blob: 7f36dbfd0ab5b67c4fefe491b8dd29e6a5782346 [file] [log] [blame]
/*
* Copyright (C) 2017 The Android Open Source Project
*
* 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 "Operations.h"
#include "CpuOperationUtils.h"
#include "tensorflow/contrib/lite/kernels/internal/optimized/optimized_ops.h"
#include "Tracing.h"
namespace android {
namespace nn {
bool l2normFloat32(const float* inputData, const Shape& inputShape,
float* outputData, const Shape& outputShape) {
NNTRACE_COMP("optimized_ops::L2Normalization::float");
tflite::optimized_ops::L2Normalization<tflite::FusedActivationFunctionType::kNone>(
inputData, convertShapeToDims(inputShape),
outputData, convertShapeToDims(outputShape));
return true;
}
bool l2normQuant8(const uint8_t* inputData, const Shape& inputShape,
uint8_t* outputData, const Shape& outputShape) {
NNTRACE_COMP("optimized_ops::L2Normalization::uint8");
tflite::optimized_ops::L2Normalization(
inputData, convertShapeToDims(inputShape),
inputShape.offset,
outputData, convertShapeToDims(outputShape));
return true;
}
bool localResponseNormFloat32(const float* inputData, const Shape& inputShape,
int32_t radius, float bias, float alpha, float beta,
float* outputData, const Shape& outputShape) {
NNTRACE_COMP("optimized_ops::LocalResponseNormalization::float");
tflite::optimized_ops::LocalResponseNormalization(
inputData, convertShapeToDims(inputShape),
radius, bias, alpha, beta,
outputData, convertShapeToDims(outputShape));
return true;
}
} // namespace nn
} // namespace android