wehub-resource-sync
116 lines
3.5 KiB
C++
116 lines
3.5 KiB
C++
// Copyright 2021 Google LLC
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//
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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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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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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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#include <cmath>
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#include <cstdint>
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#include <type_traits>
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#include "tensorflow/lite/core/c/common.h"
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#include "tensorflow/lite/kernels/custom_ops_register.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 custom {
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namespace sign {
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// Performs common preparation for pointwise, unary ops, i.e., type checks and
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// output tensor resizing.
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TfLiteStatus PointwiseUnaryOpPrepare(TfLiteContext* context, TfLiteNode* node) {
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TF_LITE_ENSURE_EQ(context, tflite::NumInputs(node), 1);
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const TfLiteTensor* input = tflite::GetInput(context, node, 0);
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TfLiteTensor* output = tflite::GetOutput(context, node, 0);
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// Validate size and type constraints
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TF_LITE_ENSURE_TYPES_EQ(context, input->type, output->type);
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TfLiteIntArray* output_shape = TfLiteIntArrayCopy(input->dims);
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return context->ResizeTensor(context, output, output_shape);
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}
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// Applies the operator Op pointwise to data of type T.
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template <typename Op, typename T>
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TfLiteStatus PointwiseUnaryOpDoEval(
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const TfLiteTensor* input,
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TfLiteTensor* output) {
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const T* data = tflite::GetTensorData<T>(input);
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T* data_output = tflite::GetTensorData<T>(output);
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const int64_t num_elements = NumElements(input);
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for (int64_t i = 0; i < num_elements; ++i) {
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data_output[i] = Op::template Eval<T>(data[i]);
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}
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return TfLiteStatus::kTfLiteOk;
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}
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// A generic evaluation function where the actual data processing is handled
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// by the Op::Eval<T> function.
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template <typename Op>
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TfLiteStatus PointwiseUnaryOpEval(TfLiteContext* context, TfLiteNode* node) {
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const TfLiteTensor* input = tflite::GetInput(context, node, 0);
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TfLiteTensor* output = tflite::GetOutput(context, node, 0);
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switch (output->type) {
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case kTfLiteFloat32:
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TF_LITE_ENSURE_OK(context,
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(PointwiseUnaryOpDoEval<Op, float>(input, output)));
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break;
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case kTfLiteFloat64:
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TF_LITE_ENSURE_OK(context,
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(PointwiseUnaryOpDoEval<Op, double>(input, output)));
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break;
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default: {
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TF_LITE_KERNEL_LOG(context, "Unsupported datatype for sign output: %s",
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TfLiteTypeGetName(output->type));
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return TfLiteStatus::kTfLiteError;
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}
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}
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return TfLiteStatus::kTfLiteOk;
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}
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// Operator that computes the sign function.
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struct Sign {
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template <typename T>
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static T Eval(T x) {
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if constexpr (std::is_floating_point_v<T>) {
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if (std::isnan(x)) {
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return x;
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}
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}
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if (x > 0) {
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return 1;
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}
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if (x < 0) {
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return -1;
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}
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return 0;
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}
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};
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} // namespace sign
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TfLiteRegistration* Register_SIGN() {
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static TfLiteRegistration r = {nullptr, nullptr,
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sign::PointwiseUnaryOpPrepare,
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sign::PointwiseUnaryOpEval<sign::Sign>};
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return &r;
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}
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} // namespace custom
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} // namespace ops
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} // namespace tflite
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