129 lines
4.7 KiB
C++
129 lines
4.7 KiB
C++
/* Copyright 2020 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 "tensorflow/lite/kernels/internal/reference/integer_ops/tanh.h"
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#include "tensorflow/lite/c/builtin_op_data.h"
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#include "tensorflow/lite/c/common.h"
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#include "tensorflow/lite/kernels/internal/common.h"
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#include "tensorflow/lite/kernels/internal/quantization_util.h"
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#include "tensorflow/lite/kernels/internal/reference/tanh.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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#include "tensorflow/lite/kernels/op_macros.h"
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namespace tflite {
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namespace ops {
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namespace micro {
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namespace activations {
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namespace {
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constexpr int kInputTensor = 0;
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constexpr int kOutputTensor = 0;
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struct OpData {
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int32_t input_zero_point;
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int32_t input_range_radius;
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int32_t input_multiplier;
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int input_left_shift;
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};
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TfLiteStatus CalculateArithmeticOpData(TfLiteContext* context, TfLiteNode* node,
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OpData* data) {
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const TfLiteTensor* input = GetInput(context, node, kInputTensor);
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TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
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TF_LITE_ENSURE_TYPES_EQ(context, input->type, output->type);
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if (input->type == kTfLiteInt8) {
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TF_LITE_ENSURE_EQ(context, output->params.zero_point, 0);
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// The number if input integer bits is set to be consistent with the
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// required value in reference_integer_ops::Tanh
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static constexpr int kInputIntegerBits = 4;
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const double input_real_multiplier =
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static_cast<double>(input->params.scale) *
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static_cast<double>(1 << (31 - kInputIntegerBits));
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const double q = std::frexp(input_real_multiplier, &data->input_left_shift);
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data->input_multiplier = static_cast<int32_t>(TfLiteRound(q * (1ll << 31)));
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data->input_range_radius =
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CalculateInputRadius(kInputIntegerBits, data->input_left_shift, 31);
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}
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return kTfLiteOk;
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}
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} // namespace
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TfLiteStatus TanhEval(TfLiteContext* context, TfLiteNode* node) {
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const TfLiteTensor* input = GetInput(context, node, kInputTensor);
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TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
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OpData data;
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CalculateArithmeticOpData(context, node, &data);
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if (input->type == kTfLiteFloat32) {
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switch (output->type) {
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case kTfLiteFloat32: {
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reference_ops::Tanh(GetTensorShape(input), GetTensorData<float>(input),
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GetTensorShape(output),
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GetTensorData<float>(output));
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return kTfLiteOk;
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}
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default:
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TF_LITE_KERNEL_LOG(context, "Input %s, output %s not supported.",
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TfLiteTypeGetName(input->type),
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TfLiteTypeGetName(output->type));
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return kTfLiteError;
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}
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} else if (input->type == kTfLiteInt8) {
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switch (output->type) {
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case kTfLiteInt8: {
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reference_integer_ops::Tanh(
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input->params.zero_point, data.input_range_radius,
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data.input_multiplier, data.input_left_shift,
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NumElements(input->dims), GetTensorData<int8_t>(input),
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GetTensorData<int8_t>(output));
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return kTfLiteOk;
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}
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default:
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TF_LITE_KERNEL_LOG(context, "Input %s, output %s not supported.",
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TfLiteTypeGetName(input->type),
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TfLiteTypeGetName(output->type));
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return kTfLiteError;
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}
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} else {
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TF_LITE_KERNEL_LOG(context, "Input %s, output %s not supported.",
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TfLiteTypeGetName(input->type),
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TfLiteTypeGetName(output->type));
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return kTfLiteError;
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}
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return kTfLiteOk;
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}
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} // namespace activations
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TfLiteRegistration* Register_TANH() {
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static TfLiteRegistration r = {/*init=*/nullptr,
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/*free=*/nullptr,
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/*prepare=*/nullptr,
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/*invoke=*/activations::TanhEval,
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/*profiling_string=*/nullptr,
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/*builtin_code=*/0,
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/*custom_name=*/nullptr,
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/*version=*/0};
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return &r;
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}
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} // namespace micro
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} // namespace ops
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} // namespace tflite
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