Add support for select (via tf.where) support to tflite.

PiperOrigin-RevId: 195734246

1 files changed, 125 insertions, 0 deletions

diff --git a/tensorflow/contrib/lite/kernels/select.cc b/tensorflow/contrib/lite/kernels/select.cc
new file mode 100644
index 0000000000..029ad9a709
--- /dev/null
+++ b/tensorflow/contrib/lite/kernels/select.cc
@@ -0,0 +1,125 @@
+/* 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/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"
+#include "tensorflow/contrib/lite/string_util.h"
+
+namespace tflite {
+namespace ops {
+namespace builtin {
+namespace select {
+
+constexpr int kInputTensorCondition = 0;
+constexpr int kInputTensorX = 1;
+constexpr int kInputTensorY = 2;
+constexpr int kOutputTensor = 0;
+
+TfLiteStatus SelectPrepare(TfLiteContext* context, TfLiteNode* node) {
+  TF_LITE_ENSURE_EQ(context, NumInputs(node), 3);
+  TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
+
+  TfLiteTensor* input_condition =
+      GetInput(context, node, kInputTensorCondition);
+  TfLiteTensor* input_x = GetInput(context, node, kInputTensorX);
+  TfLiteTensor* input_y = GetInput(context, node, kInputTensorY);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+
+  // Input must be bool.
+  TF_LITE_ENSURE(context, input_condition->type == kTfLiteBool);
+
+  // Input tensors must have the same type and size
+  TF_LITE_ENSURE_EQ(context, input_x->type, input_y->type);
+  TF_LITE_ENSURE(context, HaveSameShapes(input_x, input_y));
+  output->type = input_x->type;
+
+  // Either the same shape, or input_condition must be Rank 1 and match over the
+  // first dimension.
+  bool same_shape = HaveSameShapes(input_condition, input_x);
+  if (!same_shape && NumDimensions(input_condition) == 1) {
+    same_shape =
+        SizeOfDimension(input_condition, 0) == SizeOfDimension(input_x, 0);
+  }
+
+  TF_LITE_ENSURE(context, same_shape);
+
+  TfLiteIntArray* output_size = TfLiteIntArrayCopy(input_x->dims);
+  return context->ResizeTensor(context, output, output_size);
+}
+
+TfLiteStatus SelectEval(TfLiteContext* context, TfLiteNode* node) {
+  TfLiteTensor* input_condition =
+      GetInput(context, node, kInputTensorCondition);
+  TfLiteTensor* input_x = GetInput(context, node, kInputTensorX);
+  TfLiteTensor* input_y = GetInput(context, node, kInputTensorY);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+
+  bool is_rank_one = !HaveSameShapes(input_condition, input_x);
+
+#define TF_LITE_SELECT(type, op)                                          \
+  reference_ops::op(GetTensorData<bool>(input_condition),                 \
+                    GetTensorDims(input_condition),                       \
+                    GetTensorData<type>(input_x), GetTensorDims(input_x), \
+                    GetTensorData<type>(input_y), GetTensorDims(input_y), \
+                    GetTensorData<type>(output), GetTensorDims(output));
+
+#define TF_LITE_SWITCH(type, op)                                               \
+  switch (type) {                                                              \
+    break;                                                                     \
+    case kTfLiteBool:                                                          \
+      TF_LITE_SELECT(bool, op);                                                \
+      break;                                                                   \
+    case kTfLiteFloat32:                                                       \
+      TF_LITE_SELECT(float, op);                                               \
+      break;                                                                   \
+    case kTfLiteUInt8:                                                         \
+      TF_LITE_SELECT(uint8_t, op);                                             \
+      break;                                                                   \
+    case kTfLiteInt32:                                                         \
+      TF_LITE_SELECT(int32_t, op);                                             \
+      break;                                                                   \
+    case kTfLiteInt64:                                                         \
+      TF_LITE_SELECT(int64_t, op);                                             \
+      break;                                                                   \
+    default:                                                                   \
+      context->ReportError(context,                                            \
+                           "Does not support type other than bool|float|int"); \
+      return kTfLiteError;                                                     \
+  }
+
+  if (is_rank_one) {
+    TF_LITE_SWITCH(input_x->type, RankOneSelect);
+  } else {
+    TF_LITE_SWITCH(input_x->type, Select);
+  }
+
+#undef TF_LITE_SELECT
+#undef TF_LITE_SWITCH
+  return kTfLiteOk;
+}
+
+}  // namespace select
+
+TfLiteRegistration* Register_SELECT() {
+  static TfLiteRegistration r = {nullptr, nullptr, select::SelectPrepare,
+                                 select::SelectEval};
+  return &r;
+}
+
+}  // namespace builtin
+}  // namespace ops
+}  // namespace tflite