* 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_reduce_all.cpp
* \brief Test ReduceAll via GE IR graph mode
*/
#include <fstream>
#include <iostream>
#include <map>
#include <string>
#include <string.h>
#include <stdint.h>
#include <vector>
#include "assert.h"
#include "array_ops.h"
#include "ge_api.h"
#include "ge_api_types.h"
#include "ge_error_codes.h"
#include "ge_ir_build.h"
#include "graph.h"
#include "tensor.h"
#include "types.h"
#include "../op_graph/reduce_all_proto.h"
#define FAILED -1
#define SUCCESS 0
using namespace ge;
using std::map;
using std::string;
using std::vector;
#define LOG_PRINT(message, ...) \
do { \
printf(message, ##__VA_ARGS__); \
} while (0)
string GetTime()
{
time_t timep;
time(&timep);
char tmp[64];
struct tm tm_info;
strftime(tmp, sizeof(tmp), "%Y-%m-%d %H:%M:%S,000", localtime_r(&timep, &tm_info));
return tmp;
}
uint32_t GetDataTypeSize(DataType dt)
{
if (dt == ge::DT_BOOL || dt == ge::DT_INT8 || dt == ge::DT_UINT8) {
return 1;
}
if (dt == ge::DT_INT16 || dt == ge::DT_UINT16 || dt == ge::DT_FLOAT16 || dt == ge::DT_BF16) {
return 2;
}
if (dt == ge::DT_INT32 || dt == ge::DT_UINT32 || dt == ge::DT_FLOAT) {
return 4;
}
if (dt == ge::DT_INT64 || dt == ge::DT_UINT64 || dt == ge::DT_DOUBLE) {
return 8;
}
return 0;
}
int32_t WriteDataToFile(const string &bin_file, uint64_t data_size, const uint8_t *input_data)
{
FILE *fp = fopen(bin_file.c_str(), "wb");
if (fp == nullptr) {
printf("Failed to open file: %s\n", bin_file.c_str());
return FAILED;
}
size_t written = fwrite(input_data, sizeof(uint8_t), data_size, fp);
fclose(fp);
if (written != data_size) {
printf("Failed to write file: %s\n", bin_file.c_str());
return FAILED;
}
return SUCCESS;
}
int32_t GenBoolData(const vector<int64_t> &shapes, Tensor &input_tensor, TensorDesc &input_tensor_desc,
const vector<bool> &values)
{
input_tensor_desc.SetRealDimCnt(shapes.size());
size_t size = 1;
for (size_t i = 0; i < shapes.size(); ++i) {
size *= static_cast<size_t>(shapes[i]);
}
if (values.size() != size) {
return FAILED;
}
vector<uint8_t> raw_data(size);
for (size_t i = 0; i < size; ++i) {
raw_data[i] = static_cast<uint8_t>(values[i]);
}
input_tensor = Tensor(input_tensor_desc, raw_data.data(), raw_data.size());
return SUCCESS;
}
int32_t GenInt32Data(const vector<int64_t> &shapes, Tensor &input_tensor, TensorDesc &input_tensor_desc,
const vector<int32_t> &values)
{
input_tensor_desc.SetRealDimCnt(shapes.size());
size_t size = 1;
for (size_t i = 0; i < shapes.size(); ++i) {
size *= static_cast<size_t>(shapes[i]);
}
if (values.size() != size) {
return FAILED;
}
input_tensor = Tensor(input_tensor_desc, reinterpret_cast<const uint8_t *>(values.data()),
values.size() * sizeof(int32_t));
return SUCCESS;
}
int CreateOppInGraph(vector<ge::Tensor> &input, vector<Operator> &inputs, vector<Operator> &outputs, Graph &graph)
{
Status ret = SUCCESS;
auto reduce_all = op::ReduceAll("reduce_all_graph");
vector<int64_t> x_shape = {2, 3};
vector<int64_t> axes_shape = {1};
vector<int64_t> y_shape = {2};
auto x = op::Data("placeholder0").set_attr_index(0);
TensorDesc x_desc(ge::Shape(x_shape), FORMAT_ND, DT_BOOL);
x_desc.SetPlacement(ge::kPlacementHost);
x_desc.SetFormat(FORMAT_ND);
Tensor x_tensor;
ret = GenBoolData(x_shape, x_tensor, x_desc, {true, true, false, true, true, true});
if (ret != SUCCESS) {
printf("%s - ERROR - [XIR]: Generate input data failed\n", GetTime().c_str());
return FAILED;
}
x.update_input_desc_x(x_desc);
x.update_output_desc_y(x_desc);
input.push_back(x_tensor);
graph.AddOp(x);
reduce_all.set_input_x(x);
inputs.push_back(x);
auto axes = op::Data("placeholder1").set_attr_index(1);
TensorDesc axes_desc(ge::Shape(axes_shape), FORMAT_ND, DT_INT32);
axes_desc.SetPlacement(ge::kPlacementHost);
axes_desc.SetFormat(FORMAT_ND);
Tensor axes_tensor;
ret = GenInt32Data(axes_shape, axes_tensor, axes_desc, {1});
if (ret != SUCCESS) {
printf("%s - ERROR - [XIR]: Generate axes data failed\n", GetTime().c_str());
return FAILED;
}
axes.update_input_desc_x(axes_desc);
axes.update_output_desc_y(axes_desc);
input.push_back(axes_tensor);
graph.AddOp(axes);
reduce_all.set_input_axes(axes);
reduce_all.update_input_desc_axes(axes_desc);
inputs.push_back(axes);
TensorDesc y_desc(ge::Shape(y_shape), FORMAT_ND, DT_BOOL);
reduce_all.update_output_desc_y(y_desc);
reduce_all.set_attr_keep_dims(false);
outputs.push_back(reduce_all);
return SUCCESS;
}
int SaveInputOutput(const vector<ge::Tensor> &input, const vector<ge::Tensor> &output)
{
for (size_t i = 0; i < input.size(); ++i) {
string input_file = "./tc_ge_irrun_reduce_all_npu_input_" + std::to_string(i) + ".bin";
const uint8_t *input_data = input[i].GetData();
int64_t input_shape = input[i].GetTensorDesc().GetShape().GetShapeSize();
uint32_t data_size = input_shape * GetDataTypeSize(input[i].GetTensorDesc().GetDataType());
if (WriteDataToFile(input_file, data_size, input_data) != SUCCESS) {
return FAILED;
}
}
const bool expected[] = {false, true};
for (size_t i = 0; i < output.size(); ++i) {
string output_file = "./tc_ge_irrun_reduce_all_npu_output_" + std::to_string(i) + ".bin";
const uint8_t *output_data = output[i].GetData();
int64_t output_shape = output[i].GetTensorDesc().GetShape().GetShapeSize();
uint32_t data_size = output_shape * GetDataTypeSize(output[i].GetTensorDesc().GetDataType());
if (WriteDataToFile(output_file, data_size, output_data) != SUCCESS) {
return FAILED;
}
const bool *result_data = reinterpret_cast<const bool *>(output_data);
for (int64_t j = 0; j < output_shape; ++j) {
LOG_PRINT("result[%ld] is: %u\n", j, static_cast<unsigned int>(result_data[j]));
if (result_data[j] != expected[j]) {
printf("ReduceAll output mismatch at index %ld\n", j);
return FAILED;
}
}
}
return SUCCESS;
}
int main(int argc, char *argv[])
{
(void)argc;
(void)argv;
const char *graph_name = "tc_ge_irrun_reduce_all";
Graph graph(graph_name);
vector<ge::Tensor> input;
printf("%s - INFO - [XIR]: Start to initialize ge using ge global options\n", GetTime().c_str());
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;
}
vector<Operator> inputs;
vector<Operator> outputs;
ret = CreateOppInGraph(input, inputs, outputs, graph);
if (ret != SUCCESS) {
ge::GEFinalize();
return FAILED;
}
if (!inputs.empty() && !outputs.empty()) {
graph.SetInputs(inputs).SetOutputs(outputs);
}
map<AscendString, AscendString> build_options;
ge::Session *session = new (std::nothrow) Session(build_options);
if (session == nullptr) {
printf("%s - ERROR - [XIR]: Create ir session failed\n", GetTime().c_str());
ge::GEFinalize();
return FAILED;
}
map<AscendString, AscendString> graph_options = {{"ge.exec.precision_mode", "allow_mix_precision"}};
uint32_t graph_id = 0;
ret = session->AddGraph(graph_id, graph, graph_options);
if (ret != SUCCESS) {
printf("%s - ERROR - [XIR]: Add graph failed\n", GetTime().c_str());
delete session;
ge::GEFinalize();
return FAILED;
}
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;
ge::GEFinalize();
return FAILED;
}
ret = SaveInputOutput(input, output);
delete session;
if (ret != SUCCESS) {
ge::GEFinalize();
return FAILED;
}
ret = ge::GEFinalize();
if (ret != SUCCESS) {
printf("%s - ERROR - [XIR]: GE Finalize failed\n", GetTime().c_str());
return FAILED;
}
return SUCCESS;
}
