mirror of https://github.com/alibaba/MNN.git
94 lines
4.6 KiB
C++
94 lines
4.6 KiB
C++
//
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// ShapeAttention.cpp
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// MNN
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//
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// Created by MNN on 2023/09/10.
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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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#include "core/TensorUtils.hpp"
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namespace MNN {
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#ifdef MNN_SUPPORT_TRANSFORMER_FUSE
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class FmhaV2SizeComputer : 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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auto input0 = inputs[0], output0 = outputs[0];
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MNN_ASSERT(inputs.size() == 1);
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MNN_ASSERT(input0->buffer().dimensions == 3);
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output0->buffer().dim[0].extent = input0->buffer().dim[0].extent;
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output0->buffer().dim[1].extent = input0->buffer().dim[1].extent;
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output0->buffer().dim[2].extent = input0->buffer().dim[2].extent/3;
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output0->buffer().dimensions = 3;
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//MNN_PRINT("fmhaV2 shape:%d %d, %d %d %d %d %d\n", input0->buffer().dimensions, output0->buffer().dimensions, input0->buffer().dim[0].extent, input0->buffer().dim[1].extent, input0->buffer().dim[2].extent, input0->buffer().dim[3].extent, input0->buffer().dim[4].extent);
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//MNN_ASSERT(input0->buffer().dim[3].extent == 3);
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output0->buffer().type = input0->buffer().type;
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TensorUtils::getDescribe(output0)->dimensionFormat = TensorUtils::getDescribe(input0)->dimensionFormat;
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//printf("fmhaV2 shape:%d %d, %d %d %d\n", input0->buffer().dimensions, output0->buffer().dimensions, input0->buffer().dim[0].extent, input0->buffer().dim[1].extent, input0->buffer().dim[2].extent);
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return true;
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}
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};
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class FmhcaSizeComputer : 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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MNN_ASSERT(inputs.size() == 2);
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MNN_ASSERT(outputs.size() == 1);
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auto input0 = inputs[0];
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auto input1 = inputs[1];
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auto output0 = outputs[0];
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MNN_ASSERT(input0->buffer().dimensions == 3);
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MNN_ASSERT(input1->buffer().dimensions == 3);
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output0->buffer().dim[0].extent = input0->buffer().dim[0].extent;
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output0->buffer().dim[1].extent = input0->buffer().dim[1].extent;
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output0->buffer().dim[2].extent = input0->buffer().dim[2].extent;
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output0->buffer().dimensions = 3;
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//MNN_ASSERT(input1->buffer().dim[0].extent == input0->buffer().dim[0].extent);
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//MNN_ASSERT(input1->buffer().dim[2].extent == input0->buffer().dim[2].extent);
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//MNN_ASSERT(input1->buffer().dim[4].extent == input0->buffer().dim[3].extent);
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output0->buffer().type = input0->buffer().type;
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TensorUtils::getDescribe(output0)->dimensionFormat = TensorUtils::getDescribe(input0)->dimensionFormat;
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//printf("fmhca shape:%d %d %d, %d %d %d\n", input0->buffer().dimensions, input1->buffer().dimensions, output0->buffer().dimensions, input0->buffer().dim[0].extent, input0->buffer().dim[1].extent, input0->buffer().dim[2].extent);
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return true;
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}
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};
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class AttentionSizeComputer : 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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auto input = inputs[0], output = outputs[0];
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MNN_ASSERT(input->buffer().dimensions == 4);
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output->buffer().dim[0].extent = input->buffer().dim[0].extent;
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output->buffer().dim[1].extent = input->buffer().dim[1].extent;
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output->buffer().dim[2].extent = input->buffer().dim[2].extent * input->buffer().dim[3].extent;
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output->buffer().dimensions = 3;
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output->buffer().type = input->buffer().type;
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TensorUtils::getDescribe(output)->dimensionFormat = TensorUtils::getDescribe(input)->dimensionFormat;
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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, const std::vector<Tensor*>& outputs) const override {
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auto seqLen = static_cast<float>(outputs[0]->length(1));
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auto headDim = static_cast<float>(outputs[0]->length(2));
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float flops = 0.f;
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// qk + qkv
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flops += (2 * seqLen * headDim * seqLen);
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// softmax
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flops += (seqLen * seqLen);
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return flops / FLOPS_M;
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}
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};
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REGISTER_SHAPE_INPUTS_TRANSFORMER_FUSE(FmhaV2SizeComputer, OpType_FmhaV2);
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REGISTER_SHAPE_INPUTS_TRANSFORMER_FUSE(FmhcaSizeComputer, OpType_Fmhca);
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REGISTER_SHAPE_INPUTS_TRANSFORMER_FUSE(AttentionSizeComputer, OpType_Attention);
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#endif
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} // namespace MNN
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