140 lines
4.6 KiB
C++
140 lines
4.6 KiB
C++
/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include <stddef.h>
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#include "tensorflow/lite/c/common.h"
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#include "tensorflow/lite/kernels/internal/reference/binary_function.h"
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#include "tensorflow/lite/kernels/internal/reference/reference_ops.h"
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#include "tensorflow/lite/kernels/internal/tensor.h"
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#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
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#include "tensorflow/lite/kernels/kernel_util.h"
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namespace tflite {
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namespace ops {
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namespace builtin {
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namespace logical {
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namespace {
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// Input/output tensor index.
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constexpr int kInputTensor1 = 0;
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constexpr int kInputTensor2 = 1;
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constexpr int kOutputTensor = 0;
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// Op data for logical op.
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struct OpData {
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bool requires_broadcast;
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};
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void* Init(TfLiteContext* context, const char* buffer, size_t length) {
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auto* data = new OpData;
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data->requires_broadcast = false;
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return data;
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}
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void Free(TfLiteContext* context, void* buffer) {
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delete reinterpret_cast<OpData*>(buffer);
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}
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TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
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TF_LITE_ENSURE_EQ(context, NumInputs(node), 2);
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TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
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// Reinterprete the opaque data provided by user.
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OpData* data = reinterpret_cast<OpData*>(node->user_data);
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const TfLiteTensor* input1 = GetInput(context, node, kInputTensor1);
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const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2);
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TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
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TF_LITE_ENSURE_TYPES_EQ(context, input1->type, input2->type);
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const TfLiteType type = input1->type;
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if (type != kTfLiteBool) {
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context->ReportError(context, "Logical ops only support bool type.");
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return kTfLiteError;
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}
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output->type = type;
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data->requires_broadcast = !HaveSameShapes(input1, input2);
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TfLiteIntArray* output_size = nullptr;
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if (data->requires_broadcast) {
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TF_LITE_ENSURE_OK(context, CalculateShapeForBroadcast(
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context, input1, input2, &output_size));
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} else {
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output_size = TfLiteIntArrayCopy(input1->dims);
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}
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return context->ResizeTensor(context, output, output_size);
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}
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TfLiteStatus LogicalImpl(TfLiteContext* context, TfLiteNode* node,
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bool (*func)(bool, bool)) {
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OpData* data = reinterpret_cast<OpData*>(node->user_data);
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const TfLiteTensor* input1 = GetInput(context, node, kInputTensor1);
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const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2);
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TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
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if (data->requires_broadcast) {
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reference_ops::BroadcastBinaryFunction4DSlow<bool, bool, bool>(
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GetTensorShape(input1), GetTensorData<bool>(input1),
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GetTensorShape(input2), GetTensorData<bool>(input2),
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GetTensorShape(output), GetTensorData<bool>(output), func);
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} else {
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reference_ops::BinaryFunction<bool, bool, bool>(
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GetTensorShape(input1), GetTensorData<bool>(input1),
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GetTensorShape(input2), GetTensorData<bool>(input2),
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GetTensorShape(output), GetTensorData<bool>(output), func);
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}
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return kTfLiteOk;
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}
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bool LogicalOr(bool x, bool y) { return x || y; }
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TfLiteStatus LogicalOrEval(TfLiteContext* context, TfLiteNode* node) {
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return LogicalImpl(context, node, LogicalOr);
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}
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bool LogicalAnd(bool x, bool y) { return x && y; }
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TfLiteStatus LogicalAndEval(TfLiteContext* context, TfLiteNode* node) {
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return LogicalImpl(context, node, LogicalAnd);
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}
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} // namespace
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} // namespace logical
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TfLiteRegistration* Register_LOGICAL_OR() {
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// Init, Free, Prepare, Eval are satisfying the Interface required by
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// TfLiteRegistration.
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static TfLiteRegistration r = {logical::Init, logical::Free, logical::Prepare,
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logical::LogicalOrEval};
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return &r;
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}
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TfLiteRegistration* Register_LOGICAL_AND() {
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// Init, Free, Prepare, Eval are satisfying the Interface required by
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// TfLiteRegistration.
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static TfLiteRegistration r = {logical::Init, logical::Free, logical::Prepare,
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logical::LogicalAndEval};
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return &r;
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}
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} // namespace builtin
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} // namespace ops
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} // namespace tflite
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