MNN/source/backend/cpu/CPUReshape.cpp

112 lines
4.4 KiB
C++

//
// CPUReshape.cpp
// MNN
//
// Created by MNN on 2018/07/18.
// Copyright © 2018, Alibaba Group Holding Limited
//
#include "backend/cpu/CPUReshape.hpp"
#include "backend/cpu/CPUBackend.hpp"
#include "backend/cpu/compute/CommonOptFunction.h"
#include "core/Macro.h"
#include "core/TensorUtils.hpp"
namespace MNN {
CPUReshape::CPUReshape(Backend *b, MNN_DATA_FORMAT midFormat) : MNN::Execution(b), mStorage(2) {
mMidFormat = midFormat;
}
ErrorCode CPUReshape::onResize(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
MNN_ASSERT(1 == inputs.size() || 2 == inputs.size());
MNN_ASSERT(1 == outputs.size());
auto input = inputs[0];
auto output = outputs[0];
if (TensorUtils::getDescribe(input)->dimensionFormat != MNN_DATA_FORMAT_NC4HW4) {
return NO_ERROR;
}
int totalSize = 1;
for (int i = 0; i < input->buffer().dimensions; ++i) {
totalSize *= input->buffer().dim[i].extent;
}
TensorUtils::getDescribe(&mStorage)->dimensionFormat = MNN_DATA_FORMAT_NCHW;
mStorage.buffer().dim[0].extent = 1;
mStorage.buffer().dim[1].extent = totalSize;
mStorage.buffer().dimensions = 2;
mStorage.buffer().type = input->getType();
backend()->onAcquireBuffer(&mStorage, Backend::DYNAMIC);
backend()->onReleaseBuffer(&mStorage, Backend::DYNAMIC);
auto convertTensorMeta = [&](const Tensor* tensor, Tensor* wrapTensor) {
wrapTensor->buffer().host = mStorage.buffer().host;
wrapTensor->buffer().dimensions = tensor->dimensions();
wrapTensor->buffer().type = tensor->buffer().type;
TensorUtils::getDescribe(wrapTensor)->dimensionFormat = mMidFormat;
auto tensorFormat = TensorUtils::getDescribe(tensor)->dimensionFormat;
bool originCaffeFormat = (tensorFormat == MNN_DATA_FORMAT_NCHW || tensorFormat == MNN_DATA_FORMAT_NC4HW4);
bool wrapCaffeFormat = (mMidFormat == MNN_DATA_FORMAT_NCHW || mMidFormat == MNN_DATA_FORMAT_NC4HW4);
bool originTfFormat = (tensorFormat == MNN_DATA_FORMAT_NHWC || tensorFormat == MNN_DATA_FORMAT_NHWC4);
bool wrapTfFormat = (mMidFormat == MNN_DATA_FORMAT_NHWC || mMidFormat == MNN_DATA_FORMAT_NHWC4);
if ((originCaffeFormat && wrapCaffeFormat) || (originTfFormat && wrapTfFormat)) {
TensorUtils::copyShape(tensor, wrapTensor);
} else if (originCaffeFormat && wrapTfFormat) {
for (int i = 1; i < wrapTensor->dimensions() - 1; ++i) {
wrapTensor->setLength(i, tensor->length(i + 1));
}
wrapTensor->setLength(0, tensor->length(0));
wrapTensor->setLength(wrapTensor->dimensions() - 1, tensor->length(1));
} else if (originTfFormat && wrapCaffeFormat) {
for (int i = 2; i < wrapTensor->dimensions(); ++i) {
wrapTensor->setLength(i, tensor->length(i - 1));
}
wrapTensor->setLength(0, tensor->length(0));
wrapTensor->setLength(1, tensor->length(tensor->dimensions() - 1));
} else {
// will not reach here
MNN_ASSERT(false);
}
TensorUtils::setLinearLayout(wrapTensor);
};
convertTensorMeta(input, &mWrapTensorForInput);
convertTensorMeta(output, &mWrapTensorForOutput);
return NO_ERROR;
}
ErrorCode CPUReshape::onExecute(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
MNN_ASSERT(1 == inputs.size() || 2 == inputs.size());
MNN_ASSERT(1 == outputs.size());
if (TensorUtils::getDescribe(inputs[0])->dimensionFormat != MNN_DATA_FORMAT_NC4HW4) {
auto outputPtr = outputs[0]->host<uint8_t>();
auto inputPtr = inputs[0]->host<uint8_t>();
auto totalSize = inputs[0]->size();
::memcpy(outputPtr, inputPtr, totalSize);
return NO_ERROR;
}
auto input = inputs[0];
auto output = outputs[0];
backend()->onCopyBuffer(input, &mWrapTensorForInput);
backend()->onCopyBuffer(&mWrapTensorForOutput, output);
return NO_ERROR;
}
class CPUReshapeCreator : public CPUBackend::Creator {
public:
virtual Execution *onCreate(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs,
const MNN::Op *op, Backend *backend) const override {
return new CPUReshape(backend, op->main_as_Reshape()->dimType());
}
};
REGISTER_CPU_OP_CREATOR(CPUReshapeCreator, OpType_Reshape);
} // namespace MNN