mirror of https://github.com/alibaba/MNN.git
71 lines
2.6 KiB
C++
71 lines
2.6 KiB
C++
//
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// ShapeGridSample.cpp
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// MNN
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//
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// Created by MNN on 2021/03/24.
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// Copyright © 2018, Alibaba Group Holding Limited
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//
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#include "shape/SizeComputer.hpp"
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#include "core/Macro.h"
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namespace MNN {
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class GridSampleSizeComputer : public SizeComputer {
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virtual bool onComputeSize(const MNN::Op *op, const std::vector<Tensor *> &inputs,
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const std::vector<Tensor *> &outputs) const override {
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// https://pytorch.org/docs/1.7.1/nn.functional.html?highlight=grid_sample#torch.nn.functional.grid_sample
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// inputs[0] is input, inputs[1] is grid
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MNN_ASSERT(2 <= inputs.size());
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MNN_ASSERT(1 == outputs.size());
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auto &ibInput0 = inputs[0]->buffer();
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auto &ob = outputs[0]->buffer();
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ob.type = ibInput0.type;
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TensorUtils::getDescribe(outputs[0])->dimensionFormat = TensorUtils::getDescribe(
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inputs[0])->dimensionFormat;
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if (inputs.size() > 2) {
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// For Grad, just copy the shape
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ob.dimensions = inputs[2]->length(0);
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auto shapePtr = inputs[2]->host<int>();
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for (int i=0; i<ob.dimensions; ++i) {
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ob.dim[i].extent = shapePtr[i];
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}
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return true;
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}
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int input_dim = inputs[0]->buffer().dimensions;
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int grid_dim = inputs[1]->buffer().dimensions;
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MNN_ASSERT((4 == input_dim && 4 == grid_dim) || (5 == input_dim && 5 == grid_dim));
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if (inputs[0]->buffer().dim[0].extent != inputs[1]->buffer().dim[0].extent) {
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return false;
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}
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MNN_ASSERT(grid_dim - 2 == inputs[1]->buffer().dim[grid_dim - 1].extent);
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auto &ibInput1 = inputs[1]->buffer();
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ob.dimensions = ibInput1.dimensions;
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ob.dim[0].extent = ibInput0.dim[0].extent;
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ob.dim[1].extent = ibInput0.dim[1].extent;
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ob.dim[2].extent = ibInput1.dim[1].extent;
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ob.dim[3].extent = ibInput1.dim[2].extent;
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if (grid_dim == 5) {
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ob.dim[4].extent = ibInput1.dim[3].extent;
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}
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return true;
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}
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virtual float onComputeFlops(const MNN::Op *op, const std::vector<Tensor *> &inputs,
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const std::vector<Tensor *> &outputs) const override {
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auto gridSampleParam = op->main_as_GridSample();
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if (gridSampleParam->mode() == MNN::SampleMode_BILINEAR) {
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return 4 * SizeComputer::onComputeFlops(op, inputs, outputs);
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}
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return SizeComputer::onComputeFlops(op, inputs, outputs);
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}
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};
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REGISTER_SHAPE_INPUTS(GridSampleSizeComputer, OpType_GridSample, {2});
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} // namespace MNN
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