* Copyright (c) 2026 Huawei Technologies Co., Ltd.
* This program is free software, you can redistribute it and/or modify it under the terms and conditions of
* CANN Open Software License Agreement Version 2.0 (the "License").
* Please refer to the License for details. You may not use this file except in compliance with the License.
* THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED,
* INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE.
* See LICENSE in the root of the software repository for the full text of the License.
*/
* \file test_geir_tile.cpp
* \brief GE IR test for Tile operator
*/
#include <iostream>
#include <fstream>
#include <string.h>
#include <stdint.h>
#include <vector>
#include <string>
#include <map>
#include "assert.h"
#include "graph.h"
#include "types.h"
#include "tensor.h"
#include "ge_error_codes.h"
#include "ge_api_types.h"
#include "ge_api.h"
#include "array_ops.h"
#include "ge_ir_build.h"
#include "nn_other.h"
#include "../op_graph/tile_proto.h"
#define FAILED -1
#define SUCCESS 0
using namespace ge;
using std::map;
using std::string;
using std::vector;
#define ADD_INPUT(inputIndex, inputName, inputDtype, inputShape, inputValues) \
do { \
std::string name##inputIndex = "placeholder" + std::to_string(inputIndex); \
auto placeholder##inputIndex = op::Data(name##inputIndex.c_str()).set_attr_index(inputIndex - 1); \
TensorDesc placeholder##inputIndex##_desc = \
TensorDesc(ge::Shape(inputShape), FORMAT_ND, inputDtype); \
placeholder##inputIndex##_desc.SetPlacement(ge::kPlacementHost); \
placeholder##inputIndex##_desc.SetFormat(FORMAT_ND); \
Tensor tensor_placeholder##inputIndex; \
ret = GenData(inputShape, tensor_placeholder##inputIndex, \
placeholder##inputIndex##_desc, inputDtype, inputValues); \
if (ret != SUCCESS) { \
printf("%s - ERROR - [XIR]: Generate input data failed\n", GetTime().c_str()); \
return FAILED; \
} \
placeholder##inputIndex.update_input_desc_x(placeholder##inputIndex##_desc); \
placeholder##inputIndex.update_output_desc_y(placeholder##inputIndex##_desc); \
input.push_back(tensor_placeholder##inputIndex); \
graph.AddOp(placeholder##inputIndex); \
tile1.set_input_##inputName(placeholder##inputIndex); \
inputs.push_back(placeholder##inputIndex); \
} while (0)
#define ADD_CONST_INPUT(inputIndex, inputName, inputDtype, inputShape, inputValues) \
do { \
std::string name##inputIndex = "placeholder" + std::to_string(inputIndex); \
auto placeholder##inputIndex = op::Const(name##inputIndex.c_str()); \
TensorDesc placeholder##inputIndex##_desc = \
TensorDesc(ge::Shape(inputShape), FORMAT_ND, inputDtype); \
placeholder##inputIndex##_desc.SetPlacement(ge::kPlacementHost); \
placeholder##inputIndex##_desc.SetFormat(FORMAT_ND); \
Tensor tensor_placeholder##inputIndex; \
ret = GenData(inputShape, tensor_placeholder##inputIndex, \
placeholder##inputIndex##_desc, inputDtype, inputValues); \
if (ret != SUCCESS) { \
printf("%s - ERROR - [XIR]: Generate input data failed\n", GetTime().c_str()); \
return FAILED; \
} \
placeholder##inputIndex.SetAttr("value", tensor_placeholder##inputIndex); \
placeholder##inputIndex.update_output_desc_y(placeholder##inputIndex##_desc); \
graph.AddOp(placeholder##inputIndex); \
tile1.set_input_##inputName(placeholder##inputIndex); \
tile1.update_input_desc_##inputName(placeholder##inputIndex##_desc); \
inputs.push_back(placeholder##inputIndex); \
} while (0)
string GetTime()
{
time_t timep;
time(&timep);
char tmp[64];
strftime(tmp, sizeof(tmp), "%Y-%m-%d %H:%M:%S,000", localtime(&timep));
return tmp;
}
uint32_t GetDataTypeSize(DataType dt)
{
switch (dt) {
case ge::DT_BOOL: return 1U;
case ge::DT_INT8: return 1U;
case ge::DT_UINT8: return 1U;
case ge::DT_INT16: return 2U;
case ge::DT_UINT16: return 2U;
case ge::DT_INT32: return 4U;
case ge::DT_UINT32: return 4U;
case ge::DT_INT64: return 8U;
case ge::DT_UINT64: return 8U;
case ge::DT_FLOAT: return 4U;
case ge::DT_DOUBLE: return 8U;
default: return 0U;
}
}
int32_t GenData(
const vector<int64_t>& shapes, Tensor& inputTensor, TensorDesc& inputTensorDesc,
DataType dataType, const vector<double>& values)
{
uint32_t typeSize = GetDataTypeSize(dataType);
if (typeSize == 0U) {
printf("ERROR: data_type %d is not supported by GenData (no standard C++ type mapping)\n",
static_cast<int>(dataType));
return FAILED;
}
inputTensorDesc.SetRealDimCnt(shapes.size());
size_t size = 1;
for (uint32_t i = 0; i < shapes.size(); i++) { size *= shapes[i]; }
if (size != values.size()) {
printf("ERROR: GenData shape size %zu != values size %zu\n", size, values.size());
return FAILED;
}
uint32_t dataLen = size * typeSize;
uint8_t* pData = new (std::nothrow) uint8_t[dataLen];
if (pData == nullptr) { return FAILED; }
switch (dataType) {
case ge::DT_BOOL: {
bool* data = reinterpret_cast<bool*>(pData);
for (size_t i = 0; i < size; ++i) data[i] = (values[i] != 0);
break;
}
case ge::DT_INT8: {
int8_t* data = reinterpret_cast<int8_t*>(pData);
for (size_t i = 0; i < size; ++i) data[i] = static_cast<int8_t>(values[i]);
break;
}
case ge::DT_UINT8: {
uint8_t* data = pData;
for (size_t i = 0; i < size; ++i) data[i] = static_cast<uint8_t>(values[i]);
break;
}
case ge::DT_INT16: {
int16_t* data = reinterpret_cast<int16_t*>(pData);
for (size_t i = 0; i < size; ++i) data[i] = static_cast<int16_t>(values[i]);
break;
}
case ge::DT_UINT16: {
uint16_t* data = reinterpret_cast<uint16_t*>(pData);
for (size_t i = 0; i < size; ++i) data[i] = static_cast<uint16_t>(values[i]);
break;
}
case ge::DT_INT32: {
int32_t* data = reinterpret_cast<int32_t*>(pData);
for (size_t i = 0; i < size; ++i) data[i] = static_cast<int32_t>(values[i]);
break;
}
case ge::DT_UINT32: {
uint32_t* data = reinterpret_cast<uint32_t*>(pData);
for (size_t i = 0; i < size; ++i) data[i] = static_cast<uint32_t>(values[i]);
break;
}
case ge::DT_INT64: {
int64_t* data = reinterpret_cast<int64_t*>(pData);
for (size_t i = 0; i < size; ++i) data[i] = static_cast<int64_t>(values[i]);
break;
}
case ge::DT_UINT64: {
uint64_t* data = reinterpret_cast<uint64_t*>(pData);
for (size_t i = 0; i < size; ++i) data[i] = static_cast<uint64_t>(values[i]);
break;
}
case ge::DT_FLOAT: {
float* data = reinterpret_cast<float*>(pData);
for (size_t i = 0; i < size; ++i) data[i] = static_cast<float>(values[i]);
break;
}
case ge::DT_DOUBLE: {
double* data = reinterpret_cast<double*>(pData);
for (size_t i = 0; i < size; ++i) data[i] = values[i];
break;
}
default:
delete[] pData;
return FAILED;
}
inputTensor = Tensor(inputTensorDesc, pData, dataLen);
return SUCCESS;
}
int32_t WriteDataToFile(const string& binFile, uint64_t dataSize, uint8_t* inputData)
{
FILE* fp = fopen(binFile.c_str(), "w");
if (fp == nullptr) {
return FAILED;
}
fwrite(inputData, sizeof(uint8_t), dataSize, fp);
fclose(fp);
return SUCCESS;
}
int CreateOppInGraph(DataType inDtype, vector<Tensor>& input, vector<Operator>& inputs, vector<Operator>& outputs, Graph& graph)
{
Status ret = SUCCESS;
auto tile1 = op::Tile("tile1");
vector<int64_t> xShape = {2, 3};
vector<int64_t> multiplesShape = {2};
vector<double> xValues = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0};
vector<double> multiplesValues = {2.0, 2.0};
ADD_INPUT(1, x, inDtype, xShape, xValues);
ADD_CONST_INPUT(2, multiples, DT_INT32, multiplesShape, multiplesValues);
outputs.push_back(tile1);
return SUCCESS;
}
int main(int argc, char* argv[])
{
printf("%s - INFO - [XIR]: Start to initialize ge using ge global options\n", GetTime().c_str());
map<AscendString, AscendString> globalOptions = {{"ge.exec.deviceId", "0"}, {"ge.graphRunMode", "1"}};
Status ret = ge::GEInitialize(globalOptions);
if (ret != SUCCESS) {
printf("%s - INFO - [XIR]: Initialize ge using ge global options failed\n", GetTime().c_str());
return FAILED;
}
printf("%s - INFO - [XIR]: Initialize ge using ge global options success\n", GetTime().c_str());
DataType inDtype = DT_INT32;
std::cout << inDtype << std::endl;
const char* graphName = "tile_ge_irrun_test";
Graph graph(graphName);
vector<Tensor> input;
vector<Operator> inputs{};
vector<Operator> outputs{};
ret = CreateOppInGraph(inDtype, input, inputs, outputs, graph);
if (ret != SUCCESS) {
printf("%s - ERROR - [XIR]: Create ir graph failed\n", GetTime().c_str());
return FAILED;
}
if (!inputs.empty() && !outputs.empty()) {
graph.SetInputs(inputs).SetOutputs(outputs);
}
map<AscendString, AscendString> buildOptions = {};
printf("%s - INFO - [XIR]: Start to create ir session using build options\n", GetTime().c_str());
ge::Session* session = new Session(buildOptions);
if (session == nullptr) {
printf("%s - ERROR - [XIR]: Create ir session failed\n", GetTime().c_str());
return FAILED;
}
printf("%s - INFO - [XIR]: Create ir session using build options success\n", GetTime().c_str());
printf("%s - INFO - [XIR]: Start to add compute graph to ir session\n", GetTime().c_str());
map<AscendString, AscendString> graphOptions = {};
uint32_t graphId = 0;
ret = session->AddGraph(graphId, graph, graphOptions);
if (ret != SUCCESS) {
printf("%s - ERROR - [XIR]: Add graph failed\n", GetTime().c_str());
delete session;
ge::GEFinalize();
return FAILED;
}
printf("%s - INFO - [XIR]: Session add ir compute graph to ir session success\n", GetTime().c_str());
printf("%s - INFO - [XIR]: dump graph to txt\n", GetTime().c_str());
string filePath = "./dump";
aclgrphDumpGraph(graph, filePath.c_str(), filePath.length());
printf("%s - INFO - [XIR]: Start to run ir compute graph\n", GetTime().c_str());
vector<Tensor> output;
ret = session->RunGraph(graphId, input, output);
if (ret != SUCCESS) {
printf("%s - ERROR - [XIR]: Run graph failed\n", GetTime().c_str());
delete session;
ge::GEFinalize();
return FAILED;
}
printf("%s - INFO - [XIR]: Session run ir compute graph success\n", GetTime().c_str());
int inputNum = input.size();
for (int i = 0; i < inputNum; i++) {
string inputFile = "./tile_ge_irrun_test_npu_input_" + std::to_string(i) + ".bin";
uint8_t* inputData = input[i].GetData();
int64_t inputShape = input[i].GetTensorDesc().GetShape().GetShapeSize();
uint32_t typeSize = GetDataTypeSize(input[i].GetTensorDesc().GetDataType());
if (typeSize == 0U) {
printf("ERROR: input %d has unsupported dtype\n", i);
continue;
}
uint32_t dataSize = inputShape * typeSize;
WriteDataToFile(inputFile, dataSize, inputData);
}
int outputNum = output.size();
for (int i = 0; i < outputNum; i++) {
string outputFile = "./tile_ge_irrun_test_npu_output_" + std::to_string(i) + ".bin";
uint8_t* outputData = output[i].GetData();
int64_t outputShape = output[i].GetTensorDesc().GetShape().GetShapeSize();
uint32_t typeSize = GetDataTypeSize(output[i].GetTensorDesc().GetDataType());
if (typeSize == 0U) {
printf("ERROR: output %d has unsupported dtype\n", i);
continue;
}
uint32_t dataSize = outputShape * typeSize;
WriteDataToFile(outputFile, dataSize, outputData);
}
ge::AscendString errorMsg = ge::GEGetErrorMsgV2();
string errorStr(errorMsg.GetString());
std::cout << "Error message: " << errorStr << std::endl;
ge::AscendString warningMsg = ge::GEGetWarningMsgV2();
string warningStr(warningMsg.GetString());
std::cout << "Warning message: " << warningStr << std::endl;
delete session;
printf("%s - INFO - [XIR]: Start to finalize ir graph session\n", GetTime().c_str());
ret = ge::GEFinalize();
if (ret != SUCCESS) {
printf("%s - INFO - [XIR]: Finalize ir graph session failed\n", GetTime().c_str());
return FAILED;
}
printf("%s - INFO - [XIR]: Finalize ir graph session success\n", GetTime().c_str());
return SUCCESS;
}
