2022-08-05 12:50:34 +08:00
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#pragma once
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2022-08-22 15:01:03 +08:00
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#include "core/blob.h"
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2022-08-05 12:50:34 +08:00
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#include "core/object.h"
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#include "core/ref.h"
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2022-08-07 21:12:17 +08:00
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namespace infini {
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2022-08-05 12:50:34 +08:00
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2022-08-15 15:08:56 +08:00
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class TensorBaseObj;
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class TensorObj;
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class OperatorObj;
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class GraphObj;
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class RuntimeObj;
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class BlobObj;
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using TensorBase = Ref<TensorBaseObj>;
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using Tensor = Ref<TensorObj>;
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using Operator = Ref<OperatorObj>;
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using Graph = Ref<GraphObj>;
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using Runtime = Ref<RuntimeObj>;
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using Blob = Ref<BlobObj>;
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using TensorVec = vector<Tensor>;
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using OpVec = vector<Operator>;
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using VType = uint32_t;
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enum class DataType {
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Float32,
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UInt32,
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};
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class TensorBaseObj : public Object {
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public:
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// enum TensorType {
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// Input,
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// Weight,
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// Invalid,
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// NotCounted,
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// };
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protected:
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int dim;
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DataType dtype;
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vector<WRef<TensorBaseObj>> inputOf;
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WRef<TensorBaseObj> outputOf;
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Blob data;
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// ComputeState computed;
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// static int random_seed[256 * 16];
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// static bool random_inited;
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public:
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TensorBaseObj(int dim, DataType dtype);
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virtual ~TensorBaseObj() {}
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void dataMalloc(const Blob &blob) {
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IT_ASSERT(data == nullptr);
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data = blob;
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}
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Blob getDataPtr() const { return data; }
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template <typename T> T getDataRawPtr() const {
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IT_ASSERT(data != nullptr);
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return data->getPtr<T>();
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}
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VType getData(size_t offset) const;
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DataType getDType() const { return dtype; }
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// uint64_t getHash() const { return hash; }
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// void setInputOf(const OpVec &ops) {
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// inputOf.clear();
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// for (const auto &op : ops)
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// inputOf.emplace_back(op);
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// }
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// void addInputOf(Operator op) { inputOf.emplace_back(op); }
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// void setOutputOf(Operator op) { outputOf = op; }
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// const OpVec &getInputOf() { return inputOf; }
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// Operator *getOutputOf() { return outputOf; }
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// std::pair<Operator *, int> getOutputOfWithIndex();
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// const Dim &getDims() const { return dims; }
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// void setDims(const Dim &dms) { dims = dms; }
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// bool dataRand(int seed = 0) {
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// if (data == nullptr)
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// data = new VType[size()];
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// if (!random_inited)
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// initFastrand();
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// // srand(seed);
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// // faster rand generator; parallel
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// size_t iEnd = size();
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// // std::cerr << "Init beginned " << std::endl;
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// #pragma omp parallel for
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// for (size_t i = 0; i < iEnd; ++i)
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// data[i] = fastrand(random_seed[omp_get_thread_num() * 16]) %
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// 10000;
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// // std::cerr << "Init finished" << std::endl;
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// computed = ComputedFull;
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// return true;
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// }
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// bool setScalar(VType val) {
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// if (data == nullptr || !dims.empty())
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// return false;
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// data[0] = val;
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// return true;
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// }
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// bool setData(const Dim &ds, VType val) {
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// if (data == nullptr || ds.size() != dims.size())
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// return false;
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// data[getOffset(ds)] = val;
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// return true;
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// }
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// bool setData(size_t pos, VType val) {
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// if (data == nullptr || pos >= size())
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// return false;
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// data[pos] = val;
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// return true;
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// }
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// VType getScalar() { return data == nullptr ? 0 : data[0]; }
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// VType getData(const Dim &ds) {
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// assert(data != nullptr);
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// auto offset = getOffset(ds);
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// return offset == (size_t)-1 ? 0 : data[getOffset(ds)];
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// }
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// VType getData(size_t pos) {
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// assert(data != nullptr);
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// assert(pos < size());
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// return data[pos];
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// }
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// VType *getDataPtr() const { return data; }
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// size_t getOffset(const Dim &ds) {
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// auto nDim = ds.size();
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// assert(dims.size() == nDim);
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// if (ds.empty())
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// return 0;
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// for (size_t i = 0; i < nDim; ++i)
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// if (ds[i] < 0 || ds[i] >= dims[i])
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// return (size_t)-1;
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// size_t idx = ds[0];
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// size_t dm = 0;
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// while (++dm < nDim)
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// idx = idx * dims[dm] + ds[dm];
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// return idx;
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// }
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// VType getBroadcastData(const Dim &ds) {
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// assert(data != nullptr);
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// auto offset = getBroadcastOffset(ds);
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// return offset == (size_t)-1 ? 0 : data[getOffset(ds)];
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// }
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// VType getBroadcastData(size_t pos) {
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// assert(data != nullptr);
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// return data[pos % size()];
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// }
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// size_t getBroadcastOffset(const Dim &ds) {
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// assert(ds.size() >= dims.size());
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// auto nDim = dims.size();
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// auto nBroadcastDim = ds.size() - nDim;
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// for (size_t i = 0; i < nDim; ++i)
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// if (ds[nBroadcastDim + i] < 0 || ds[nBroadcastDim + i] >=
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// dims[i])
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// return (size_t)-1;
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// size_t idx = 0;
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// for (size_t i = 0; i < nDim; ++i)
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// idx = idx * dims[i] + ds[nBroadcastDim + i];
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// return idx;
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// }
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// void itInit() { it = Dim(dims.size(), 0); }
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// void itReset() {
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// itInit();
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// for (size_t i = 0, iEnd = it.size(); i < iEnd; ++i)
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// it[i] = 0;
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// }
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// bool itValid() {
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// if (it.size() != dims.size())
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// return false;
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// for (size_t i = 0, iEnd = it.size(); i < iEnd; ++i)
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// if (it[i] >= dims[i])
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// return false;
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// return true;
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// }
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// const Dim &itGet() { return it; }
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// void itNext() {
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// auto p = it.size() - 1;
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// it[p] += 1;
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// while (p >= 1) {
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// if (it[p] == dims[p]) {
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// it[p] = 0;
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// it[--p] += 1;
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// } else
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// break;
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// }
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// }
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// size_t size() const {
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// size_t sz = 1;
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// auto dm = dims.size();
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// while (dm > 0)
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// sz *= dims[--dm];
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// return sz;
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// }
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// TensorType getType() const { return type; }
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// void setType(TensorType ty) { type = ty; }
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// static inline void initFastrand() {
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// assert(omp_get_max_threads() <= 256);
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// // srand(0); // constant seed for test
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// // align random_seed to avoid false sharing
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// for (int i = 0; i < 256 * 16; ++i) {
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// // random_seed[i] = rand();
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// // constant random seed for test
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// random_seed[i] = i;
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// }
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// random_inited = true;
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// }
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// static inline int fastrand(int &g_seed) {
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// g_seed = (214013 * g_seed + 2531011);
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// return (g_seed >> 16) & 0x7FFF;
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// }
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// std::vector<std::vector<int>> const *getSplittingPoints() const {
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// assert(!splittingPoints.empty());
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// return &splittingPoints;
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// }
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// bool setSplittingPoints(std::vector<std::vector<int>> value) {
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// assert(!value.empty());
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// splittingPoints = value;
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// return true;
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// }
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// void printSplittingPoints() {
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// if (splittingPoints.empty())
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// printf("Empty SplittingPoints");
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// else {
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// printf("[");
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// for (auto &vs : splittingPoints) {
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// printf("[");
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// for (auto v : vs)
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// printf("%2d,", v);
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// printf("],");
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// }
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// printf("]");
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// }
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// }
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// void initSplittingPoints() {
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// splittingPoints.resize(getDims().size()); }
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// void printShape();
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};
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2022-08-09 14:58:45 +08:00
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} // namespace infini
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