wehub-resource-sync
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 <cmath>
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#include "tensorflow/lite/core/c/common.h"
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#include "tensorflow/lite/kernels/internal/common.h"
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#include "tensorflow/lite/kernels/internal/reference/integer_ops/lut.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 exp {
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// This file has reference implementation of Exp.
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enum KernelType {
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kReference,
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};
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struct ExpContext {
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ExpContext(TfLiteContext* context, TfLiteNode* node) {
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input = GetInput(context, node, 0);
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output = GetOutput(context, node, 0);
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}
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const TfLiteTensor* input;
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TfLiteTensor* output;
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};
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struct OpData {
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union {
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int8_t lut_int8[LUTSize<int8_t>()];
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int16_t lut_int16[LUTSize<int16_t>()];
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};
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};
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void* Init(TfLiteContext* context, const char* buffer, size_t length) {
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return new OpData;
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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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OpData* data = static_cast<OpData*>(node->user_data);
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TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
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TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
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ExpContext op_context(context, node);
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const TfLiteTensor* input = op_context.input;
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TF_LITE_ENSURE(context, input != nullptr);
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TfLiteTensor* output = op_context.output;
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TfLiteIntArray* output_dims = TfLiteIntArrayCopy(input->dims);
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output->type = input->type;
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if (input->type == kTfLiteInt8) {
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LUTPopulate<int8_t>(
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input->params.scale, input->params.zero_point, output->params.scale,
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output->params.zero_point, [](float value) { return std::exp(value); },
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data->lut_int8);
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} else if (input->type == kTfLiteInt16) {
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TF_LITE_ENSURE_EQ(context, input->params.zero_point, 0);
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TF_LITE_ENSURE_EQ(context, output->params.zero_point, 0);
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LUTPopulate<int16_t>(
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input->params.scale, input->params.zero_point, output->params.scale,
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output->params.zero_point, [](float value) { return std::exp(value); },
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data->lut_int16);
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}
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return context->ResizeTensor(context, op_context.output, output_dims);
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}
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template <KernelType kernel_type>
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TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
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OpData* data = reinterpret_cast<OpData*>(node->user_data);
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ExpContext op_context(context, node);
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// TODO(kanlig): supports half, bfloat16, float64, complex64, and complex128.
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if (kernel_type == kReference) {
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switch (op_context.input->type) {
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case kTfLiteFloat32:
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reference_ops::Exp(GetTensorData<float>(op_context.input),
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NumElements(op_context.input),
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GetTensorData<float>(op_context.output));
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break;
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case kTfLiteInt8:
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reference_integer_ops::LookupTable(
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GetTensorData<int8_t>(op_context.input),
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NumElements(op_context.input), data->lut_int8,
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GetTensorData<int8_t>(op_context.output));
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break;
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case kTfLiteInt16:
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reference_integer_ops::LookupTable(
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GetTensorData<int16_t>(op_context.input),
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NumElements(op_context.input), data->lut_int16,
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GetTensorData<int16_t>(op_context.output));
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break;
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default:
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TF_LITE_KERNEL_LOG(context,
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"Type %d is currently not supported by Exp.",
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op_context.input->type);
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return kTfLiteError;
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}
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}
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return kTfLiteOk;
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}
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} // namespace exp
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TfLiteRegistration* Register_EXP_REF() {
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static TfLiteRegistration r = {exp::Init, exp::Free, exp::Prepare,
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exp::Eval<exp::kReference>};
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return &r;
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}
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// TODO(kanlig): add optimized implementation of Exp.
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TfLiteRegistration* Register_EXP() { return Register_EXP_REF(); }
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} // namespace builtin
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} // namespace ops
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} // namespace tflite
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