mindspore2022/mindspore/ccsrc/debug/debug_services.cc

217 lines
8.3 KiB
C++

/**
* Copyright 2019-2020 Huawei Technologies Co., Ltd
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "debug/debug_services.h"
namespace mindspore {
DebugServices::DebugServices() {
tensor_loader_ = new TensorLoader();
uint32_t iter_num = -1;
tensor_loader_->set_iter_num(iter_num);
}
DebugServices::DebugServices(const DebugServices &other) {
tensor_loader_ = other.tensor_loader_;
watchpoint_table = other.watchpoint_table;
}
DebugServices &DebugServices::operator=(const DebugServices &other) {
if (this != &other) {
tensor_loader_ = other.tensor_loader_;
watchpoint_table = other.watchpoint_table;
}
return *this;
}
DebugServices::~DebugServices() { delete tensor_loader_; }
void DebugServices::AddWatchpoint(unsigned int id, unsigned int watch_condition,
const std::vector<std::tuple<std::string, bool>> &check_node_list) {
std::lock_guard<std::mutex> lg(lock_);
watchpoint_t watchpoint_item;
watchpoint_item.id = id;
if (watch_condition == 0) {
watchpoint_item.conditions.nan.enabled = true;
} else if (watch_condition == 1) {
watchpoint_item.conditions.inf.enabled = true;
watchpoint_item.conditions.neg_inf.enabled = true;
}
watchpoint_item.check_node_list = check_node_list;
watchpoint_table[id] = watchpoint_item;
}
void DebugServices::RemoveWatchpoint(unsigned int id) {
std::lock_guard<std::mutex> lg(lock_);
watchpoint_table.erase(id);
}
void DebugServices::CheckWatchpoints(std::vector<std::string> *name, std::vector<std::string> *slot,
std::vector<char *> *data_ptr, std::vector<unsigned int> *data_size,
std::vector<int> *condition, std::vector<unsigned int> *wacthpoint_id) {
std::lock_guard<std::mutex> lg(lock_);
std::vector<std::shared_ptr<TensorData>> tensor_list = tensor_loader_->GetTensor();
std::string current_tensor_name;
std::unordered_map<unsigned int, watchpoint_t> watchpoints_to_check_table;
for (std::size_t i = 0; i < tensor_list.size(); i++) {
current_tensor_name = tensor_list[i]->GetName();
mindspore::tensor::TensorPtr tensor_ptr = tensor_list[i]->GetTensor();
int tensor_data_type = tensor_ptr->data_type_c();
// check if we need to analyze this node and for which watchpoints we will check
// create a list of watchpoints to check
watchpoints_to_check_table.clear();
for (auto w_table_item : watchpoint_table) {
// if the watchpoint is checking for a nan or inf and the current tensor is not of a float type, then
// don't check the watchpoint for this tensor
if (std::get<1>(w_table_item).conditions.inf.enabled || std::get<1>(w_table_item).conditions.neg_inf.enabled ||
std::get<1>(w_table_item).conditions.nan.enabled) {
if (tensor_data_type != kNumberTypeFloat16 && tensor_data_type != kNumberTypeFloat &&
tensor_data_type != kNumberTypeFloat32 && tensor_data_type != kNumberTypeFloat64) {
continue;
}
}
auto check_node_list = std::get<1>(w_table_item).check_node_list;
for (auto check_node : check_node_list) {
std::string w_name = std::get<0>(check_node);
bool w_type = std::get<1>(check_node);
// check if the current node tensor name is included the watchpoint
std::string current_node_name = current_tensor_name.substr(0, current_tensor_name.find_first_of(":"));
if ((w_type == true && (current_tensor_name.find(w_name) != string::npos || w_name == "*")) ||
(w_type == false && current_node_name == w_name)) {
watchpoints_to_check_table[w_table_item.second.id] = w_table_item.second;
break;
}
}
}
// check if no watchpoints are valid for the current tensor
if (watchpoints_to_check_table.empty()) {
continue;
}
// need to add support for float16 and float64, and other types when we support conditions beyond inf and nan
if (tensor_data_type != kNumberTypeFloat && tensor_data_type != kNumberTypeFloat32) {
continue;
}
float *start_addr = reinterpret_cast<float *>(tensor_ptr->data_c());
unsigned int num_elements = (tensor_ptr->data().nbytes()) / sizeof(float);
std::unordered_map<unsigned int, watchpoint_t>::iterator it_w_table_check;
std::vector<unsigned int> hit_encountered;
for (unsigned int index = 0; index < num_elements; index++) {
float x = start_addr[index];
it_w_table_check = watchpoints_to_check_table.begin();
while (it_w_table_check != watchpoints_to_check_table.end()) {
if ((it_w_table_check->second.conditions.inf.enabled || it_w_table_check->second.conditions.neg_inf.enabled) &&
isinf(x)) {
hit_encountered.push_back(it_w_table_check->second.id);
} else if (it_w_table_check->second.conditions.nan.enabled && isnan(x)) {
hit_encountered.push_back(it_w_table_check->second.id);
}
++it_w_table_check;
}
if (hit_encountered.size()) {
for (auto it_hit_id = hit_encountered.begin(); it_hit_id != hit_encountered.end(); ++it_hit_id) {
std::string name_no_slot = current_tensor_name.substr(0, current_tensor_name.find_first_of(":"));
name->push_back(name_no_slot);
slot->push_back(std::to_string(tensor_list[i]->GetSlot()));
data_ptr->push_back(reinterpret_cast<char *>(tensor_ptr->data_c()));
data_size->push_back(tensor_ptr->data().nbytes());
int condition_item = -1;
if (watchpoint_table[*it_hit_id].conditions.nan.enabled) {
condition_item = 0;
} else if (watchpoint_table[*it_hit_id].conditions.inf.enabled ||
watchpoint_table[*it_hit_id].conditions.neg_inf.enabled) {
condition_item = 1;
}
condition->push_back(condition_item);
wacthpoint_id->push_back(*it_hit_id);
watchpoints_to_check_table.erase(*it_hit_id);
}
hit_encountered.clear();
}
if (watchpoints_to_check_table.empty()) {
break;
}
}
}
}
void DebugServices::ReadNodesTensors(std::vector<std::string> name, std::vector<std::string> *ret_name,
std::vector<char *> *data_ptr, std::vector<unsigned int> *data_size,
std::vector<TypePtr> *dtype, std::vector<std::vector<int>> *shape) {
std::vector<std::tuple<std::string, std::shared_ptr<TensorData>>> result_list;
tensor_loader_->SearchTensors(name, &result_list);
for (auto result : result_list) {
if (!std::get<1>(result)) {
continue;
}
ret_name->push_back(std::get<0>(result));
data_ptr->push_back(reinterpret_cast<char *>(std::get<1>(result)->GetTensor()->data_c()));
data_size->push_back(std::get<1>(result)->GetTensor()->data().nbytes());
dtype->push_back(std::get<1>(result)->GetTensor()->Dtype());
shape->push_back(std::get<1>(result)->GetTensor()->shape());
}
}
bool DebugServices::IsWatchPoint(std::string kernel_name,
std::unordered_map<unsigned int, watchpoint_t> watchpoint_table) {
bool ret = false;
for (auto w_table_item : watchpoint_table) {
auto check_node_list = std::get<1>(w_table_item).check_node_list;
for (auto check_node : check_node_list) {
std::string w_name = std::get<0>(check_node);
bool w_type = std::get<1>(check_node);
if ((w_type == true &&
((kernel_name.find(w_name) != string::npos && kernel_name.rfind(w_name, 0) == 0) || w_name == "*")) ||
(w_type == false && kernel_name == w_name)) {
ret = true;
return ret;
}
}
}
return ret;
}
TensorLoader *DebugServices::tensor_loader() const { return tensor_loader_; }
std::unordered_map<unsigned int, DebugServices::watchpoint_t> DebugServices::GetWatchpointTable() {
return watchpoint_table;
}
} // namespace mindspore