* 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_max_pool_v2.cpp
* \brief MaxPoolV2 GE IR test example
*/
#include <ctime>
#include <complex>
#include <cstdio>
#include <fstream>
#include <iostream>
#include <map>
#include <numeric>
#include <stdint.h>
#include <string>
#include <string.h>
#include <vector>
#include "assert.h"
#include "ge_api.h"
#include "ge_api_types.h"
#include "ge_error_codes.h"
#include "ge_ir_build.h"
#include "graph.h"
#include "graph/operator.h"
#include "graph/operator_reg.h"
#include "tensor.h"
#include "types.h"
#include "array_ops.h"
#include "nn_other.h"
#include "../op_graph/max_pool_v2_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)
{
uint32_t oneByte = 1;
uint32_t twoByte = 2;
uint32_t fourByte = 4;
uint32_t eightByte = 8;
if (dt == ge::DT_FLOAT) {
return fourByte;
} else if (dt == ge::DT_FLOAT16 || dt == ge::DT_BF16 || dt == ge::DT_INT16 || dt == ge::DT_UINT16) {
return twoByte;
} else if (dt == ge::DT_INT32 || dt == ge::DT_UINT32) {
return fourByte;
} else if (dt == ge::DT_INT64 || dt == ge::DT_UINT64 || dt == ge::DT_DOUBLE) {
return eightByte;
}
return oneByte;
}
template <typename T>
int32_t GenTensorData(
const vector<int64_t>& shapes, Tensor& input_tensor, TensorDesc& input_tensor_desc, const vector<T>& values)
{
input_tensor_desc.SetRealDimCnt(shapes.size());
size_t size = 1;
for (auto dim : shapes) {
size *= dim;
}
if (size != values.size()) {
printf(
"%s - ERROR - [XIR]: GenTensorData size mismatch, expected %zu, got %zu\n", GetTime().c_str(), size,
values.size());
return FAILED;
}
auto* data = new (std::nothrow) T[size];
if (data == nullptr) {
return FAILED;
}
for (size_t i = 0; i < size; ++i) {
data[i] = values[i];
}
input_tensor = Tensor(input_tensor_desc, reinterpret_cast<uint8_t*>(data), size * sizeof(T));
return SUCCESS;
}
template <typename T>
int32_t GenOnesData(
vector<int64_t> shapes, Tensor& input_tensor, TensorDesc& input_tensor_desc, DataType data_type, const vector<T>& values)
{
input_tensor_desc.SetRealDimCnt(shapes.size());
size_t size = 1;
for (uint32_t i = 0; i < shapes.size(); i++) {
size *= shapes[i];
}
auto* data = new (std::nothrow) T[size];
if (data == nullptr) {
return FAILED;
}
for (size_t i = 0; i < size; ++i) {
data[i] = values[i];
}
input_tensor = Tensor(input_tensor_desc, reinterpret_cast<uint8_t*>(data), size * sizeof(T));
return SUCCESS;
}
int32_t WriteDataToFile(const string& bin_file, uint64_t data_size, uint8_t* input_data)
{
FILE* fp = fopen(bin_file.c_str(), "w");
if (fp == nullptr) {
printf("%s - ERROR - [XIR]: Failed to open file %s\n", GetTime().c_str(), bin_file.c_str());
return FAILED;
}
fwrite(input_data, sizeof(uint8_t), data_size, fp);
fclose(fp);
return SUCCESS;
}
#define ADD_INPUT(inputIndex, inputName, inputDtype, inputShape, inputValues) \
vector<int64_t> placeholder##inputIndex##_shape = inputShape; \
auto placeholder##inputIndex = \
op::Data("placeholder" + inputIndex).set_attr_index((inputIndex) - 1); \
TensorDesc placeholder##inputIndex##_desc = \
TensorDesc(ge::Shape(placeholder##inputIndex##_shape), FORMAT_ND, inputDtype); \
placeholder##inputIndex##_desc.SetPlacement(ge::kPlacementHost); \
placeholder##inputIndex##_desc.SetFormat(FORMAT_ND); \
Tensor tensor_placeholder##inputIndex; \
ret = GenTensorData( \
placeholder##inputIndex##_shape, tensor_placeholder##inputIndex, placeholder##inputIndex##_desc, \
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); \
max_pool_v2.set_input_##inputName(placeholder##inputIndex); \
inputs.push_back(placeholder##inputIndex)
#define ADD_CONST_INPUT(intputIndex, intputName, intputDtype, inputShape, inputValues) \
vector<int64_t> placeholder##intputIndex##_shape = inputShape; \
auto placeholder##intputIndex = op::Const("placeholder" + intputIndex); \
TensorDesc placeholder##intputIndex##_desc = \
TensorDesc(ge::Shape(placeholder##intputIndex##_shape), FORMAT_ND, intputDtype); \
placeholder##intputIndex##_desc.SetPlacement(ge::kPlacementHost); \
placeholder##intputIndex##_desc.SetFormat(FORMAT_ND); \
Tensor tensor_placeholder##intputIndex; \
ret = GenOnesData( \
placeholder##intputIndex##_shape, tensor_placeholder##intputIndex, placeholder##intputIndex##_desc, \
intputDtype, inputValues); \
if (ret != SUCCESS) { \
printf("%s - ERROR - [XIR]: Generate input data failed\n", GetTime().c_str()); \
return FAILED; \
} \
placeholder##intputIndex.SetAttr("value", tensor_placeholder##intputIndex); \
placeholder##intputIndex.update_output_desc_y(placeholder##intputIndex##_desc); \
graph.AddOp(placeholder##intputIndex); \
max_pool_v2.set_input_##intputName(placeholder##intputIndex); \
max_pool_v2.update_input_desc_##intputName(placeholder##intputIndex##_desc); \
inputs.push_back(placeholder##intputIndex);
#define ADD_INPUT_ATTR(attrName, attrValue) max_pool_v2.set_attr_##attrName(attrValue)
#define ADD_OUTPUT(outputIndex, outputName, outputDtype, outputShape) \
TensorDesc outputName##outputIndex##_desc_ = TensorDesc(ge::Shape(outputShape), FORMAT_ND, outputDtype); \
max_pool_v2.update_output_desc_##outputName(outputName##outputIndex##_desc_)
int CreateOppInGraph(
std::vector<ge::Tensor>& input, std::vector<Operator>& inputs, std::vector<Operator>& outputs, Graph& graph)
{
Status ret = SUCCESS;
auto max_pool_v2 = op::MaxPoolV2("max_pool_v2");
std::vector<int64_t> x_shape = {1, 1, 1, 1};
std::vector<int64_t> ksize_shape = {4};
std::vector<int64_t> strides_shape = {4};
std::vector<int64_t> y_shape = {1};
std::vector<uint16_t> x_data = { 1 };
std::vector<int32_t> ksize_data = {1, 1, 1, 1};
std::vector<int32_t> strides_data = {1, 6, 36, 1};
ADD_INPUT(1, x, DT_FLOAT16, x_shape, x_data);
ADD_CONST_INPUT(2, ksize, DT_INT32, ksize_shape, ksize_data);
ADD_CONST_INPUT(3, strides, DT_INT32, strides_shape, strides_data);
max_pool_v2.set_attr_padding("VALID");
ADD_INPUT_ATTR(data_format, "NHWC");
ADD_OUTPUT(1, y, DT_FLOAT16, y_shape);
outputs.push_back(max_pool_v2);
return SUCCESS;
}
int main(int argc, char* argv[])
{
(void)argc;
(void)argv;
const char* graph_name = "tc_ge_irrun_test_max_pool_v2";
Graph graph(graph_name);
std::vector<ge::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 - ERROR - [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());
std::vector<Operator> inputs{};
std::vector<Operator> outputs{};
ret = CreateOppInGraph(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 using build options\n", GetTime().c_str());
ge::Session* session = new Session(build_options);
if (session == nullptr) {
printf("%s - ERROR - [XIR]: Create ir session using build options 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());
std::map<AscendString, AscendString> graph_options = {};
uint32_t graph_id = 0;
ret = session->AddGraph(graph_id, graph, graph_options);
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());
std::string file_path = "./dump";
aclgrphDumpGraph(graph, file_path.c_str(), file_path.length());
printf("%s - INFO - [XIR]: Start to run ir compute graph\n", GetTime().c_str());
std::vector<ge::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]: Session run ir compute graph success\n", GetTime().c_str());
int input_num = input.size();
for (int i = 0; i < input_num; i++) {
std::cout << "input " << i << " dtype : " << input[i].GetTensorDesc().GetDataType() << std::endl;
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();
std::cout << "this is " << i << "th input, input shape size =" << input_shape << std::endl;
uint32_t data_size = input_shape * GetDataTypeSize(input[i].GetTensorDesc().GetDataType());
WriteDataToFile((const char*)input_file.c_str(), data_size, input_data_i);
}
int output_num = output.size();
for (int i = 0; i < output_num; i++) {
std::cout << "output " << i << " dtype : " << output[i].GetTensorDesc().GetDataType() << std::endl;
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();
std::cout << "this is " << i << "th output, output shape size =" << output_shape << std::endl;
uint32_t data_size = output_shape * GetDataTypeSize(output[i].GetTensorDesc().GetDataType());
WriteDataToFile((const char*)output_file.c_str(), data_size, output_data_i);
float* resultData = (float*)output_data_i;
for (int64_t j = 0; j < output_shape; j++) {
printf("result[%ld] is: %f\n", j, resultData[j]);
}
}
ge::AscendString error_msg = ge::GEGetErrorMsgV2();
std::string error_str(error_msg.GetString());
std::cout << "Error message: " << error_str << std::endl;
ge::AscendString warning_msg = ge::GEGetWarningMsgV2();
std::string warning_str(warning_msg.GetString());
std::cout << "Warning message: " << warning_str << std::endl;
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;
}