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