MNN/source/backend/vulkan/execution/VulkanReshape.cpp

139 lines
6.3 KiB
C++

//
// VulkanReshape.cpp
// MNN
//
// Created by MNN on 2019/01/31.
// Copyright © 2018, Alibaba Group Holding Limited
//
#include "backend/vulkan/execution/VulkanReshape.hpp"
#include "core/Macro.h"
#include "core/TensorUtils.hpp"
namespace MNN {
VulkanReshape::VulkanReshape(const Op* op, Backend* bn) : VulkanBasicExecution(bn), mStorage(2) {
mDimType = MNN_DATA_FORMAT_NCHW;
if (op->type() == OpType_Reshape) {
mDimType = op->main_as_Reshape()->dimType();
}
auto vkBackend = static_cast<VulkanBackend*>(bn);
mTensorConvert0.reset(new VulkanImageConverter(vkBackend));
mTensorConvert1.reset(new VulkanImageConverter(vkBackend));
}
VulkanReshape::VulkanReshape(Backend* bn) : VulkanBasicExecution(bn), mDimType(MNN_DATA_FORMAT_NCHW), mStorage(2) {
auto vkBackend = static_cast<VulkanBackend*>(bn);
mTensorConvert0.reset(new VulkanImageConverter(vkBackend));
mTensorConvert1.reset(new VulkanImageConverter(vkBackend));
}
VulkanReshape::~VulkanReshape() {
}
ErrorCode VulkanReshape::setLayout(const Tensor* input, const Tensor* output) {
int totalSize = 1;
mWrapTensorForInput.buffer().type = input->buffer().type;
mWrapTensorForOutput.buffer().type = output->buffer().type;
int extraMulti = 1;
int extraDivide = 1;
if (TensorUtils::getDescribe(input)->dimensionFormat == MNN_DATA_FORMAT_NC4HW4) {
TensorUtils::getDescribe(&mWrapTensorForInput)->dimensionFormat = MNN_DATA_FORMAT_NCHW;
TensorUtils::getDescribe(&mWrapTensorForOutput)->dimensionFormat = MNN_DATA_FORMAT_NCHW;
extraMulti = ALIGN_UP4(input->channel());
extraDivide = input->channel();
} else {
TensorUtils::getDescribe(&mWrapTensorForInput)->dimensionFormat = MNN_DATA_FORMAT_NHWC;
TensorUtils::getDescribe(&mWrapTensorForOutput)->dimensionFormat = MNN_DATA_FORMAT_NHWC;
}
for (int i = 0; i < input->buffer().dimensions; ++i) {
totalSize *= input->buffer().dim[i].extent;
}
mStorage.buffer().dim[0].extent = 1;
mStorage.buffer().dim[1].extent = totalSize / extraDivide * extraMulti;
backend()->onAcquireBuffer(&mStorage, Backend::DYNAMIC);
TensorUtils::copyShape(input, &mWrapTensorForInput);
if (TensorUtils::getDescribe(input)->dimensionFormat == MNN_DATA_FORMAT_NC4HW4 &&
mDimType == MNN_DATA_FORMAT_NHWC) {
TensorUtils::getDescribe(&mWrapTensorForInput)->dimensionFormat = MNN_DATA_FORMAT_NHWC;
if (mWrapTensorForInput.buffer().dimensions == 4) {
mWrapTensorForInput.buffer().dim[1].extent = mWrapTensorForInput.buffer().dim[2].extent;
mWrapTensorForInput.buffer().dim[2].extent = mWrapTensorForInput.buffer().dim[3].extent;
mWrapTensorForInput.buffer().dim[3].extent = mWrapTensorForInput.buffer().dim[1].extent;
}
}
mWrapTensorForInput.buffer().device = mStorage.buffer().device;
TensorUtils::setLinearLayout(&mWrapTensorForInput);
TensorUtils::copyShape(output, &mWrapTensorForOutput);
if (TensorUtils::getDescribe(input)->dimensionFormat == MNN_DATA_FORMAT_NC4HW4 &&
mDimType == MNN_DATA_FORMAT_NHWC) {
TensorUtils::getDescribe(&mWrapTensorForOutput)->dimensionFormat = MNN_DATA_FORMAT_NHWC;
if (mWrapTensorForOutput.buffer().dimensions == 4) {
mWrapTensorForOutput.buffer().dim[1].extent = mWrapTensorForOutput.buffer().dim[2].extent;
mWrapTensorForOutput.buffer().dim[2].extent = mWrapTensorForOutput.buffer().dim[3].extent;
mWrapTensorForOutput.buffer().dim[3].extent = mWrapTensorForOutput.buffer().dim[1].extent;
}
}
mWrapTensorForOutput.buffer().device = mStorage.buffer().device;
TensorUtils::setLinearLayout(&mWrapTensorForOutput);
return NO_ERROR;
}
ErrorCode VulkanReshape::onEncode(const std::vector<Tensor*>& inputs, const std::vector<Tensor*>& outputs,
const VulkanCommandPool::Buffer* cmdBuffer) {
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 &&
TensorUtils::getDescribe(output)->dimensionFormat != MNN_DATA_FORMAT_NC4HW4) {
// the layout of input and output tensor are all buffer, then copy buffer directly
auto inputBuffer = reinterpret_cast<VkBuffer>(input->deviceId());
auto outputBuffer = reinterpret_cast<VkBuffer>(output->deviceId());
cmdBuffer->barrierSource(inputBuffer, 0, input->size());
const VkBufferCopy copyRegion = {0, 0, static_cast<VkDeviceSize>(input->size())};
vkCmdCopyBuffer(cmdBuffer->get(), inputBuffer, outputBuffer, 1, &copyRegion);
} else {
this->setLayout(input, output);
// encode tensor convert
mTensorConvert0->encodeTensorToBuffer(
input, reinterpret_cast<VkBuffer>(mWrapTensorForInput.deviceId()), mStorage.size(), 0,
TensorUtils::getDescribe(&mWrapTensorForInput)->dimensionFormat, cmdBuffer);
cmdBuffer->barrierSource(reinterpret_cast<VkBuffer>(mWrapTensorForInput.deviceId()), 0,
mWrapTensorForInput.size());
mTensorConvert1->encodeBufferToTensor(
reinterpret_cast<VkBuffer>(mWrapTensorForOutput.deviceId()), output, mStorage.size(), 0,
TensorUtils::getDescribe(&mWrapTensorForOutput)->dimensionFormat, cmdBuffer);
backend()->onReleaseBuffer(&mStorage, Backend::DYNAMIC);
}
return NO_ERROR;
}
class VulkanReshapeCreator : public VulkanBackend::Creator {
public:
virtual VulkanBasicExecution* onCreate(const std::vector<Tensor*>& inputs, const std::vector<Tensor*>& outputs, const MNN::Op* op, Backend* bn) const override {
return new VulkanReshape(op, bn);
}
};
static bool gResistor = []() {
VulkanBackend::addCreator(OpType_Reshape, new VulkanReshapeCreator);
VulkanBackend::addCreator(OpType_Squeeze, new VulkanReshapeCreator);
VulkanBackend::addCreator(OpType_Unsqueeze, new VulkanReshapeCreator);
VulkanBackend::addCreator(OpType_ExpandDims, new VulkanReshapeCreator);
return true;
}();
} // namespace MNN