Relu1 custom op.

This is implemented as custom op instead of builtin op because Relu1 is not
supported in Tensorflow and not commonly used.

PiperOrigin-RevId: 211571619

4 files changed, 158 insertions, 0 deletions

diff --git a/tensorflow/contrib/lite/kernels/BUILD b/tensorflow/contrib/lite/kernels/BUILD
index ab989c5425..b7c5cbf207 100644
--- a/tensorflow/contrib/lite/kernels/BUILD
+++ b/tensorflow/contrib/lite/kernels/BUILD
@@ -192,6 +192,7 @@ cc_library(
         "pooling.cc",
         "pow.cc",
         "reduce.cc",
+        "relu1.cc",
         "reshape.cc",
         "resize_bilinear.cc",
         "select.cc",
@@ -305,6 +306,23 @@ tf_cc_test(
 )
 
 tf_cc_test(
+    name = "relu1_test",
+    size = "small",
+    srcs = ["relu1_test.cc"],
+    tags = [
+        "no_oss",
+        "tflite_not_portable_ios",
+    ],
+    deps = [
+        ":builtin_ops",
+        "//tensorflow/contrib/lite:framework",
+        "//tensorflow/contrib/lite/kernels:test_util",
+        "@com_google_googletest//:gtest",
+        "@flatbuffers",
+    ],
+)
+
+tf_cc_test(
     name = "activations_test",
     size = "small",
     srcs = ["activations_test.cc"],
diff --git a/tensorflow/contrib/lite/kernels/register.cc b/tensorflow/contrib/lite/kernels/register.cc
index 188015f43c..c66959fdf4 100644
--- a/tensorflow/contrib/lite/kernels/register.cc
+++ b/tensorflow/contrib/lite/kernels/register.cc
@@ -25,6 +25,7 @@ TfLiteRegistration* Register_AUDIO_SPECTROGRAM();
 TfLiteRegistration* Register_LAYER_NORM_LSTM();
 TfLiteRegistration* Register_MFCC();
 TfLiteRegistration* Register_DETECTION_POSTPROCESS();
+TfLiteRegistration* Register_RELU_1();
 
 }  // namespace custom
 
@@ -249,6 +250,7 @@ BuiltinOpResolver::BuiltinOpResolver() {
   AddCustom("AudioSpectrogram",
             tflite::ops::custom::Register_AUDIO_SPECTROGRAM());
   AddCustom("LayerNormLstm", tflite::ops::custom::Register_LAYER_NORM_LSTM());
+  AddCustom("Relu1", tflite::ops::custom::Register_RELU_1());
   AddCustom("TFLite_Detection_PostProcess",
             tflite::ops::custom::Register_DETECTION_POSTPROCESS());
 }
diff --git a/tensorflow/contrib/lite/kernels/relu1.cc b/tensorflow/contrib/lite/kernels/relu1.cc
new file mode 100644
index 0000000000..abafee2d57
--- /dev/null
+++ b/tensorflow/contrib/lite/kernels/relu1.cc
@@ -0,0 +1,59 @@
+/* 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 "tensorflow/contrib/lite/context.h"
+#include "tensorflow/contrib/lite/kernels/internal/tensor.h"
+#include "tensorflow/contrib/lite/kernels/kernel_util.h"
+
+namespace tflite {
+namespace ops {
+namespace custom {
+namespace relu1 {
+
+TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+  TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
+  TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
+  const TfLiteTensor* input = GetInput(context, node, 0);
+  TF_LITE_ENSURE_EQ(context, input->type, kTfLiteFloat32);
+  TfLiteTensor* output = GetOutput(context, node, 0);
+  output->type = input->type;
+  return context->ResizeTensor(context, output,
+                               TfLiteIntArrayCopy(input->dims));
+}
+
+// This is derived from lite/kernels/activations.cc.
+TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* input = GetInput(context, node, 0);
+  TfLiteTensor* output = GetOutput(context, node, 0);
+  const int elements = NumElements(input);
+  const float* in = input->data.f;
+  const float* in_end = in + elements;
+  float* out = output->data.f;
+  for (; in < in_end; ++in, ++out) {
+    *out = std::min(std::max(0.f, *in), 1.f);
+  }
+  return kTfLiteOk;
+}
+
+}  // namespace relu1
+
+TfLiteRegistration* Register_RELU_1() {
+  static TfLiteRegistration r = {/*init=*/nullptr, /*free=*/nullptr,
+                                 relu1::Prepare, relu1::Eval};
+  return &r;
+}
+
+}  // namespace custom
+}  // namespace ops
+}  // namespace tflite
diff --git a/tensorflow/contrib/lite/kernels/relu1_test.cc b/tensorflow/contrib/lite/kernels/relu1_test.cc
new file mode 100644
index 0000000000..c1e0149c20
--- /dev/null
+++ b/tensorflow/contrib/lite/kernels/relu1_test.cc
@@ -0,0 +1,79 @@
+/* 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 "flatbuffers/flexbuffers.h"  // flatbuffers
+#include "tensorflow/contrib/lite/kernels/register.h"
+#include "tensorflow/contrib/lite/kernels/test_util.h"
+
+namespace tflite {
+namespace ops {
+namespace custom {
+
+TfLiteRegistration* Register_RELU_1();
+
+namespace {
+
+using ::testing::ElementsAreArray;
+
+class BaseActivationsOpModel : public SingleOpModel {
+ public:
+  explicit BaseActivationsOpModel(const TensorData& input) {
+    input_ = AddInput(input);
+    output_ = AddOutput({input.type, {}});
+    flexbuffers::Builder fbb;
+    fbb.Map([&]() {});
+    fbb.Finish();
+    SetCustomOp("RELU_1", fbb.GetBuffer(), Register_RELU_1);
+    BuildInterpreter({GetShape(input_)});
+  }
+
+ protected:
+  int input_;
+  int output_;
+};
+
+class FloatActivationsOpModel : public BaseActivationsOpModel {
+ public:
+  using BaseActivationsOpModel::BaseActivationsOpModel;
+
+  void SetInput(std::initializer_list<float> data) {
+    PopulateTensor(input_, data);
+  }
+  std::vector<float> GetOutput() { return ExtractVector<float>(output_); }
+};
+
+TEST(FloatActivationsOpTest, Relu1) {
+  FloatActivationsOpModel m(/*input=*/{TensorType_FLOAT32, {1, 2, 4, 1}});
+  m.SetInput({
+      0.0, -0.6, 0.2, -0.4,  //
+      0.3, -2.0, 1.1, -0.1,  //
+  });
+  m.Invoke();
+  EXPECT_THAT(m.GetOutput(), ElementsAreArray({
+                                 0.0, 0.0, 0.2, 0.0,  //
+                                 0.3, 0.0, 1.0, 0.0,  //
+                             }));
+}
+
+}  // namespace
+}  // namespace custom
+}  // namespace ops
+}  // namespace tflite
+
+int main(int argc, char** argv) {
+  ::tflite::LogToStderr();
+  ::testing::InitGoogleTest(&argc, argv);
+  return RUN_ALL_TESTS();
+}