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/*
* 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"
namespace android {
namespace nn {
// executionMutex is used to protect concurrent access of non-threadsafe resources
// like gemmlowp::GemmContext.
// std::mutex is safe for pthreads on Android.
static std::mutex executionMutex;
bool fullyConnectedFloat32(const float* inputData, const Shape& inputShape,
const float* weightsData, const Shape& weightsShape,
const float* biasData, const Shape& biasShape,
int32_t activation,
float* outputData, const Shape& outputShape) {
float output_activation_min, output_activation_max;
CalculateActivationRangeFloat(activation, &output_activation_min,
&output_activation_max);
tflite::optimized_ops::FullyConnected(
inputData, convertShapeToDims(inputShape),
weightsData, convertShapeToDims(weightsShape),
biasData, convertShapeToDims(biasShape),
output_activation_min, output_activation_max,
outputData, convertShapeToDims(outputShape));
return true;
}
bool fullyConnectedQuant8(const uint8_t* inputData, const Shape& inputShape,
const uint8_t* weightsData, const Shape& weightsShape,
const int32_t* biasData, const Shape& biasShape,
int32_t activation,
uint8_t* outputData, const Shape& outputShape) {
int32_t inputOffset = -inputShape.offset;
int32_t weightsOffset = -weightsShape.offset;
int32_t outputOffset = outputShape.offset;
float real_multiplier = 0.0;
int32_t output_multiplier = 0;
int32_t output_shift = 0;
int32_t output_activation_min = 0;
int32_t output_activation_max = 0;
if (!GetQuantizedConvolutionMultipler(inputShape, weightsShape, biasShape,
outputShape, &real_multiplier) ||
!QuantizeMultiplierSmallerThanOne(real_multiplier, &output_multiplier,
&output_shift)) {
return false;
}
CalculateActivationRangeUint8(activation, outputShape,
&output_activation_min,
&output_activation_max);
static gemmlowp::GemmContext gemm_context;
// Prevent concurrent executions that access gemm_context.
std::unique_lock<std::mutex> lock(executionMutex);
// Alow gemmlowp automatically decide how many threads to use.
gemm_context.set_max_num_threads(0);
tflite::optimized_ops::FullyConnected(
inputData, convertShapeToDims(inputShape), inputOffset,
weightsData, convertShapeToDims(weightsShape), weightsOffset,
biasData, convertShapeToDims(biasShape),
outputOffset, output_multiplier, output_shift,
output_activation_min, output_activation_max,
outputData, convertShapeToDims(outputShape), &gemm_context);
return true;
}
} // namespace nn
} // namespace android
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