mirror of https://github.com/alibaba/MNN.git
68 lines
2.5 KiB
C++
68 lines
2.5 KiB
C++
//
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// CPUMatrixBandPart.cpp
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// MNN
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//
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// Created by MNN on 2019/09/17.
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// Copyright © 2018, Alibaba Group Holding Limited
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//
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#include "backend/cpu/CPUMatrixBandPart.hpp"
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#include "backend/cpu/compute/ConvOpt.h"
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#include "core/TensorUtils.hpp"
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#include "core/Macro.h"
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namespace MNN {
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ErrorCode CPUMatrixBandPart::onResize(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
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MNN_ASSERT(3 == inputs.size());
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auto dimensions = inputs[0]->dimensions();
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auto height = inputs[0]->length(dimensions - 2);
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auto width = inputs[0]->length(dimensions - 1);
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mMask.reset(Tensor::createDevice<float>({1, height*width}, Tensor::CAFFE_C4));
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auto res = backend()->onAcquireBuffer(mMask.get(), Backend::DYNAMIC);
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if (!res) {
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return OUT_OF_MEMORY;
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}
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backend()->onReleaseBuffer(mMask.get(), Backend::DYNAMIC);
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return NO_ERROR;
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}
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ErrorCode CPUMatrixBandPart::onExecute(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
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// Generate Mask
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auto lower = inputs[1]->host<int32_t>()[0];
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auto upper = inputs[2]->host<int32_t>()[0];
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auto maskPtr = mMask->host<float>();
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auto dimensions = inputs[0]->dimensions();
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auto height = inputs[0]->length(dimensions - 2);
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auto width = inputs[0]->length(dimensions - 1);
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for (int y = 0; y < height; ++y) {
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auto maskY = maskPtr + y * width;
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for (int x = 0; x < width; ++x) {
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bool valid = (lower < 0 || (y - x) <= lower) && (upper < 0 || (x - y) <= upper);
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maskY[x] = valid ? 1.0f : 0.0f;
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}
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}
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// Run Mul
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auto outputPtr = outputs[0]->host<float>();
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auto inputPtr = inputs[0]->host<float>();
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int outside = 1;
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for (int i = 0; i < inputs[0]->dimensions() - 2; ++i) {
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outside *= inputs[0]->length(i);
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}
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auto inside = height * width;
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for (int i = 0; i < outside; ++i) {
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MNNMatrixProdCommon(outputPtr + i * inside, inputPtr + i * inside, maskPtr, inside, 0, 0, 0, 1);
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}
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return NO_ERROR;
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}
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class CPUMatrixBandPartCreator : public CPUBackend::Creator {
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public:
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virtual Execution *onCreate(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs,
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const MNN::Op *op, Backend *backend) const override {
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return new CPUMatrixBandPart(backend);
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}
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};
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REGISTER_CPU_OP_CREATOR(CPUMatrixBandPartCreator, OpType_MatrixBandPart);
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} // namespace MNN
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