mirror of https://github.com/alibaba/MNN.git
71 lines
2.3 KiB
C++
71 lines
2.3 KiB
C++
//
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// ShapeRange.cpp
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// MNN
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//
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// Created by MNN on 2019/01/10.
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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 "math.h"
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namespace MNN {
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template <typename T>
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static int computeSize(const MNN::Op* op, const std::vector<Tensor*>& inputs, const std::vector<Tensor*>& outputs) {
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Tensor* start_in = inputs[0];
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Tensor* limit_in = inputs[1];
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Tensor* delta_in = inputs[2];
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MNN_ASSERT((1 == start_in->buffer().dimensions) || (0 == start_in->buffer().dimensions));
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MNN_ASSERT((1 == limit_in->buffer().dimensions) || (0 == limit_in->buffer().dimensions));
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MNN_ASSERT((1 == delta_in->buffer().dimensions) || (0 == delta_in->buffer().dimensions));
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const float start = (float)start_in->host<T>()[0];
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const float limit = (float)limit_in->host<T>()[0];
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const float delta = (float)delta_in->host<T>()[0];
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MNN_ASSERT(0 != delta);
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if (delta > 0) {
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if (limit < start) {
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return 0;
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}
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} else {
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if (limit > start) {
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return 0;
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}
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}
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int32_t size = ceilf(fabsf((limit - start) / delta));
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return (int)size;
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}
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class RangeComputer : 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() == 3);
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int output_size = 0;
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switch (inputs[0]->getType().code) {
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case halide_type_int:
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output_size = computeSize<int32_t>(op, inputs, outputs);
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outputs[0]->setType(MNN::DataType_DT_INT32);
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break;
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case halide_type_float:
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output_size = computeSize<float>(op, inputs, outputs);
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outputs[0]->setType(MNN::DataType_DT_FLOAT);
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break;
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default:
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MNN_ASSERT(false); // unsupported type
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}
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outputs[0]->buffer().dimensions = 1;
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outputs[0]->buffer().dim[0].extent = output_size;
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TensorUtils::getDescribe(outputs[0])->dimensionFormat = TensorUtils::getDescribe(inputs[0])->dimensionFormat;
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return true;
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}
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};
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REGISTER_SHAPE_INPUTS(RangeComputer, OpType_Range, (std::vector<int>{0, 1, 2}));
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} // namespace MNN
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