* 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_zeta.cpp
* \brief GE IR test for Zeta operator
*/
#include <iostream>
#include <fstream>
#include <string.h>
#include <stdint.h>
#include <ctime>
#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 "../op_graph/zeta_proto.h"
#define FAILED -1
#define SUCCESS 0
using namespace ge;
using std::map;
using std::string;
using std::vector;
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:
case ge::DT_UINT8:
return 1U;
case ge::DT_FLOAT16:
case ge::DT_INT16:
case ge::DT_UINT16:
return 2U;
case ge::DT_FLOAT:
case ge::DT_INT32:
case ge::DT_UINT32:
return 4U;
case ge::DT_DOUBLE:
case ge::DT_INT64:
case ge::DT_UINT64:
return 8U;
default:
return 0U;
}
}
int32_t GenData(vector<int64_t> shapes, Tensor& tensor, TensorDesc& tensor_desc, DataType data_type, double value)
{
tensor_desc.SetRealDimCnt(shapes.size());
size_t size = 1;
for (uint32_t i = 0; i < shapes.size(); i++) {
size *= static_cast<size_t>(shapes[i]);
}
uint32_t type_size = GetDataTypeSize(data_type);
if (type_size == 0U) {
printf("%s - ERROR - [XIR]: GenData: unsupported data type\n", GetTime().c_str());
return FAILED;
}
uint32_t data_len = static_cast<uint32_t>(size * type_size);
uint8_t* buf = new (std::nothrow) uint8_t[data_len];
if (buf == nullptr) {
printf("%s - ERROR - [XIR]: GenData: allocate memory failed\n", GetTime().c_str());
return FAILED;
}
if (data_type == ge::DT_FLOAT) {
float* p = reinterpret_cast<float*>(buf);
for (size_t i = 0; i < size; ++i) {
p[i] = static_cast<float>(value);
}
} else if (data_type == ge::DT_DOUBLE) {
double* p = reinterpret_cast<double*>(buf);
for (size_t i = 0; i < size; ++i) {
p[i] = static_cast<double>(value);
}
}
tensor = Tensor(tensor_desc, buf, data_len);
delete[] buf;
return SUCCESS;
}
int32_t WriteDataToFile(string bin_file, uint64_t data_size, uint8_t* inputData)
{
FILE* fp = fopen(bin_file.c_str(), "wb");
if (fp == nullptr) {
return FAILED;
}
fwrite(inputData, sizeof(uint8_t), data_size, fp);
fclose(fp);
return SUCCESS;
}
void ProcessInputData(vector<Tensor>& input)
{
for (size_t i = 0; i < input.size(); i++) {
string input_file = "./tc_ge_irrun_test_0008_npu_input_" + std::to_string(i) + ".bin";
uint8_t* input_data_i = input[i].GetData();
int64_t input_shape = input[i].GetTensorDesc().GetShape().GetShapeSize();
uint32_t type_size = GetDataTypeSize(input[i].GetTensorDesc().GetDataType());
if (type_size == 0U) {
printf("ERROR: input %zu has unsupported dtype\n", i);
continue;
}
uint32_t data_size = static_cast<uint32_t>(input_shape * type_size);
WriteDataToFile(input_file.c_str(), data_size, input_data_i);
}
}
void ProcessOutputData(vector<Tensor>& output)
{
for (size_t i = 0; i < output.size(); i++) {
string output_file = "./tc_ge_irrun_test_0008_npu_output_" + std::to_string(i) + ".bin";
uint8_t* output_data_i = output[i].GetData();
int64_t output_shape = output[i].GetTensorDesc().GetShape().GetShapeSize();
uint32_t type_size = GetDataTypeSize(output[i].GetTensorDesc().GetDataType());
if (type_size == 0U) {
printf("ERROR: output %zu has unsupported dtype\n", i);
continue;
}
uint32_t data_size = static_cast<uint32_t>(output_shape * type_size);
WriteDataToFile(output_file.c_str(), data_size, output_data_i);
}
}
int CreateOppInGraph(DataType inDtype, vector<Tensor>& input, vector<Operator>& inputs, vector<Operator>& outputs,
Graph& graph)
{
vector<int64_t> shape = {2, 3};
auto x_data = op::Data("x_data").set_attr_index(0);
TensorDesc x_desc = TensorDesc(ge::Shape(shape), FORMAT_ND, inDtype);
x_desc.SetPlacement(ge::kPlacementHost);
x_desc.SetFormat(FORMAT_ND);
Tensor x_tensor;
int32_t ret = GenData(shape, x_tensor, x_desc, inDtype, 2.0);
if (ret != SUCCESS) {
printf("%s - ERROR - [XIR]: Generate x data failed\n", GetTime().c_str());
return FAILED;
}
x_data.update_input_desc_x(x_desc);
x_data.update_output_desc_y(x_desc);
graph.AddOp(x_data);
input.push_back(x_tensor);
inputs.push_back(x_data);
auto q_data = op::Data("q_data").set_attr_index(1);
TensorDesc q_desc = TensorDesc(ge::Shape(shape), FORMAT_ND, inDtype);
q_desc.SetPlacement(ge::kPlacementHost);
q_desc.SetFormat(FORMAT_ND);
Tensor q_tensor;
ret = GenData(shape, q_tensor, q_desc, inDtype, 1.5);
if (ret != SUCCESS) {
printf("%s - ERROR - [XIR]: Generate q data failed\n", GetTime().c_str());
return FAILED;
}
q_data.update_input_desc_x(q_desc);
q_data.update_output_desc_y(q_desc);
graph.AddOp(q_data);
input.push_back(q_tensor);
inputs.push_back(q_data);
auto zeta_op = op::Zeta("zeta_op");
zeta_op.set_input_x(x_data);
zeta_op.set_input_q(q_data);
TensorDesc z_desc = TensorDesc(ge::Shape(shape), FORMAT_ND, inDtype);
zeta_op.update_output_desc_z(z_desc);
graph.AddOp(zeta_op);
outputs.push_back(zeta_op);
return SUCCESS;
}
int main()
{
const char* graph_name = "tc_ge_irrun_test";
Graph graph(graph_name);
vector<Tensor> input;
printf("%s - INFO - [XIR]: Start to initialize ge using ge global options\n", GetTime().c_str());
std::map<AscendString, AscendString> global_options = {{"ge.exec.deviceId", "0"}, {"ge.graphRunMode", "1"}};
Status ret = ge::GEInitialize(global_options);
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());
vector<Operator> inputs{};
vector<Operator> outputs{};
DataType inDtype = DT_FLOAT;
ret = CreateOppInGraph(inDtype, input, inputs, outputs, graph);
if (ret != SUCCESS) {
printf("%s - ERROR - [XIR]: Create graph failed\n", GetTime().c_str());
return FAILED;
}
if (!inputs.empty() && !outputs.empty()) {
graph.SetInputs(inputs).SetOutputs(outputs);
}
std::map<AscendString, AscendString> build_options = {};
printf("%s - INFO - [XIR]: Start to create ir session\n", GetTime().c_str());
ge::Session* session = new Session(build_options);
if (session == nullptr) {
printf("%s - ERROR - [XIR]: Create session failed\n", GetTime().c_str());
return FAILED;
}
printf("%s - INFO - [XIR]: Create ir session success\n", GetTime().c_str());
uint32_t graph_id = 0;
std::map<AscendString, AscendString> graph_options = {};
printf("%s - INFO - [XIR]: Add graph\n", GetTime().c_str());
ret = session->AddGraph(graph_id, graph, graph_options);
if (ret != SUCCESS) {
printf("%s - ERROR - [XIR]: Add graph failed\n", GetTime().c_str());
delete session;
GEFinalize();
return FAILED;
}
printf("%s - INFO - [XIR]: Start to run graph\n", GetTime().c_str());
vector<Tensor> output;
ret = session->RunGraph(graph_id, input, output);
if (ret != SUCCESS) {
printf("%s - ERROR - [XIR]: Run graph failed\n", GetTime().c_str());
delete session;
GEFinalize();
return FAILED;
}
printf("%s - INFO - [XIR]: Run graph success\n", GetTime().c_str());
ProcessInputData(input);
ProcessOutputData(output);
printf("%s - INFO - [XIR]: Start to finalize ir graph session\n", GetTime().c_str());
delete session;
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;
}
