Internal Change.

PiperOrigin-RevId: 175307445

1 files changed, 129 insertions, 0 deletions

diff --git a/tensorflow/contrib/lite/kernels/resize_bilinear.cc b/tensorflow/contrib/lite/kernels/resize_bilinear.cc
new file mode 100644
index 0000000000..1613c9a89f
--- /dev/null
+++ b/tensorflow/contrib/lite/kernels/resize_bilinear.cc
@@ -0,0 +1,129 @@
+/* Copyright 2017 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/builtin_op_data.h"
+#include "tensorflow/contrib/lite/context.h"
+#include "tensorflow/contrib/lite/kernels/internal/optimized/optimized_ops.h"
+#include "tensorflow/contrib/lite/kernels/internal/reference/reference_ops.h"
+#include "tensorflow/contrib/lite/kernels/internal/tensor.h"
+#include "tensorflow/contrib/lite/kernels/kernel_util.h"
+#include "tensorflow/contrib/lite/kernels/op_macros.h"
+
+namespace tflite {
+namespace ops {
+namespace builtin {
+namespace resize_bilinear {
+
+// This file has three implementation of RESIZE_BILINEAR.
+enum KernelType {
+  kReference,
+  kGenericOptimized,  // Neon-free
+  kNeonOptimized,
+};
+
+constexpr int kInputTensor = 0;
+constexpr int kOutputTensor = 0;
+
+TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+  auto* params =
+      reinterpret_cast<TfLiteResizeBilinearParams*>(node->builtin_data);
+
+  TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
+  TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
+
+  TfLiteTensor* input = GetInput(context, node, kInputTensor);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+
+  // TODO(ahentz): Our current implementations rely on the inputs being 4D.
+  TF_LITE_ENSURE_EQ(context, NumDimensions(input), 4);
+
+  // TODO(ahentz): Our current implementations only support float32.
+  TF_LITE_ENSURE_EQ(context, output->type, kTfLiteFloat32);
+  TF_LITE_ENSURE_EQ(context, input->type, output->type);
+
+  TfLiteIntArray* output_size = TfLiteIntArrayCreate(4);
+  output_size->data[0] = input->dims->data[0];
+  output_size->data[1] = params->new_height;
+  output_size->data[2] = params->new_width;
+  output_size->data[3] = input->dims->data[3];
+
+  return context->ResizeTensor(context, output, output_size);
+}
+
+template <KernelType kernel_type>
+TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+  auto* params =
+      reinterpret_cast<TfLiteResizeBilinearParams*>(node->builtin_data);
+
+  TfLiteTensor* input = GetInput(context, node, kInputTensor);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+
+  // We have to fake a tensor here, to satisfy ResizeBilinear().
+  int32 output_size_data[2] = {params->new_height, params->new_width};
+
+  if (output->type == kTfLiteFloat32) {
+#define TF_LITE_RESIZE_BILINEAR(type)                                     \
+  type::ResizeBilinear(GetTensorData<float>(input), GetTensorDims(input), \
+                       output_size_data, GetTensorDims({1, 1, 1, 2}),     \
+                       GetTensorData<float>(output), GetTensorDims(output))
+
+    if (kernel_type == kReference) {
+      TF_LITE_RESIZE_BILINEAR(reference_ops);
+    }
+    if (kernel_type == kGenericOptimized || kernel_type == kNeonOptimized) {
+      TF_LITE_RESIZE_BILINEAR(optimized_ops);
+    }
+#undef TF_LITE_RESIZE_BILINEAR
+  } else {
+    context->ReportError(context, "Inputs and outputs not all float types.");
+    return kTfLiteError;
+  }
+
+  return kTfLiteOk;
+}
+
+}  // namespace resize_bilinear
+
+TfLiteRegistration* Register_RESIZE_BILINEAR_REF() {
+  static TfLiteRegistration r = {
+      nullptr, nullptr, resize_bilinear::Prepare,
+      resize_bilinear::Eval<resize_bilinear::kReference>};
+  return &r;
+}
+
+TfLiteRegistration* Register_RESIZE_BILINEAR_GENERIC_OPT() {
+  static TfLiteRegistration r = {
+      nullptr, nullptr, resize_bilinear::Prepare,
+      resize_bilinear::Eval<resize_bilinear::kGenericOptimized>};
+  return &r;
+}
+
+TfLiteRegistration* Register_RESIZE_BILINEAR_NEON_OPT() {
+  static TfLiteRegistration r = {
+      nullptr, nullptr, resize_bilinear::Prepare,
+      resize_bilinear::Eval<resize_bilinear::kNeonOptimized>};
+  return &r;
+}
+
+TfLiteRegistration* Register_RESIZE_BILINEAR() {
+#ifdef USE_NEON
+  return Register_RESIZE_BILINEAR_NEON_OPT();
+#else
+  return Register_RESIZE_BILINEAR_GENERIC_OPT();
+#endif
+}
+
+}  // namespace builtin
+}  // namespace ops
+}  // namespace tflite