const TensorType& output) {
+    input1_ = AddInput(input1);
+    input2_ = AddInput(input2);
+    output_ = AddOutput(output);
+    SetBuiltinOp(op, BuiltinOptions_MaximumMinimumOptions,
+                 CreateMaximumMinimumOptions(builder_).Union());
+    BuildInterpreter({GetShape(input1_), GetShape(input2_)});
+  }
+
+  template <class T>
+  void SetInput1(std::initializer_list<T> data) {
+    PopulateTensor(input1_, data);
+  }
+
+  template <class T>
+  void SetInput2(std::initializer_list<T> data) {
+    PopulateTensor(input2_, data);
+  }
+
+  template <class T>
+  std::vector<T> GetOutput() {
+    return ExtractVector<T>(output_);
+  }
+  std::vector<int> GetOutputShape() { return GetTensorShape(output_); }
+
+ protected:
+  int input1_;
+  int input2_;
+  int output_;
+};
+
+template <typename data_type>
+void TestModel(tflite::BuiltinOperator op, const TensorData& input1,
+               const TensorData& input2, const TensorData& output,
+               std::initializer_list<data_type> input1_values,
+               std::initializer_list<data_type> input2_values,
+               std::initializer_list<data_type> output_values) {
+  MaxMinOpModel m(op, input1, input2, output.type);
+  m.SetInput1<data_type>(input1_values);
+  m.SetInput2<data_type>(input2_values);
+  m.Invoke();
+  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray(output.shape));
+  EXPECT_THAT(m.GetOutput<data_type>(), ElementsAreArray(output_values));
+}
+
+template <>
+void TestModel(tflite::BuiltinOperator op, const TensorData& input1,
+               const TensorData& input2, const TensorData& output,
+               std::initializer_list<float> input1_values,
+               std::initializer_list<float> input2_values,
+               std::initializer_list<float> output_values) {
+  MaxMinOpModel m(op, input1, input2, output.type);
+  m.SetInput1<float>(input1_values);
+  m.SetInput2<float>(input2_values);
+  m.Invoke();
+  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray(output.shape));
+  EXPECT_THAT(m.GetOutput<float>(),
+              ElementsAreArray(ArrayFloatNear(output_values)));
+}
+
+TEST(MaximumOpTest, FloatTest) {
+  std::initializer_list<float> data1 = {1.0, 0.0, -1.0, 11.0, -2.0, -1.44};
+  std::initializer_list<float> data2 = {-1.0, 0.0, 1.0, 12.0, -3.0, -1.43};
+  TestModel<float>(BuiltinOperator_MAXIMUM, {TensorType_FLOAT32, {3, 1, 2}},
+                   {TensorType_FLOAT32, {3, 1, 2}},
+                   {TensorType_FLOAT32, {3, 1, 2}}, data1, data2,
+                   {1.0, 0.0, 1.0, 12.0, -2.0, -1.43});
+  TestModel<float>(BuiltinOperator_MINIMUM, {TensorType_FLOAT32, {3, 1, 2}},
+                   {TensorType_FLOAT32, {3, 1, 2}},
+                   {TensorType_FLOAT32, {3, 1, 2}}, data1, data2,
+                   {-1.0, 0.0, -1.0, 11.0, -3.0, -1.44});
+}
+
+TEST(MaxMinOpTest, Uint8Test) {
+  std::initializer_list<uint8_t> data1 = {1, 0, 2, 11, 2, 23};
+  std::initializer_list<uint8_t> data2 = {0, 0, 1, 12, 255, 1};
+  TestModel<uint8_t>(BuiltinOperator_MAXIMUM, {TensorType_UINT8, {3, 1, 2}},
+                     {TensorType_UINT8, {3, 1, 2}},
+                     {TensorType_UINT8, {3, 1, 2}}, data1, data2,
+                     {1, 0, 2, 12, 255, 23});
+  TestModel<uint8_t>(BuiltinOperator_MINIMUM, {TensorType_UINT8, {3, 1, 2}},
+                     {TensorType_UINT8, {3, 1, 2}},
+                     {TensorType_UINT8, {3, 1, 2}}, data1, data2,
+                     {0, 0, 1, 11, 2, 1});
+}
+
+TEST(MaximumOpTest, FloatWithBroadcastTest) {
+  std::initializer_list<float> data1 = {1.0, 0.0, -1.0, -2.0, -1.44, 11.0};
+  std::initializer_list<float> data2 = {0.5, 2.0};
+  TestModel<float>(BuiltinOperator_MAXIMUM, {TensorType_FLOAT32, {3, 1, 2}},
+                   {TensorType_FLOAT32, {2}}, {TensorType_FLOAT32, {3, 1, 2}},
+                   data1, data2, {1.0, 2.0, 0.5, 2.0, 0.5, 11.0});
+  TestModel<float>(BuiltinOperator_MINIMUM, {TensorType_FLOAT32, {3, 1, 2}},
+                   {TensorType_FLOAT32, {2}}, {TensorType_FLOAT32, {3, 1, 2}},
+                   data1, data2, {0.5, 0.0, -1.0, -2.0, -1.44, 2.0});
+}
+
+TEST(MaximumOpTest, Int32WithBroadcastTest) {
+  std::initializer_list<int32_t> data1 = {1, 0, -1, -2, 3, 11};
+  std::initializer_list<int32_t> data2 = {2};
+  TestModel<int32>(BuiltinOperator_MAXIMUM, {TensorType_INT32, {3, 1, 2}},
+                   {TensorType_INT32, {1}}, {TensorType_INT32, {3, 1, 2}},
+                   data1, data2, {2, 2, 2, 2, 3, 11});
+  TestModel<int32>(BuiltinOperator_MINIMUM, {TensorType_INT32, {3, 1, 2}},
+                   {TensorType_INT32, {1}}, {TensorType_INT32, {3, 1, 2}},
+                   data1, data2, {1, 0, -1, -2, 2, 2});
+}
+}  // namespace
+}  // namespace tflite
+
+int main(int argc, char** argv) {
+  ::tflite::LogToStderr();
+  ::testing::InitGoogleTest(&argc, argv);
+  return RUN_ALL_TESTS();
+}