2019-12-27 22:16:57 +08:00
|
|
|
//
|
|
|
|
// ShapeBroadcastTo.cpp
|
|
|
|
// MNN
|
|
|
|
//
|
|
|
|
// Created by MNN on 2019/12/2.
|
|
|
|
// Copyright © 2018, Alibaba Group Holding Limited
|
|
|
|
//
|
|
|
|
|
|
|
|
#include "core/Macro.h"
|
|
|
|
#include "core/SizeComputer.hpp"
|
|
|
|
#include "core/TensorUtils.hpp"
|
|
|
|
|
|
|
|
namespace MNN {
|
|
|
|
|
|
|
|
class ShapeBroadcastTo : public SizeComputer {
|
|
|
|
virtual bool onComputeSize(const MNN::Op* op, const std::vector<Tensor*>& inputs,
|
|
|
|
const std::vector<Tensor*>& outputs) const override {
|
|
|
|
MNN_ASSERT(inputs.size() == 2);
|
|
|
|
MNN_ASSERT(outputs.size() == 1);
|
|
|
|
auto input = inputs[0];
|
|
|
|
auto shape = inputs[1];
|
|
|
|
auto output = outputs[0];
|
2020-02-26 09:57:17 +08:00
|
|
|
output->buffer().dimensions = shape->elementSize();
|
|
|
|
const int dimension = output->dimensions();
|
2019-12-27 22:16:57 +08:00
|
|
|
const int* shapeData = shape->host<int>();
|
|
|
|
for (int i = 0; i < dimension; ++i) {
|
|
|
|
output->setLength(i, shapeData[i]);
|
|
|
|
}
|
|
|
|
output->buffer().type = input->buffer().type;
|
|
|
|
TensorUtils::getDescribe(output)->dimensionFormat = TensorUtils::getDescribe(input)->dimensionFormat;
|
2020-02-26 09:57:17 +08:00
|
|
|
if (output->dimensions() != input->dimensions()) {
|
|
|
|
if (output->elementSize() != input->elementSize()) {
|
|
|
|
MNN_ERROR("Don't support dimension not the same and size not the same for BroadcastTo\n");
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
}
|
2019-12-27 22:16:57 +08:00
|
|
|
return true;
|
|
|
|
}
|
|
|
|
};
|
|
|
|
|
|
|
|
REGISTER_SHAPE_INPUTS(ShapeBroadcastTo, OpType_BroadcastTo, {1});
|
|
|
|
|
|
|
|
} // namespace MNN
|