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change switchn to case and add ut

tags/v1.2.0
zhou_lili 3 years ago
parent
8d35443bb9
commit
dd6996e2e9
18 changed files with 1016 additions and 203 deletions
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  1. +106
    -75
      ge/graph/load/new_model_manager/davinci_model.cc
  2. +9
    -7
      ge/graph/load/new_model_manager/davinci_model.h
  3. +6
    -6
      ge/graph/load/new_model_manager/model_manager.cc
  4. +3
    -3
      ge/graph/load/new_model_manager/model_manager.h
  5. +3
    -1
      ge/graph/load/new_model_manager/task_info/hccl_task_info.cc
  6. +4
    -2
      ge/graph/manager/graph_manager.cc
  7. +5
    -1
      ge/graph/passes/common_subexpression_elimination_pass.cc
  8. +474
    -79
      ge/graph/passes/multi_batch_clone_pass.cc
  9. +41
    -17
      ge/graph/passes/multi_batch_clone_pass.h
  10. +4
    -0
      ge/graph/passes/unused_args_clean_pass.cc
  11. +5
    -7
      ge/graph/preprocess/multi_batch_copy_graph.cc
  12. +2
    -3
      ge/graph/preprocess/multi_batch_options.cc
  13. +3
    -0
      inc/framework/omg/omg_inner_types.h
  14. +1
    -1
      metadef
  15. +1
    -1
      parser
  16. +1
    -0
      tests/ut/ge/CMakeLists.txt
  17. +101
    -0
      tests/ut/ge/graph/load/davinci_model_unittest.cc
  18. +247
    -0
      tests/ut/ge/graph/passes/multi_batch_clone_pass_unittest.cc

+ 106
- 75
ge/graph/load/new_model_manager/davinci_model.cc View File

@@ -87,6 +87,7 @@ const uint32_t kDumpL1FusionOpMByteSize = 2097152; // 2 * 1024 * 1024
const uint32_t kDumpFlagOfL1Fusion = 0;
const char *const kDefaultBatchLable = "Batch_default";
const char *const kGetDynamicDimsName = "ascend_mbatch_get_dynamic_dims_node";
const char *const kMultiBatchNodePostfix = "_ascend_mbatch_batch_";
const int32_t kInvalidStream = -1;
const uint32_t kEndOfSequence = 0x0704000a;
const uint32_t kEndOfSequenceNew = 507005;
@@ -867,6 +868,10 @@ Status DavinciModel::InitNodes(const ComputeGraphPtr &compute_graph) {
GELOGE(PARAM_INVALID, "NetOutput init failed, Name: %s", op_desc->GetName().c_str());
return PARAM_INVALID;
}
if (InitRealSizeAndShapeInfo(compute_graph, node) != SUCCESS) {
GELOGE(PARAM_INVALID, "Init real size and shape failed, Name: %s", op_desc->GetName().c_str());
return PARAM_INVALID;
}
continue;
}

@@ -1143,16 +1148,24 @@ Status DavinciModel::InitNetOutput(const ComputeGraphPtr &graph, const NodePtr &
real_virtual_addrs_.insert(real_addr);
}
}
return SUCCESS;
}

Status DavinciModel::InitRealSizeAndShapeInfo(const ComputeGraphPtr &compute_graph, const NodePtr &node) {
if (node->GetName().find(kMultiBatchNodePostfix) != string::npos) {
GELOGD("No need to get size and shape of netoutput in subgraph.");
return SUCCESS;
}
GELOGD("Start init real size and shape info of %s.", node->GetName().c_str());
GetAllGearsInfo(node);
if (is_getnext_sink_dynamic_) {
GE_IF_BOOL_EXEC(GetGetDynamicDimsNodeInfo(node) != SUCCESS,
GELOGE(PARAM_INVALID, "Failed to get info of getdynamicdims node."); return PARAM_INVALID;);
}
if (is_online_infer_dynamic_) {
GE_IF_BOOL_EXEC(GetGearAndRealOutSizeInfo(input_count, node) != SUCCESS,
GE_IF_BOOL_EXEC(GetGearAndRealOutSizeInfo(compute_graph, node) != SUCCESS,
GELOGE(PARAM_INVALID, "Failed to get gear and real out size info."); return PARAM_INVALID;);
GE_IF_BOOL_EXEC(GetGearAndRealOutShapeInfo(input_count, op_desc) != SUCCESS,
GE_IF_BOOL_EXEC(GetGearAndRealOutShapeInfo(compute_graph, node) != SUCCESS,
GELOGE(PARAM_INVALID, "Failed to get gear and real out shape info."); return PARAM_INVALID;);
}

@@ -1171,7 +1184,7 @@ void DavinciModel::GetAllGearsInfo(const NodePtr &node) {
if (shape_str.empty()) {
continue;
}
std::vector<int64_t> gear_info;
std::vector<int32_t> gear_info;
std::vector<std::string> dims = ge::StringUtils::Split(shape_str, ',');
for (const auto &dim : dims) {
if (dim.empty()) {
@@ -1187,6 +1200,7 @@ void DavinciModel::GetAllGearsInfo(const NodePtr &node) {
}
}
}

Status DavinciModel::GetGetDynamicDimsNodeInfo(const NodePtr &node) {
GE_CHECK_NOTNULL(node->GetOpDesc());
size_t input_count = node->GetAllInDataAnchors().size();
@@ -1224,11 +1238,11 @@ Status DavinciModel::GetGetDynamicDimsNodeInfo(const NodePtr &node) {
return SUCCESS;
}

Status DavinciModel::GetGearAndRealOutSizeInfo(size_t input_count, const NodePtr &node) {
GELOGD("Start get gear and real output size info of %s, input count is %zu.", node->GetName().c_str(), input_count);
Status DavinciModel::GetGearAndRealOutSizeInfo(const ComputeGraphPtr &graph, const NodePtr &node) {
GELOGD("Start get gear and real output size info of %s.", node->GetName().c_str());
merge_nodes_gear_and_real_out_size_info_.clear();
for (size_t idx = 0; idx < input_count; ++idx) {
auto in_anchor = node->GetAllInDataAnchors().at(idx);
size_t idx = 0;
for (const auto &in_anchor : node->GetAllInDataAnchors()) {
auto peer_out_anchor = in_anchor->GetPeerOutAnchor();
if (peer_out_anchor == nullptr) {
continue;
@@ -1236,89 +1250,106 @@ Status DavinciModel::GetGearAndRealOutSizeInfo(size_t input_count, const NodePtr
auto peer_node = peer_out_anchor->GetOwnerNode();
auto op_desc = peer_node->GetOpDesc();
GE_CHECK_NOTNULL(op_desc);
if ((peer_node->GetType() == MERGE) && (op_desc->HasAttr(ATTR_INSERT_BY_MBATCH))) {
if (GetRealOutputSizeOfMerge(idx, peer_node) != SUCCESS) {
if ((peer_node->GetType() == CASE) && (op_desc->HasAttr(ATTR_INSERT_BY_MBATCH))) {
if (GetRealOutputSizeOfCase(graph, idx, peer_node) != SUCCESS) {
GELOGE(PARAM_INVALID, "Get real output size of %s failed.", peer_node->GetName().c_str());
return PARAM_INVALID;
}
}
idx++;
}
return SUCCESS;
}

Status DavinciModel::GetRealOutputSizeOfMerge(size_t input_index, const NodePtr &merge_node) {
GELOGD("Start get output size of %s, which is %zu input to netoutput.", merge_node->GetName().c_str(), input_index);
std::map<vector<int64_t>, int64_t> gear_and_real_out_size_info;
for (auto &in_anchor : merge_node->GetAllInDataAnchors()) {
auto peer_out_anchor = in_anchor->GetPeerOutAnchor();
if (peer_out_anchor == nullptr) {
continue;
}
auto in_node = peer_out_anchor->GetOwnerNode();
GELOGD("Input node of merge is %s.", in_node->GetName().c_str());
auto op_desc = in_node->GetOpDesc();
GE_CHECK_NOTNULL(op_desc);
string batch_label;
if (AttrUtils::GetStr(op_desc, ATTR_NAME_BATCH_LABEL, batch_label)) {
size_t batch_index = static_cast<size_t>(stoi(batch_label.substr(batch_label.rfind('_') + 1)));
GELOGD("Batch index of %s is %zu.", op_desc->GetName().c_str(), batch_index);
if (batch_index > all_gears_info_.size()) {
GELOGE(PARAM_INVALID, "The value of ATTR_NAME_BATCH_LABEL is invalid.");
return PARAM_INVALID;
}

const vector<int64_t> output_size_list = ModelUtils::GetOutputSize(op_desc);
int output_index = ge::AnchorUtils::GetIdx(peer_out_anchor);
auto tensor_desc = op_desc->GetOutputDescPtr(output_index);
GE_CHECK_NOTNULL(tensor_desc);
int64_t data_size = 0;
if (TensorUtils::GetTensorSizeInBytes(*tensor_desc, data_size) != GRAPH_SUCCESS) {
GELOGE(FAILED, "Get tensor size in bytes failed.");
return FAILED;
Status DavinciModel::GetRealOutputSizeOfCase(const ComputeGraphPtr &graph, size_t input_index,
const NodePtr &case_node) {
GELOGD("Start get output size of %s, which is %zu input to netoutput.", case_node->GetName().c_str(), input_index);
const auto &func_desc = case_node->GetOpDesc();
GE_CHECK_NOTNULL(func_desc);
std::map<vector<int32_t>, int64_t> gear_and_real_out_size_info;
for (const auto &name : func_desc->GetSubgraphInstanceNames()) {
const auto &subgraph = graph->GetSubgraph(name);
if (subgraph == nullptr) {
GELOGE(GE_GRAPH_EMPTY_SUBGRAPH, "Subgraph not found, name: %s.", name.c_str());
return GE_GRAPH_EMPTY_SUBGRAPH;
}
for (auto &node : subgraph->GetDirectNode()) {
if (node->GetType() == NETOUTPUT) {
auto op_desc = node->GetOpDesc();
GE_CHECK_NOTNULL(op_desc);
string batch_label;
if (AttrUtils::GetStr(op_desc, ATTR_NAME_BATCH_LABEL, batch_label)) {
size_t batch_index = static_cast<size_t>(stoi(batch_label.substr(batch_label.rfind('_') + 1)));
GELOGD("Batch index of %s is %zu.", op_desc->GetName().c_str(), batch_index);
if (batch_index > all_gears_info_.size()) {
GELOGE(PARAM_INVALID, "The value of ATTR_NAME_BATCH_LABEL is invalid.");
return PARAM_INVALID;
}

const vector<int64_t> input_size_list = ModelUtils::GetInputSize(op_desc);
auto tensor_desc = op_desc->GetInputDescPtr(input_index);
GE_CHECK_NOTNULL(tensor_desc);
int64_t data_size = 0;
if (TensorUtils::GetTensorSizeInBytes(*tensor_desc, data_size) != GRAPH_SUCCESS) {
GELOGE(FAILED, "Get tensor size in bytes failed.");
return FAILED;
}
gear_and_real_out_size_info[all_gears_info_[batch_index]] = data_size;
GELOGD("Get real gear index is: %zu, gear info is %s, size is %ld, tensor size is %ld",
batch_index, formats::JoinToString(all_gears_info_[batch_index]).c_str(),
input_size_list[input_index], data_size);
}
break;
}
gear_and_real_out_size_info[all_gears_info_[batch_index]] = data_size;
GELOGD("Get real gear index is: %zu, gear info is %s, size is %ld, tensor size is %ld",
batch_index, formats::JoinToString(all_gears_info_[batch_index]).c_str(),
output_size_list[output_index], data_size);
}
}
merge_nodes_gear_and_real_out_size_info_[input_index] = gear_and_real_out_size_info;
return SUCCESS;
}

Status DavinciModel::GetGearAndRealOutShapeInfo(size_t input_count, const OpDescPtr &op_desc) {
GELOGD("Start to get dynamic output dims of %s.", op_desc->GetName().c_str());
Status DavinciModel::GetGearAndRealOutShapeInfo(const ComputeGraphPtr &graph, const NodePtr &node) {
GELOGD("Start to get dynamic output dims of %s.", node->GetName().c_str());
merge_nodes_gear_and_real_out_shape_info_.clear();
std::vector<std::string> dynamic_output_shape_info;
if (!AttrUtils::GetListStr(op_desc, ATTR_NAME_DYNAMIC_OUTPUT_DIMS, dynamic_output_shape_info)) {
GELOGD("Can not get dynamic output dims attr");
return SUCCESS;
}
GELOGI("Dynamic output shape info is %s", formats::JoinToString(dynamic_output_shape_info).c_str());
std::vector<vector<int64_t>> dynamic_output_shape;
ParseDynamicOutShape(dynamic_output_shape_info, dynamic_output_shape);
// idx: input_index to netoutput
for (size_t idx = 0; idx < input_count; ++idx) {
std::map<vector<int64_t>, vector<int64_t>> gear_and_real_out_shape_info;
for (auto &it : dynamic_output_shape) {
auto gear_index = static_cast<size_t>(it[0]);
if (gear_index > all_gears_info_.size()) {
GELOGE(PARAM_INVALID, "The value of cur index: %zu is invalid.", static_cast<size_t>(it[0]));
return PARAM_INVALID;
size_t idx = 0;
for (const auto &in_anchor : node->GetAllInDataAnchors()) {
auto peer_out_anchor = in_anchor->GetPeerOutAnchor();
if (peer_out_anchor == nullptr) {
continue;
}
auto peer_node = peer_out_anchor->GetOwnerNode();
auto op_desc = peer_node->GetOpDesc();
GE_CHECK_NOTNULL(op_desc);
if ((peer_node->GetType() == CASE) && (op_desc->HasAttr(ATTR_INSERT_BY_MBATCH))) {
std::vector<std::string> dynamic_output_shape_info;
if (!AttrUtils::GetListStr(node->GetOpDesc(), ATTR_NAME_DYNAMIC_OUTPUT_DIMS, dynamic_output_shape_info)) {
GELOGD("Can not get dynamic output dims attr from %s.", node->GetName().c_str());
return SUCCESS;
}
GELOGI("Dynamic output shape info is %s", formats::JoinToString(dynamic_output_shape_info).c_str());
std::vector<vector<int64_t>> dynamic_output_shape;
ParseDynamicOutShape(dynamic_output_shape_info, dynamic_output_shape);
std::map<vector<int32_t>, vector<int64_t>> gear_and_real_out_shape_info;
for (auto &it : dynamic_output_shape) {
auto gear_index = static_cast<size_t>(it[0]);
if (gear_index > all_gears_info_.size()) {
GELOGE(PARAM_INVALID, "The value of cur index: %zu is invalid.", static_cast<size_t>(it[0]));
return PARAM_INVALID;
}

if (static_cast<size_t>(it[1]) == idx) {
vector<int64_t> output_shape;
for (size_t i = 2; i < it.size(); ++i) {
output_shape.emplace_back(it[i]);
if (static_cast<size_t>(it[1]) == idx) {
vector<int64_t> output_shape;
for (size_t i = 2; i < it.size(); ++i) {
output_shape.emplace_back(it[i]);
}
gear_and_real_out_shape_info[all_gears_info_[gear_index]] = output_shape;
GELOGD("Get real gear index is: %zu, gear info is %s, output shape is %s.",
gear_index, formats::JoinToString(all_gears_info_[gear_index]).c_str(),
formats::JoinToString(output_shape).c_str());
}
gear_and_real_out_shape_info[all_gears_info_[gear_index]] = output_shape;
GELOGD("Get real gear index is: %zu, gear info is %s, output shape is %s.",
gear_index, formats::JoinToString(all_gears_info_[gear_index]).c_str(),
formats::JoinToString(output_shape).c_str());
}
merge_nodes_gear_and_real_out_shape_info_[idx] = gear_and_real_out_shape_info;
}
merge_nodes_gear_and_real_out_shape_info_[idx] = gear_and_real_out_shape_info;
idx++;
}
return SUCCESS;
}
@@ -1962,7 +1993,7 @@ void DavinciModel::CreateOutput(uint32_t index, const OpDescPtr &op_desc, InputO
uint32_t &format_result) {
/// netoutput input tensor desc
GE_IF_BOOL_EXEC(op_desc->GetInputDescPtr(index) == nullptr, GELOGE(FAILED, "OpDesc GetInputDescPtr is nullptr");
return );
return);
Format format = op_desc->GetInputDescPtr(index)->GetFormat();
GeShape shape = op_desc->GetInputDescPtr(index)->GetShape();
DataType data_type = op_desc->GetInputDescPtr(index)->GetDataType();
@@ -2567,7 +2598,7 @@ Status DavinciModel::ReturnResult(uint32_t data_id, const bool rslt_flg, const b
GELOGD("Reinit cur dynamic dims when getnext sink dynamic.");
cur_dynamic_dims_.clear();
cur_dynamic_dims_.resize(shape_of_cur_dynamic_dims_);
auto ret = rtMemcpy(cur_dynamic_dims_.data(), shape_of_cur_dynamic_dims_ * sizeof(int64_t),
auto ret = rtMemcpy(cur_dynamic_dims_.data(), shape_of_cur_dynamic_dims_ * sizeof(int32_t),
netoutput_last_input_addr_, netoutput_last_input_size_, RT_MEMCPY_DEVICE_TO_HOST);
GE_CHK_RT_RET(ret);
}
@@ -2668,11 +2699,11 @@ void *DavinciModel::Run(DavinciModel *model) {
GE_IF_BOOL_EXEC(current_data.blobs.empty(), break);
auto shape_data_buffer_data = current_data.blobs.back().data;
auto shape_data_buffer_length = current_data.blobs.back().length;
model->cur_dynamic_dims_.assign(reinterpret_cast<int64_t *>(shape_data_buffer_data),
reinterpret_cast<int64_t *>(shape_data_buffer_data) +
shape_data_buffer_length / sizeof(int64_t));
model->cur_dynamic_dims_.assign(reinterpret_cast<int32_t *>(shape_data_buffer_data),
reinterpret_cast<int32_t *>(shape_data_buffer_data) +
shape_data_buffer_length / sizeof(int32_t));
GELOGD("Data: cur dynamic dims is %s", formats::JoinToString(model->cur_dynamic_dims_).c_str());
delete[] reinterpret_cast<int64_t *>(current_data.blobs.back().data);
delete[] reinterpret_cast<int32_t *>(current_data.blobs.back().data);
current_data.blobs.pop_back();
}
GE_IF_BOOL_EXEC(ProfilingManager::Instance().ProfilingModelExecuteOn(), model->SetProfileTime(MODEL_PRE_PROC_END));


+ 9
- 7
ge/graph/load/new_model_manager/davinci_model.h View File

@@ -864,11 +864,13 @@ class DavinciModel {

void ParseDynamicOutShape(const vector<string> &str_info, vector<vector<int64_t>> &vec_info);
bool IsGetNextSinkDynamic(const OpDescPtr &op_desc);

Status InitRealSizeAndShapeInfo(const ComputeGraphPtr &compute_graph, const NodePtr &node);
void GetAllGearsInfo(const NodePtr &node);
Status GetGetDynamicDimsNodeInfo(const NodePtr &node);
Status GetGearAndRealOutSizeInfo(size_t input_count, const NodePtr &node);
Status GetRealOutputSizeOfMerge(size_t input_index, const NodePtr &merge_node);
Status GetGearAndRealOutShapeInfo(size_t input_count, const OpDescPtr &op_desc);
Status GetGearAndRealOutSizeInfo(const ComputeGraphPtr &graph, const NodePtr &node);
Status GetRealOutputSizeOfCase(const ComputeGraphPtr &graph, size_t input_index, const NodePtr &case_node);
Status GetGearAndRealOutShapeInfo(const ComputeGraphPtr &graph, const NodePtr &node);

bool is_weight_mem_has_inited_;
bool is_feature_map_mem_has_inited_;
@@ -1021,15 +1023,15 @@ class DavinciModel {
bool is_new_model_desc_{false};
bool is_online_infer_dynamic_ = false;
bool is_getnext_sink_dynamic_ = false;
vector<int64_t> cur_dynamic_dims_;
vector<int32_t> cur_dynamic_dims_;
void *netoutput_last_input_addr_ = nullptr;
int64_t netoutput_last_input_size_ = 0;
size_t shape_of_cur_dynamic_dims_ = 0;
// key: input_index: input is merge node; value: each gear info and each output size
map<size_t, map<vector<int64_t>, int64_t>> merge_nodes_gear_and_real_out_size_info_;
map<size_t, map<vector<int32_t>, int64_t>> merge_nodes_gear_and_real_out_size_info_;
// key: input_index: input is merge node; value: each gear info and each output shape
map<size_t, map<vector<int64_t>, vector<int64_t>>> merge_nodes_gear_and_real_out_shape_info_;
vector<vector<int64_t>> all_gears_info_;
map<size_t, map<vector<int32_t>, vector<int64_t>>> merge_nodes_gear_and_real_out_shape_info_;
vector<vector<int32_t>> all_gears_info_;

multimap<uint32_t, uint32_t> op_id_map_;
vector<ProfileInfo> profile_list_;


+ 6
- 6
ge/graph/load/new_model_manager/model_manager.cc View File

@@ -460,8 +460,8 @@ Status ModelManager::DataInput(const InputData &input_data, OutputData &output_d

Status ModelManager::GetCurDynamicDims(const vector<vector<int64_t>> &user_real_input_dims,
const vector<pair<string, vector<int64_t>>> &user_input_dims,
vector<int64_t> &cur_dynamic_dims) {
GELOGD(" Start get cur dynamic dims.");
vector<int32_t> &cur_dynamic_dims) {
GELOGD("Start get cur dynamic dims.");
if (user_real_input_dims.size() != user_input_dims.size()) {
GELOGE(INTERNAL_ERROR,
"The input count of user: %zu should be equal to the data count of graph: %zu",
@@ -478,7 +478,7 @@ Status ModelManager::GetCurDynamicDims(const vector<vector<int64_t>> &user_real_
}
for (size_t j = 0; j < user_input_dims.at(i).second.size(); ++j) {
if (user_input_dims.at(i).second.at(j) < 0) {
cur_dynamic_dims.emplace_back(user_real_input_dims[i][j]);
cur_dynamic_dims.emplace_back(static_cast<int32_t>(user_real_input_dims[i][j]));
}
}
}
@@ -523,7 +523,7 @@ Status ModelManager::DataInputTensor(uint32_t model_id, const std::vector<InputT
input_data.blobs.push_back(data);
}
if (!GetLocalOmgContext().user_input_dims.empty() && GetLocalOmgContext().need_multi_batch) {
std::vector<int64_t> cur_dynamic_dims;
std::vector<int32_t> cur_dynamic_dims;
if (!GetLocalOmgContext().user_real_input_dims.empty()) {
if (GetCurDynamicDims(GetLocalOmgContext().user_real_input_dims, GetLocalOmgContext().user_input_dims,
cur_dynamic_dims) != SUCCESS) {
@@ -531,9 +531,9 @@ Status ModelManager::DataInputTensor(uint32_t model_id, const std::vector<InputT
return INTERNAL_ERROR;
}
DataBuffer data;
data.data = new(std::nothrow) int64_t[cur_dynamic_dims.size()];
data.data = new(std::nothrow) int32_t[cur_dynamic_dims.size()];
GE_CHECK_NOTNULL(data.data);
uint64_t length = static_cast<uint64_t>(cur_dynamic_dims.size() * sizeof(int64_t));
uint32_t length = static_cast<uint32_t>(cur_dynamic_dims.size() * sizeof(int32_t));
GE_CHK_BOOL_EXEC(memcpy_s(data.data, length, cur_dynamic_dims.data(), length) == EOK, return INTERNAL_ERROR,
"Failed to memcpy data.");
data.length = length;


+ 3
- 3
ge/graph/load/new_model_manager/model_manager.h View File

@@ -126,14 +126,14 @@ class FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY ModelManager {
///
/// @ingroup domi_ome
/// @brief Get cur_dynamic_dims for all input.
/// @param [in] vector<vector<uint64_t>> &user_real_input_dims: dims info of all user_inputs.
/// @param [in] vector<vector<int64_t>> &user_real_input_dims: dims info of all user_inputs.
/// @param [in] vector<pair<string, vector<int64_t>>> &user_input_dims: key:name. value:dynamic dims from option.
/// @param [out] vector<uint64_t> &cur_dynamic_dims: real dims gather, where the index of -1.
/// @param [out] vector<int32_t> &cur_dynamic_dims: real dims gather, where the index of -1.
/// @return 0: SUCCESS / others: INTERNAL_ERROR
///
Status GetCurDynamicDims(const vector<vector<int64_t>> &user_real_input_dims,
const vector<pair<string, vector<int64_t>>> &user_input_dims,
vector<int64_t> &cur_dynamic_dims);
vector<int32_t> &cur_dynamic_dims);

///
/// @ingroup domi_ome


+ 3
- 1
ge/graph/load/new_model_manager/task_info/hccl_task_info.cc View File

@@ -145,7 +145,9 @@ Status HcclTaskInfo::SetFollowStream(const ge::ConstOpDescPtr &op_desc, DavinciM
} else {
GELOGI("need to reuse follow stream and create new follow stream.");
size_t created_stream_num = follow_stream_usage.size();
hccl_stream_list_ = follow_stream_usage;
for (const auto &stream : follow_stream_usage) {
hccl_stream_list_.emplace_back(stream);
}
ret = CreateStream(hccl_stream_num - created_stream_num, davinci_model, main_stream_id);
if (ret != SUCCESS) {
GELOGE(RT_FAILED, "Create hccl stream failed.");


+ 4
- 2
ge/graph/manager/graph_manager.cc View File

@@ -2780,8 +2780,10 @@ Status GraphManager::ParseInputsDims(const std::vector<InputTensorInfo> &input_t
if (!GetLocalOmgContext().dynamic_node_type.empty()) {
vector<NodePtr> data_nodes;
vector<NodePtr> getnext_nosink_nodes;
data_nodes = compute_graph_->TryGetExtAttr(kExtAttrDataNodes, data_nodes);
getnext_nosink_nodes = compute_graph_->TryGetExtAttr(kExtAttrGetNextNoSink, getnext_nosink_nodes);
data_nodes = GetLocalOmgContext().data_nodes;
getnext_nosink_nodes = GetLocalOmgContext().getnext_nosink_nodes;
GELOGD("Data nodes count is %zu, getnext nosink nodes count is %zu.", data_nodes.size(),
getnext_nosink_nodes.size());
if (GetLocalOmgContext().dynamic_node_type == DATA) {
if (getnext_nosink_nodes.empty()) {
// just data or data+getnext_sink


+ 5
- 1
ge/graph/passes/common_subexpression_elimination_pass.cc View File

@@ -26,6 +26,10 @@

namespace ge {
namespace {
std::set<std::string> un_compute_attrs = {
{ATTR_NAME_DATA_DUMP_ORIGIN_OP_NAMES},
};

std::string GetCseKey(const NodePtr &node) {
std::stringstream ss;
ss << node->GetType() << "-data-inputs-";
@@ -49,7 +53,7 @@ std::string GetCseKey(const NodePtr &node) {
ss << name << "-";
}

ss << "attrs-" << AttrUtils::GetAllAttrsStr(node->GetOpDesc());
ss << "attrs-" << AttrUtils::GetAttrsStrAfterRid(node->GetOpDesc(), un_compute_attrs);

return ss.str();
}


+ 474
- 79
ge/graph/passes/multi_batch_clone_pass.cc View File

@@ -25,31 +25,65 @@
#include "graph/utils/tensor_utils.h"
#include "graph/utils/type_utils.h"
#include "register/op_registry.h"
#include "graph/common/omg_util.h"

namespace ge {
namespace {
constexpr uint8_t kDataInIndex = 0;
constexpr uint8_t kDataOutIndex = 0;
constexpr uint8_t kCaseArgIndex = 1;
const int kDivisionConst = 2;
const size_t kNumOfGetnextNode = 1;

const std::string kMultiBatchCaseNode = "ascend_mbatch_shape_case";
const std::string kMultiBatchDataNode = "ascend_mbatch_shape_data";
const std::string kMultiBatchGetDynamicDimsNode = "ascend_mbatch_get_dynamic_dims_node";
const std::string kMultiBatchConstNode = "ascend_mbatch_shape_const";
const std::string kMultiBatchMapIndexNode = "ascend_mbatch_shape_mapindex";
const std::string kMultiBatchNodePostfix = "_ascend_mbatch_batch_";
const char *const kGetNextName = "IteratorV2";
} // namespace

inline bool IsGetNextType(const NodePtr &node) {
std::string original_type;
GE_IF_BOOL_EXEC(GetOriginalType(node, original_type) != SUCCESS,
GELOGW("Get original type failed."); return false);
return (original_type == kGetNextName);
}

Status MultiBatchClonePass::Run(ComputeGraphPtr graph) {
GE_IF_BOOL_EXEC(graph == nullptr, GELOGE(FAILED, "Original graph is nullptr"); return FAILED);
if (graph->GetParentGraph() != nullptr) {
GELOGD("Subgraph %s skip the MultiBatchClonePass", graph->GetName().c_str());
return SUCCESS;
}

if (!GetLocalOmgContext().need_multi_batch) {
GELOGI("No need to process_multi for no_train graph.");
return SUCCESS;
}
std::vector<NodePtr> data_nodes;
std::vector<NodePtr> getnext_nosink_nodes;
std::vector<NodePtr> getnext_sink_nodes;
if (multibatch::CheckSequenceOfOptions(graph, data_nodes, getnext_nosink_nodes, getnext_sink_nodes) != SUCCESS) {
GELOGE(PARAM_INVALID, "[Train_Dynamic] CheckSequenceOfOptions failed.");
return PARAM_INVALID;
}
if (multibatch::UpdateNameOfInputShape(graph, data_nodes, getnext_nosink_nodes, getnext_sink_nodes) != SUCCESS) {
GELOGE(PARAM_INVALID, "[Train_Dynamic] UpdateNameForInputShapeOfOption failed.");
return PARAM_INVALID;
}
if (multibatch::DeleteIdentityInsertByAdapter(graph) != SUCCESS) {
GELOGE(PARAM_INVALID, "[Train_Dynamic] DeleteIdentityInsertByAdapter failed.");
return PARAM_INVALID;
}
if (!multibatch::InitDynamicParams(batch_shapes_)) {
GELOGD("There is no multi-batch options, no need clone multi-batch graph");
return SUCCESS;
}

if (multibatch::CheckNegativeCountOfOptions(batch_shapes_) != SUCCESS) {
GELOGE(PARAM_INVALID, "[Train_Dynamic] Input_shape and dynamic_dims should set correct params.");
return PARAM_INVALID;
}
GELOGD("Begin to run Multi-batch clone on graph: %s", graph->GetName().c_str());
GE_CHK_STATUS_RET(multibatch::CheckDynamicParams(batch_shapes_), "Invalid multi-batch param");
if (CollectIoNodes(graph) != SUCCESS) {
@@ -66,21 +100,14 @@ Status MultiBatchClonePass::Run(ComputeGraphPtr graph) {

(void)AttrUtils::GetStr(graph, ATTR_NAME_SESSION_GRAPH_ID, session_graph_id_);
ComputeGraphPtr branch = MakeShared<ComputeGraph>(graph->GetName());
if (branch == nullptr) {
GELOGE(OUT_OF_MEMORY, "Create multi-batch graph failed");
return OUT_OF_MEMORY;
}
GE_IF_BOOL_EXEC(branch == nullptr, GELOGE(OUT_OF_MEMORY, "Create multi batch graph failed"); return OUT_OF_MEMORY);
(void)AttrUtils::SetStr(branch, ATTR_NAME_SESSION_GRAPH_ID, session_graph_id_);

graph->InValid(); // Will modify, need topological again.
graph->Swap(*branch);
if (CreateRootGraph(graph) != SUCCESS) {
return FAILED;
}

if (CreateSubgraphs(graph, branch) != SUCCESS) {
return FAILED;
}
GE_CHK_STATUS_RET(CreateRootGraph(graph), "Construct root graph failed.");
GE_CHK_STATUS_RET(CreateOriGraph(branch), "Construct original graph failed.")
GE_CHK_STATUS_RET(CreateSubgraphs(graph, branch), "Construct subgraph failed.");

GE_CHK_STATUS_RET(PruneDirectOutput(graph), "Prune direct output failed");
GELOGD("MultiBatchClonePass Leave");
@@ -95,9 +122,13 @@ Status MultiBatchClonePass::Run(ComputeGraphPtr graph) {
///
Status MultiBatchClonePass::CollectIoNodes(const ComputeGraphPtr &graph) {
for (const auto &node : graph->GetDirectNode()) {
if (!GetLocalOmgContext().dynamic_node_type.empty() && IsGetNextType(node)) {
all_data_nodes_.emplace_back(node);
GE_CHK_STATUS_RET(InitParamsOfGetNext(node), "Init params of %s failed.", node->GetName().c_str());
}
if (node->GetType() == DATA) {
all_data_nodes_.emplace_back(node);
} else if (node->GetType() == CONSTANT) {
} else if (node->GetType() == CONSTANT || node->GetType() == CONSTANTOP) {
all_const_nodes_.emplace_back(node);
} else if (node->GetType() == NETOUTPUT) {
all_output_nodes_.emplace_back(node);
@@ -114,10 +145,16 @@ Status MultiBatchClonePass::CollectIoNodes(const ComputeGraphPtr &graph) {
}

int64_t data_index = 0;
size_t getnext_node_count = 0;
for (size_t i = 0; i < all_data_nodes_.size(); ++i) {
if (IsGetNextType(all_data_nodes_[i])) {
// just one getnext node in graph
getnext_node_count++;
continue;
}
const auto &op_desc = all_data_nodes_[i]->GetOpDesc();
if (!AttrUtils::GetInt(op_desc, ATTR_NAME_INDEX, data_index)) {
(void)AttrUtils::SetInt(op_desc, ATTR_NAME_INDEX, i);
(void)AttrUtils::SetInt(op_desc, ATTR_NAME_INDEX, i - getnext_node_count);
}
}

@@ -133,7 +170,43 @@ Status MultiBatchClonePass::CollectIoNodes(const ComputeGraphPtr &graph) {
"Remove edge failed");
}
}
GELOGD("Data count is %zu, const count is %zu, getnext count is %zu, output count is %zu, direct out count is %zu.",
all_data_nodes_.size(), all_const_nodes_.size(), getnext_node_count, all_output_nodes_.size(),
direct_output_.size());

return SUCCESS;
}

Status MultiBatchClonePass::InitParamsOfGetNext(const NodePtr &node) {
data_count_from_getnext_ = 0;
getnext_sink_dynamic_dims_ = false;
GE_CHECK_NOTNULL(node->GetOpDesc());
data_count_from_getnext_ = node->GetOpDesc()->GetOutputsSize();
if (GetLocalOmgContext().dynamic_node_type == GETNEXT) {
data_count_from_getnext_ = data_count_from_getnext_ / kDivisionConst;
for (size_t i = 0; i < data_count_from_getnext_; ++i) {
GeTensorDesc output_desc = node->GetOpDesc()->GetOutputDesc(i);
GELOGD("The %zu data shape from getnext sink is %s.", i,
formats::JoinToString(output_desc.GetShape().GetDims()).c_str());
const auto &dims = output_desc.GetShape().GetDims();
if (std::all_of(dims.begin(), dims.end(), [](int64_t val) {return val >= 0; })) {
GELOGD("The %zu data from %s is static.", i, node->GetName().c_str());
} else {
getnext_sink_dynamic_dims_ = true;
GELOGD("Dynamic dims in the pattern of getnext sink.");
}
}
}
if (node->GetOutControlAnchor() != nullptr) {
for (const auto &peer_in_control_anchor : node->GetOutControlAnchor()->GetPeerInControlAnchors()) {
NodePtr next_node = peer_in_control_anchor->GetOwnerNode();
GE_CHECK_NOTNULL(next_node);
if (next_node->GetType() == CONSTANTOP) {
out_control_nodes_.insert(next_node);
GELOGD("Control edge: %s connect with %s.", node->GetName().c_str(), next_node->GetName().c_str());
}
}
}
return SUCCESS;
}

@@ -144,7 +217,11 @@ Status MultiBatchClonePass::CollectIoNodes(const ComputeGraphPtr &graph) {
/// @return 0: SUCCESS / others: FAILED
///
Status MultiBatchClonePass::CreateRootGraph(const ComputeGraphPtr &graph) {
GELOGD("Start create root graph of %s.", graph->GetName().c_str());
uint32_t input_num = all_data_nodes_.size() + all_const_nodes_.size();
if (data_count_from_getnext_ != 0) {
input_num = input_num + data_count_from_getnext_ - kNumOfGetnextNode;
}
uint32_t output_num = all_output_nodes_[0]->GetAllInDataAnchorsSize();

OpDescBuilder op_builder(kMultiBatchCaseNode, CASE);
@@ -185,6 +262,10 @@ Status MultiBatchClonePass::CreateRootGraph(const ComputeGraphPtr &graph) {
op_desc->GetName().c_str());
return FAILED;
}
if (!AttrUtils::SetBool(op_desc, ATTR_INSERT_BY_MBATCH, true)) {
GELOGE(INTERNAL_ERROR, "Failed to add insert attr on case node %s", op_desc->GetName().c_str());
return INTERNAL_ERROR;
}
GE_CHK_STATUS_RET(multibatch::StampDynamicType(op_desc), "Set dynamic type failed");

GE_CHK_STATUS_RET(CreateIndexNode(graph), "Create index node failed");
@@ -202,7 +283,7 @@ Status MultiBatchClonePass::CreateRootGraph(const ComputeGraphPtr &graph) {
/// @param [in] NodePtr node: index data node.
/// @return 0: SUCCESS / others: FAILED
///
Status MultiBatchClonePass::CreateIndexDataNode(const ComputeGraphPtr &graph, NodePtr &node) {
Status MultiBatchClonePass::CreateIndexDataNode(const ComputeGraphPtr &graph, NodePtr &shape_node) {
const OpDescPtr data_desc = MakeShared<OpDesc>(kMultiBatchDataNode, DATA);
if (data_desc == nullptr) {
GELOGE(OUT_OF_MEMORY, "Create multi-batch data node failed");
@@ -220,11 +301,12 @@ Status MultiBatchClonePass::CreateIndexDataNode(const ComputeGraphPtr &graph, No
}

size_t data_index = all_data_nodes_.size();
data_index = data_count_from_getnext_ != 0 ? data_index - kNumOfGetnextNode : data_index;
(void)AttrUtils::SetInt(data_desc, ATTR_NAME_INDEX, data_index);
(void)AttrUtils::SetBool(data_desc, ATTR_INSERT_BY_MBATCH, true);

node = graph->AddNode(data_desc);
if (node == nullptr) {
shape_node = graph->AddNode(data_desc);
if (shape_node == nullptr) {
GELOGE(OUT_OF_MEMORY, "Create multi-batch data node failed");
return OUT_OF_MEMORY;
}
@@ -286,15 +368,19 @@ Status MultiBatchClonePass::CreateIndexConstNode(const ComputeGraphPtr &graph, N
/// @return 0: SUCCESS / others: FAILED
///
Status MultiBatchClonePass::CreateIndexNode(const ComputeGraphPtr &graph) {
// Data --> MapIndex --> Case
NodePtr data_node;
GE_CHK_STATUS_RET(CreateIndexDataNode(graph, data_node), "Create data node failed");
// Data/GetDynamicDims --> MapIndex --> Case
if (!getnext_sink_dynamic_dims_) {
GE_CHK_STATUS_RET(CreateIndexDataNode(graph, shape_node_), "Create data node failed");
} else {
GE_CHK_STATUS_RET(CreateGetDynamicDimsNode(graph, shape_node_), "Create get dynamic dims node failed");
}

NodePtr const_node;
GE_CHK_STATUS_RET(CreateIndexConstNode(graph, const_node), "Create const node failed");

GELOGD("Shape node name is %s, type is %s, const node name is %s.", shape_node_->GetName().c_str(),
shape_node_->GetType().c_str(), const_node->GetName().c_str());
OpDescBuilder op_builder(kMultiBatchMapIndexNode, "MapIndex");
op_builder.AddInput("x", data_node->GetOpDesc()->GetOutputDesc(0))
op_builder.AddInput("x", shape_node_->GetOpDesc()->GetOutputDesc(0))
.AddInput("data_seq", const_node->GetOpDesc()->GetOutputDesc(0))
.AddOutput("y", GeTensorDesc(GeShape(), FORMAT_ND, DT_INT32));

@@ -309,8 +395,10 @@ Status MultiBatchClonePass::CreateIndexNode(const ComputeGraphPtr &graph) {
return OUT_OF_MEMORY;
}

if (GraphUtils::AddEdge(data_node->GetOutDataAnchor(0), index_node->GetInDataAnchor(0)) != GRAPH_SUCCESS) {
GELOGE(FAILED, "Failed to add edge between node:%s to MapIndex:%s", data_node->GetName().c_str(),
GE_CHK_STATUS_RET(AddAttrForGetDynamicDims(shape_node_), "Failed to add attr for %s.",
shape_node_->GetName().c_str());
if (GraphUtils::AddEdge(shape_node_->GetOutDataAnchor(0), index_node->GetInDataAnchor(0)) != GRAPH_SUCCESS) {
GELOGE(FAILED, "Failed to add edge between node:%s to MapIndex:%s", shape_node_->GetName().c_str(),
index_node->GetName().c_str());
return FAILED;
}
@@ -328,6 +416,120 @@ Status MultiBatchClonePass::CreateIndexNode(const ComputeGraphPtr &graph) {
return SUCCESS;
}

Status MultiBatchClonePass::CreateGetDynamicDimsNode(const ComputeGraphPtr &graph, NodePtr &shape_node) {
const OpDescPtr data_desc = MakeShared<OpDesc>(kMultiBatchGetDynamicDimsNode, GETDYNAMICDIMS);
if (data_desc == nullptr) {
GELOGE(OUT_OF_MEMORY, "Create multi-batch get dynamic dims node failed");
return OUT_OF_MEMORY;
}

// input of GetDynamicDims is shape_of_each_data, output is gear_info
for (size_t i = 0; i < GetLocalOmgContext().user_input_dims.size(); ++i) {
size_t input_shape_dims = GetLocalOmgContext().user_input_dims.at(i).second.size();
// add input desc without GeShape for const input, value of input_shape is 1 transferred by adapter
if (input_shape_dims == 1 && GetLocalOmgContext().user_input_dims.at(i).second.at(0) == 0) {
GeTensorDesc tensor_desc;
tensor_desc.SetFormat(FORMAT_ND);
tensor_desc.SetDataType(DT_INT32);
auto ret = data_desc->AddInputDesc(tensor_desc);
GE_IF_BOOL_EXEC(ret != GRAPH_SUCCESS, GELOGE(INTERNAL_ERROR, "Failed to add input desc for created data");
return FAILED);
continue;
}
GeTensorDesc tensor_desc(GeShape({static_cast<int32_t>(input_shape_dims)}), FORMAT_ND, DT_INT32);
auto ret = data_desc->AddInputDesc(tensor_desc);
GE_IF_BOOL_EXEC(ret != GRAPH_SUCCESS, GELOGE(INTERNAL_ERROR, "Failed to add input desc for created data");
return FAILED);
}
GeTensorDesc tensor_desc(GeShape({static_cast<int32_t>(batch_shapes_.at(0).size())}), FORMAT_ND, DT_INT32);
auto ret = data_desc->AddOutputDesc(tensor_desc);
GE_IF_BOOL_EXEC(ret != GRAPH_SUCCESS, GELOGE(INTERNAL_ERROR, "Failed to add output desc for created data");
return FAILED);

(void)AttrUtils::SetBool(data_desc, ATTR_INSERT_BY_MBATCH, true);

shape_node = graph->AddNode(data_desc);
if (shape_node == nullptr) {
GELOGE(OUT_OF_MEMORY, "Create multi-batch dynamic dims node failed");
return OUT_OF_MEMORY;
}
return SUCCESS;
}

Status MultiBatchClonePass::AddAttrForGetDynamicDims(const NodePtr &shape_node) {
if (!getnext_sink_dynamic_dims_) {
GELOGD("No need to add attr when not insert get dynamic dims node.");
return SUCCESS;
}
GELOGD("Add attr for :%s, type is %s:", shape_node->GetName().c_str(), shape_node->GetType().c_str());
if (!AttrUtils::SetInt(shape_node->GetOpDesc(), ATTR_GETNEXT_SINK_DATA_COUNT, data_count_from_getnext_)) {
GELOGE(INTERNAL_ERROR, "set ATTR_GETNEXT_SINK_DATA_COUNT failed");
return INTERNAL_ERROR;
}
vector<int64_t> shape_info;
for (size_t i = 0; i < GetLocalOmgContext().user_input_dims.size(); ++i) {
if (GetLocalOmgContext().user_input_dims.at(i).second.size() == 1 &&
GetLocalOmgContext().user_input_dims.at(i).second.at(0) == 0) {
shape_info.emplace_back(0);
continue;
}
shape_info.emplace_back(GetLocalOmgContext().user_input_dims.at(i).second.size());
for (size_t j = 0; j < GetLocalOmgContext().user_input_dims.at(i).second.size(); ++j) {
shape_info.emplace_back(GetLocalOmgContext().user_input_dims.at(i).second.at(j));
}
}
if (!AttrUtils::SetListInt(shape_node->GetOpDesc(), ATTR_GETNEXT_SINK_SHAPE_INFO, shape_info)) {
GELOGE(INTERNAL_ERROR, "set ATTR_GETNEXT_SINK_SHAPE_INFO failed");
return INTERNAL_ERROR;
}
return SUCCESS;
}

Status MultiBatchClonePass::LinkGetNextToGetDynamicDims(const NodePtr &getnext_node, const NodePtr &shape_node) {
GELOGD("Start relink shape anchor of %s to %s.", getnext_node->GetName().c_str(), shape_node->GetName().c_str());
size_t input_index = 0;
size_t data_count = getnext_node->GetAllOutDataAnchors().size() / kDivisionConst;
for (size_t out_index = data_count; out_index < getnext_node->GetAllOutDataAnchors().size(); ++out_index,
++input_index) {
GELOGD("Start add %s of %zu out_anchor to %s of %zu in_anchor.", getnext_node->GetName().c_str(), out_index,
shape_node->GetName().c_str(), input_index);
auto out_data_anchor = getnext_node->GetOutDataAnchor(out_index);
auto ret = GraphUtils::AddEdge(out_data_anchor, shape_node->GetInDataAnchor(input_index));
GE_IF_BOOL_EXEC(ret != GRAPH_SUCCESS, GELOGE(INTERNAL_ERROR, "Failed to link getnext %s to getdynamicdims %s",
getnext_node->GetName().c_str(), shape_node->GetName().c_str());
return INTERNAL_ERROR);
}
return SUCCESS;
}

Status MultiBatchClonePass::LinkGetDynamicDimsToNetOutput(const NodePtr &output_node) {
if (!GetLocalOmgContext().dynamic_node_type.empty()) {
if (!AttrUtils::SetStr(output_node->GetOpDesc(), ATTR_ALL_GEARS_INFO, GetLocalOmgContext().dynamic_dims)) {
GELOGE(INTERNAL_ERROR, "Failed to set all gears info attr on netoutput %s.", output_node->GetName().c_str());
return INTERNAL_ERROR;
}
}
if (getnext_sink_dynamic_dims_) {
GELOGD("Start link %s to %s.", shape_node_->GetName().c_str(), output_node->GetName().c_str());
size_t input_index = output_node->GetAllInDataAnchors().size();
if (NodeUtils::AppendInputAnchor(output_node, input_index + 1) != GRAPH_SUCCESS) {
GELOGE(INTERNAL_ERROR, "Append input anchor of %s of %zu failed.", output_node->GetName().c_str(), input_index);
return INTERNAL_ERROR;
}
auto ret = GraphUtils::AddEdge(shape_node_->GetOutDataAnchor(kDataOutIndex),
output_node->GetInDataAnchor(input_index));
GE_IF_BOOL_EXEC(ret != GRAPH_SUCCESS, GELOGE(INTERNAL_ERROR, "Failed to link netoutput %s to getdynamicdims %s",
output_node->GetName().c_str(), shape_node_->GetName().c_str());
return INTERNAL_ERROR);
if (!AttrUtils::SetBool(output_node->GetOpDesc(), ATTR_GETNEXT_SINK_DYNMAIC, true)) {
GELOGE(INTERNAL_ERROR, "Failed to set getnext sink dynamic attr on netoutput %s.",
output_node->GetName().c_str());
return INTERNAL_ERROR;
}
}
return SUCCESS;
}

///
/// @ingroup ge
/// @brief Create input node for root graph.
@@ -337,8 +539,10 @@ Status MultiBatchClonePass::CreateIndexNode(const ComputeGraphPtr &graph) {
Status MultiBatchClonePass::CreateInputNode(const ComputeGraphPtr &graph) {
// Data --> Case
std::vector<NodePtr> all_data_nodes;
const size_t arg_index = kCaseArgIndex;
for (size_t i = 0; i < all_data_nodes_.size(); ++i) {
size_t case_input_index = kCaseArgIndex;
NodePtr getnext_node = nullptr;
size_t input_index_of_getnext = 0;
for (size_t i = 0; i < all_data_nodes_.size(); ++i, ++case_input_index) {
const auto &node = all_data_nodes_[i];
const OpDescPtr op_desc = AttrUtils::CopyOpDesc(node->GetOpDesc());
if (op_desc == nullptr) {
@@ -353,22 +557,60 @@ Status MultiBatchClonePass::CreateInputNode(const ComputeGraphPtr &graph) {
op_desc->SetName(node->GetName());
const NodePtr &data = graph->AddNode(op_desc);
GE_CHK_BOOL_EXEC(data != nullptr, return FAILED, "Add node[%s] to graph failed", op_desc->GetName().c_str());
if (GraphUtils::AddEdge(data->GetOutDataAnchor(0), case_node_->GetInDataAnchor(arg_index + i)) != GRAPH_SUCCESS) {
GELOGE(FAILED, "Failed to add edge between Data:%s to Case:%s",
data->GetName().c_str(), case_node_->GetName().c_str());
return FAILED;
if (IsGetNextType(node)) {
getnext_node = data;
input_index_of_getnext = case_input_index;
case_input_index = case_input_index + data_count_from_getnext_;
continue;
} else {
if (GraphUtils::AddEdge(data->GetOutDataAnchor(0), case_node_->GetInDataAnchor(case_input_index)) !=
GRAPH_SUCCESS) {
GELOGE(FAILED, "Failed to add edge between Data:%s to Case:%s", data->GetName().c_str(),
case_node_->GetName().c_str());
return FAILED;
}
}

if (SetMaxShapeToData(data) != SUCCESS) {
if (SetMaxShape(data) != SUCCESS) {
GELOGE(FAILED, "Set max shape of %s failed.", data->GetName().c_str());
return FAILED;
}
all_data_nodes.emplace_back(data);
}
if (getnext_node != nullptr) {
if (LinkEdgeForGetNext(getnext_node, input_index_of_getnext) != SUCCESS) {
GELOGE(FAILED, "Failed to link edge for %s.", getnext_node->GetName().c_str());
return FAILED;
}
if (SetMaxShape(getnext_node) != SUCCESS) {
GELOGE(FAILED, "Set max shape of %s failed.", getnext_node->GetName().c_str());
return FAILED;
}
all_data_nodes.emplace_back(getnext_node);
}

all_data_nodes_.swap(all_data_nodes);
return SUCCESS;
}

Status MultiBatchClonePass::LinkEdgeForGetNext(const NodePtr &getnext_node, size_t &case_input_index) {
GELOGD("Start link edge for %s, which is the %zu input of %s.", getnext_node->GetName().c_str(),
case_input_index, case_node_->GetName().c_str());
for (size_t out_index = 0; out_index < data_count_from_getnext_; ++out_index, ++case_input_index) {
if (GraphUtils::AddEdge(getnext_node->GetOutDataAnchor(out_index),
case_node_->GetInDataAnchor(case_input_index)) != GRAPH_SUCCESS) {
GELOGE(FAILED, "Failed to add data edge between %zu Data:%s to %zu Case:%s", out_index,
getnext_node->GetName().c_str(), case_input_index, case_node_->GetName().c_str());
return FAILED;
}
}
if (getnext_sink_dynamic_dims_) {
GE_CHK_STATUS_RET(LinkGetNextToGetDynamicDims(getnext_node, shape_node_), "Failed to add link for %s.",
shape_node_->GetName().c_str());
}
return SUCCESS;
}

///
/// @ingroup ge
/// @brief Create Const node for root graph.
@@ -378,7 +620,11 @@ Status MultiBatchClonePass::CreateInputNode(const ComputeGraphPtr &graph) {
Status MultiBatchClonePass::CreateConstNode(const ComputeGraphPtr &graph) {
// Const --> Case
std::vector<NodePtr> all_const_nodes;
const size_t arg_index = kCaseArgIndex + all_data_nodes_.size();
size_t arg_index = kCaseArgIndex + all_data_nodes_.size();
if (data_count_from_getnext_ != 0) {
arg_index = arg_index + data_count_from_getnext_ - kNumOfGetnextNode;
}

for (size_t i = 0; i < all_const_nodes_.size(); ++i) {
const auto &node = all_const_nodes_[i];
const OpDescPtr op_desc = AttrUtils::CopyOpDesc(node->GetOpDesc());
@@ -395,15 +641,33 @@ Status MultiBatchClonePass::CreateConstNode(const ComputeGraphPtr &graph) {
const NodePtr &data = graph->AddNode(op_desc);
GE_CHK_BOOL_EXEC(data != nullptr, return FAILED, "Add node[%s] to graph failed", op_desc->GetName().c_str());
if (GraphUtils::AddEdge(data->GetOutDataAnchor(0), case_node_->GetInDataAnchor(arg_index + i)) != GRAPH_SUCCESS) {
GELOGE(FAILED, "Failed to add edge between Const:%s to Case:%s",
data->GetName().c_str(), case_node_->GetName().c_str());
GELOGE(FAILED, "Failed to add edge between Const:%s to Case:%s", data->GetName().c_str(),
case_node_->GetName().c_str());
return FAILED;
}
all_const_nodes.emplace_back(data);
}
ChangeConstToData();
all_const_nodes_.swap(all_const_nodes);
return SUCCESS;
}

void MultiBatchClonePass::ChangeConstToData() {
size_t data_index = all_data_nodes_.size();
if (data_count_from_getnext_ != 0) {
data_index = data_index + data_count_from_getnext_ - kNumOfGetnextNode;
}
for (size_t i = 0; i < all_const_nodes_.size(); ++i, ++data_index) { // Trans subgraph Const to Data.
auto &const_node = all_const_nodes_[i];
bool need_change_type = true;
if (out_control_nodes_.find(const_node) != out_control_nodes_.end()) {
GELOGD("No need to change %s to data type.", const_node->GetName().c_str());
need_change_type = false;
break;
}
if (!need_change_type) {
continue;
}
const OpDescPtr &op_desc = all_const_nodes_[i]->GetOpDesc();
op_desc->SetType(DATA);
(void)op_desc->DelAttr(ATTR_NAME_WEIGHTS); // Delete weight.
@@ -413,9 +677,6 @@ Status MultiBatchClonePass::CreateConstNode(const ComputeGraphPtr &graph) {
(void)AttrUtils::SetInt(op_desc, ATTR_NAME_INDEX, data_index);
(void)NodeUtils::AppendInputAnchor(all_const_nodes_[i], 1);
}

all_const_nodes_.swap(all_const_nodes);
return SUCCESS;
}

///
@@ -461,7 +722,8 @@ Status MultiBatchClonePass::CreateOutputNode(const ComputeGraphPtr &graph) {
}
}
}

GE_CHK_STATUS_RET(LinkGetDynamicDimsToNetOutput(node), "Failed to add edge between %s to netoutput: %s.",
shape_node_->GetName().c_str(), output->GetName().c_str());
all_output_nodes_.clear();
all_output_nodes_.emplace_back(node);
return SUCCESS;
@@ -473,34 +735,69 @@ Status MultiBatchClonePass::CreateOutputNode(const ComputeGraphPtr &graph) {
/// @param [in] const NodePtr &data: data in Root/Case graph.
/// @return 0: SUCCESS / others: FAILED
///
Status MultiBatchClonePass::SetMaxShapeToData(const NodePtr &data) {
auto data_shape = NodeUtils::GetOutputDesc(*data, kDataOutIndex).GetShape();
auto data_name = data->GetName();
Status MultiBatchClonePass::SetMaxShape(const NodePtr &data) {
GELOGD("Start set max shape for %s.", data->GetName().c_str());
if (!IsGetNextType(data)) {
if (SetMaxShapeToData(data, kDataOutIndex) != SUCCESS) {
GELOGE(PARAM_INVALID, "Failed to update max shape of %s.", data->GetName().c_str());
return PARAM_INVALID;
}
} else {
for (size_t out_anchor_index = 0; out_anchor_index < data_count_from_getnext_; ++out_anchor_index) {
if (SetMaxShapeToData(data, out_anchor_index) != SUCCESS) {
GELOGE(PARAM_INVALID, "Failed to update max shape of %s.", data->GetName().c_str());
return PARAM_INVALID;
}
}
}
return SUCCESS;
}

Status MultiBatchClonePass::SetMaxShapeToData(const NodePtr &node, size_t out_anchor_index) {
GELOGD("Start update max shape of %s, %zu output.", node->GetName().c_str(), out_anchor_index);
auto data_shape = NodeUtils::GetOutputDesc(*node, out_anchor_index).GetShape();
string data_name = node->GetName();
if (IsGetNextType(node)) {
data_name.append("_").append(std::to_string(out_anchor_index));
}
GELOGD("Update max shape of %s, shape dims is %s.", data_name.c_str(),
formats::JoinToString(data_shape.GetDims()).c_str());
const auto &dims = data_shape.GetDims();
if (std::all_of(dims.begin(), dims.end(), [](int64_t val) { return val >= 0; })) {
return SUCCESS;
if (!IsGetNextType(node)) {
if (std::all_of(dims.begin(), dims.end(), [](int64_t val) { return val >= 0; })) {
GELOGD("No need to do anything for static data.");
return SUCCESS;
}
} else {
if (std::all_of(dims.begin(), dims.end(), [](int64_t val) { return val >= 0; })) {
if (getnext_sink_dynamic_dims_) {
// need to update shape of Shape_node when getnext node has dynamic data
GE_CHK_STATUS_RET(UpdateShapeOfShapeNode(node, out_anchor_index), "Failed to update shape of shape node");
}
return SUCCESS;
}
}
(void)AttrUtils::SetListInt(data->GetOpDesc(), ATTR_MBATCH_ORIGIN_INPUT_DIMS, data_shape.GetDims());
(void)AttrUtils::SetListInt(node->GetOpDesc(), ATTR_MBATCH_ORIGIN_INPUT_DIMS, data_shape.GetDims());

GeTensorDesc tensor(NodeUtils::GetOutputDesc(*data, kDataOutIndex));
GeTensorDesc tensor(NodeUtils::GetOutputDesc(*node, kDataOutIndex));
std::vector<std::string> input_dims_str;
for (size_t i = 0; i < batch_shapes_.size(); ++i) {
auto shape = data_shape;
auto ret = multibatch::CalcShape(data_to_dynamic_info_.at(data_name).at(i), shape);
if (ret != SUCCESS) {
GELOGE(ret, "Failed to calculate the shape for data node %s, the shape may not match", data->GetName().c_str());
GELOGE(ret, "Failed to calculate the shape for data node %s, the shape may not match", node->GetName().c_str());
return ret;
}
tensor.SetShape(shape);
int64_t tensor_size = 0;
(void)TensorUtils::GetTensorSizeInBytes(tensor, tensor_size);
string input_str = TypeUtils::FormatToSerialString(tensor.GetFormat()) + ":" +
TypeUtils::DataTypeToSerialString(tensor.GetDataType()) + ":" + data->GetName() + ":" +
TypeUtils::DataTypeToSerialString(tensor.GetDataType()) + ":" + node->GetName() + ":" +
std::to_string(tensor_size) + ":" + std::to_string(tensor.GetShape().GetDimNum()) + ":" +
formats::JoinToString(tensor.GetShape().GetDims());
input_dims_str.emplace_back(input_str);
}
(void)AttrUtils::SetListStr(data->GetOpDesc(), "_all_origin_gears_inputs", input_dims_str);
(void)AttrUtils::SetListStr(node->GetOpDesc(), "_all_origin_gears_inputs", input_dims_str);

size_t max_shape_index = 0;
int64_t max_size = 0;
@@ -519,18 +816,72 @@ Status MultiBatchClonePass::SetMaxShapeToData(const NodePtr &data) {
max_shape_index = i;
}
}
return SetShapeToData(data_to_dynamic_info_.at(data_name).at(max_shape_index), node, data_shape, out_anchor_index);
}

return SetShapeToData(data_to_dynamic_info_.at(data_name).at(max_shape_index), data, data_shape);
///
/// @ingroup ge
/// @brief Set max shape to Data/GetNext node in root graph.
/// @param [in] const std::vector<int64_t> &shapes: dims of shape.
/// @param [in] const NodePtr &data: data in Root/Case graph.
/// @param [in] GeShape &data_shape: dims of data node.
/// @param [in] size_t out_anchor_index: out anchor index of data node.
/// @return 0: SUCCESS / others: FAILED
///
Status MultiBatchClonePass::SetShapeToData(const std::vector<int64_t> &shapes, const NodePtr &data, GeShape &data_shape,
size_t out_anchor_index) {
GELOGD("Start set shape to %zu out of %s.", out_anchor_index, data->GetName().c_str());
if (multibatch::CalcShape(shapes, data_shape) != SUCCESS) {
GELOGE(INTERNAL_ERROR, "Failed to calculate the batched shape for data node %s, the shapes may not match",
data->GetName().c_str());
return INTERNAL_ERROR;
}

if (NodeUtils::UpdateOutputShape(*data, out_anchor_index, data_shape) != GRAPH_SUCCESS) {
GELOGE(INTERNAL_ERROR, "Failed to update output shape for data %s", data->GetName().c_str());
return INTERNAL_ERROR;
}
if (!IsGetNextType(data)) {
if (NodeUtils::UpdateInputShape(*data, kDataInIndex, data_shape) != GRAPH_SUCCESS) {
GELOGE(INTERNAL_ERROR, "Failed to update input shape for data %s", data->GetName().c_str());
return INTERNAL_ERROR;
}
} else {
if (getnext_sink_dynamic_dims_) {
// need to update shape of Shape_node when getnext_sink_dynamic
GE_CHK_STATUS_RET(UpdateShapeOfShapeNode(data, out_anchor_index), "Failed to update shape of shape node");
}
}

GELOGI("Update the data %s input/output shape to the max %s", data->GetName().c_str(),
formats::ShapeToString(data_shape).c_str());
return SUCCESS;
}

Status MultiBatchClonePass::UpdateShapeOfShapeNode(const NodePtr &node, size_t out_anchor_index) {
GELOGD("Start update output shape of shape node insert by adapter, which is the %zu out of %s.", out_anchor_index,
node->GetName().c_str());
auto data_shape = NodeUtils::GetOutputDesc(*node, out_anchor_index).GetShape();
size_t shape_index = out_anchor_index + (node->GetAllOutDataAnchors().size() / kDivisionConst);
GeTensorDesc output_desc = node->GetOpDesc()->GetOutputDesc(shape_index);
std::vector<int64_t> output_dims = {static_cast<int64_t>(data_shape.GetDims().size())};
GeShape output_shape(output_dims);
output_desc.SetShape(output_shape);
if (node->GetOpDesc()->UpdateOutputDesc(shape_index, output_desc) != SUCCESS) {
GELOGE(FAILED, "Update output desc fail.");
return FAILED;
}
return SUCCESS;
}

///
/// @ingroup ge
/// @brief Update Data node in Subgraph.
/// @param [in] const NodePtr &data: data in Subgraph.
/// @param [in] size_t index: The batch index.
/// @param [in] size_t batch_index: The batch index.
/// @return 0: SUCCESS / others: FAILED
///
Status MultiBatchClonePass::UpdateSubgraphData(const NodePtr &data, size_t index) {
Status MultiBatchClonePass::UpdateSubgraphData(const NodePtr &data, size_t batch_index) {
int node_index = -1;
if (!AttrUtils::GetInt(data->GetOpDesc(), ATTR_NAME_INDEX, node_index)) {
GELOGE(FAILED, "Failed to get index from data[%s]", data->GetName().c_str());
@@ -545,6 +896,8 @@ Status MultiBatchClonePass::UpdateSubgraphData(const NodePtr &data, size_t index

auto data_shape = NodeUtils::GetOutputDesc(*data, kDataOutIndex).GetShape();
const auto &dims = data_shape.GetDims();
GELOGD("Start update shape of %s , batch index is %zu, dims is %s.", data->GetName().c_str(), batch_index,
formats::JoinToString(dims).c_str());
if (std::all_of(dims.begin(), dims.end(), [](int64_t val) { return val >= 0; })) {
return SUCCESS;
}
@@ -559,35 +912,77 @@ Status MultiBatchClonePass::UpdateSubgraphData(const NodePtr &data, size_t index
}

auto parent_name = data_name.substr(0, pos);
return SetShapeToData(data_to_dynamic_info_.at(parent_name).at(index), data, data_shape);
return SetShapeToData(data_to_dynamic_info_.at(parent_name).at(batch_index), data, data_shape, kDataOutIndex);
}

///
/// @ingroup ge
/// @brief Set max shape to Data node in root graph.
/// @param [in] const std::vector<int64_t> &shapes: dims of shape.
/// @param [in] const NodePtr &data: data in Root/Case graph.
/// @param [in] GeShape &data_shape: dims of data node.
/// @return 0: SUCCESS / others: FAILED
///
Status MultiBatchClonePass::SetShapeToData(const vector<int64_t> &shapes, const NodePtr &data, GeShape &data_shape) {
// must not be error, the calc result has been checked in function InsertSwitchNForData
if (multibatch::CalcShape(shapes, data_shape) != SUCCESS) {
return INTERNAL_ERROR;
Status MultiBatchClonePass::CreateOriGraph(const ComputeGraphPtr &graph) {
if (data_count_from_getnext_ == 0) {
GELOGD("No need to change original graph without getnext node.");
return SUCCESS;
}

if (NodeUtils::UpdateInputShape(*data, kDataInIndex, data_shape) != GRAPH_SUCCESS) {
GELOGE(INTERNAL_ERROR, "Failed to update input shape for data %s", data->GetName().c_str());
return INTERNAL_ERROR;
GELOGD("Start change original graph: %s when exit getnext node.", graph->GetName().c_str());
size_t data_index = all_data_nodes_.size() - kNumOfGetnextNode;
for (const auto &node : graph->GetDirectNode()) {
if (IsGetNextType(node)) {
for (size_t out_index = 0; out_index < data_count_from_getnext_; ++out_index, ++data_index) {
auto out_data_anchor = node->GetOutDataAnchor(out_index);
GE_IF_BOOL_EXEC(out_data_anchor == nullptr, continue);
NodePtr data_node = CreateDataNode(graph, out_data_anchor, data_index);
GE_IF_BOOL_EXEC(data_node == nullptr, GELOGE(INTERNAL_ERROR, "Create %zu data node failed.",
out_data_anchor->GetIdx()); return INTERNAL_ERROR);
for (auto &in_anchor : out_data_anchor->GetPeerInDataAnchors()) {
GE_IF_BOOL_EXEC(in_anchor == nullptr, continue);
NodePtr dst_node = in_anchor->GetOwnerNode();
if (GraphUtils::RemoveEdge(out_data_anchor, in_anchor) != GRAPH_SUCCESS) {
GELOGE(INTERNAL_ERROR, "Failed to remove edge between %s to %s", node->GetName().c_str(),
dst_node->GetName().c_str());
return INTERNAL_ERROR;
}
if (GraphUtils::AddEdge(data_node->GetOutDataAnchor(0), dst_node->GetInDataAnchor(in_anchor->GetIdx())) !=
GRAPH_SUCCESS) {
GELOGE(INTERNAL_ERROR, "Failed to add edge between %s to %s", data_node->GetName().c_str(),
dst_node->GetName().c_str());
return INTERNAL_ERROR;
}
}
}
if (graph->RemoveNode(node) != GRAPH_SUCCESS) {
GELOGE(GRAPH_FAILED, "Remove node %s failed!", node->GetName().c_str());
return GRAPH_FAILED;
}
break;
}
}
return SUCCESS;
}

if (NodeUtils::UpdateOutputShape(*data, kDataOutIndex, data_shape) != GRAPH_SUCCESS) {
GELOGE(INTERNAL_ERROR, "Failed to update output shape for data %s", data->GetName().c_str());
return INTERNAL_ERROR;
NodePtr MultiBatchClonePass::CreateDataNode(const ComputeGraphPtr &graph, const OutDataAnchorPtr &out_data_anchor,
size_t data_index) {
size_t out_anchor_index = out_data_anchor->GetIdx();
std::string node_name = out_data_anchor->GetOwnerNode()->GetName() + "_" + std::to_string(out_anchor_index);
OpDescPtr op_desc = MakeShared<OpDesc>(node_name, DATA);
if (op_desc == nullptr) {
GELOGE(OUT_OF_MEMORY, "Create data node failed.");
return nullptr;
}
(void)AttrUtils::SetInt(op_desc, ATTR_NAME_INDEX, data_index);

GELOGI("Update %s input/output shape to %s", data->GetName().c_str(), formats::ShapeToString(data_shape).c_str());
return SUCCESS;
OpDescPtr getnext_op_desc = out_data_anchor->GetOwnerNode()->GetOpDesc();
if (getnext_op_desc == nullptr) {
GELOGE(OUT_OF_MEMORY, "Op desc of %s is nullptr.", out_data_anchor->GetOwnerNode()->GetName().c_str());
return nullptr;
}
if (op_desc->AddInputDesc(getnext_op_desc->GetOutputDesc(out_anchor_index)) != GRAPH_SUCCESS) {
GELOGE(INTERNAL_ERROR, "Add %s input desc failed.", op_desc->GetName().c_str());
return nullptr;
}
if (op_desc->AddOutputDesc(getnext_op_desc->GetOutputDesc(out_anchor_index)) != GRAPH_SUCCESS) {
GELOGE(INTERNAL_ERROR, "Add %s output desc failed.", op_desc->GetName().c_str());
return nullptr;
}
NodePtr data_node = graph->AddNode(op_desc);
GELOGD("Success create %s node.", data_node->GetName().c_str());
return data_node;
}

///
@@ -598,17 +993,14 @@ Status MultiBatchClonePass::SetShapeToData(const vector<int64_t> &shapes, const
/// @return 0: SUCCESS / others: FAILED
///
Status MultiBatchClonePass::CreateSubgraphs(const ComputeGraphPtr &graph, const ComputeGraphPtr &branch) {
GELOGD("Start create subgraphs for %s.", graph->GetName().c_str());
const auto &op_desc = case_node_->GetOpDesc();
for (size_t i = 0; i < batch_shapes_.size(); ++i) {
std::vector<NodePtr> input_nodes;
std::vector<NodePtr> output_nodes;
const std::string postfix = kMultiBatchNodePostfix + std::to_string(i);
ComputeGraphPtr subgraph = (i == 0) ? branch : GraphUtils::CloneGraph(branch, postfix, input_nodes, output_nodes);
if (subgraph == nullptr) {
GELOGE(FAILED, "Create multi-batch case node failed");
return FAILED;
}

GE_IF_BOOL_EXEC(subgraph == nullptr, GELOGE(FAILED, "Create multi-batch case node failed"); return FAILED);
subgraph->SetName("Batch_" + std::to_string(i));
subgraph->SetParentNode(case_node_);
subgraph->SetParentGraph(graph);
@@ -621,6 +1013,7 @@ Status MultiBatchClonePass::CreateSubgraphs(const ComputeGraphPtr &graph, const
op_desc->AddSubgraphName(key_name);
op_desc->SetSubgraphInstanceName(i, subgraph->GetName());

GELOGD("The %s has %zu input, %zu output.", subgraph->GetName().c_str(), input_nodes.size(), output_nodes.size());
for (const auto &data : input_nodes) {
GE_CHK_STATUS_RET(UpdateSubgraphData(data, i), "Update %s failed", subgraph->GetName().c_str());
}
@@ -666,6 +1059,7 @@ Status MultiBatchClonePass::UpdateSubgraphOutput(const NodePtr &output_node) {
/// @return 0: SUCCESS / others: FAILED
///
Status MultiBatchClonePass::PruneDirectOutput(const ComputeGraphPtr &graph) {
GELOGD("Start prune direct output.");
const auto &func_desc = case_node_->GetOpDesc();
uint32_t unused_num = 0;
uint32_t output_num = func_desc->GetOutputsSize();
@@ -710,6 +1104,7 @@ Status MultiBatchClonePass::PruneDirectOutput(const ComputeGraphPtr &graph) {
///
Status MultiBatchClonePass::UpdateOutputTensor(uint32_t parent_index, uint32_t unused_num) {
if (unused_num == 0) {
GELOGD("No need to update output tensor.");
return SUCCESS;
}



+ 41
- 17
ge/graph/passes/multi_batch_clone_pass.h View File

@@ -36,6 +36,7 @@ class MultiBatchClonePass : public GraphPass {
/// @return 0: SUCCESS / others: FAILED
///
Status CollectIoNodes(const ComputeGraphPtr &graph);
Status InitParamsOfGetNext(const NodePtr &node);

///
/// @ingroup ge
@@ -49,10 +50,12 @@ class MultiBatchClonePass : public GraphPass {
/// @ingroup ge
/// @brief Create index data node for root graph.
/// @param [in] const ComputeGraphPtr &graph: Root/Case graph.
/// @param [in] NodePtr node: index data node.
/// @param [in] NodePtr shape_node: index data node, DATA or GETDYNAMICDIMS type.
/// @return 0: SUCCESS / others: FAILED
///
Status CreateIndexDataNode(const ComputeGraphPtr &graph, NodePtr &node);
Status CreateIndexDataNode(const ComputeGraphPtr &graph, NodePtr &shape_node);

Status CreateGetDynamicDimsNode(const ComputeGraphPtr &graph, NodePtr &shape_node);

///
/// @ingroup ge
@@ -70,6 +73,9 @@ class MultiBatchClonePass : public GraphPass {
/// @return 0: SUCCESS / others: FAILED
///
Status CreateIndexNode(const ComputeGraphPtr &graph);
Status AddAttrForGetDynamicDims(const NodePtr &shape_node);
Status LinkGetNextToGetDynamicDims(const NodePtr &getnext_node, const NodePtr &shape_node);
Status LinkGetDynamicDimsToNetOutput(const NodePtr &output_node);

///
/// @ingroup ge
@@ -78,39 +84,54 @@ class MultiBatchClonePass : public GraphPass {
/// @return 0: SUCCESS / others: FAILED
///
Status CreateInputNode(const ComputeGraphPtr &graph);
Status LinkEdgeForGetNext(const NodePtr &getnext_node, size_t &case_input_index);

///
/// @ingroup ge
/// @brief Create Const node for root graph.
/// @param [in] const ComputeGraphPtr &graph: Root/Case graph.
/// @brief Set max shape to Data node in root graph.
/// @param [in] const NodePtr &data: data in Root/Case graph.
/// @return 0: SUCCESS / others: FAILED
///
Status CreateConstNode(const ComputeGraphPtr &graph);
Status SetMaxShape(const NodePtr &data);
Status SetMaxShapeToData(const NodePtr &node, size_t out_anchor_index);
///
/// @ingroup ge
/// @brief Set max shape to Data/GetNext node in root graph.
/// @param [in] const std::vector<int64_t> &shapes: dims of shape.
/// @param [in] const NodePtr &data: data in Root/Case graph.
/// @param [in] GeShape &data_shape: dims of data node.
/// @param [in] size_t out_anchor_index: out anchor index of data node.
/// @return 0: SUCCESS / others: FAILED
///
Status SetShapeToData(const std::vector<int64_t> &shapes, const NodePtr &data, GeShape &data_shape,
size_t out_anchor_index);
Status UpdateShapeOfShapeNode(const NodePtr &node, size_t out_anchor_index);

///
/// @ingroup ge
/// @brief Create output node for root graph.
/// @brief Create Const node for root graph.
/// @param [in] const ComputeGraphPtr &graph: Root/Case graph.
/// @return 0: SUCCESS / others: FAILED
///
Status CreateOutputNode(const ComputeGraphPtr &graph);
Status CreateConstNode(const ComputeGraphPtr &graph);
void ChangeConstToData();

///
/// @ingroup ge
/// @brief Set max shape to Data node in root graph.
/// @param [in] const NodePtr &data: data in Root/Case graph.
/// @brief Create output node for root graph.
/// @param [in] const ComputeGraphPtr &graph: Root/Case graph.
/// @return 0: SUCCESS / others: FAILED
///
Status SetMaxShapeToData(const NodePtr &data);
Status CreateOutputNode(const ComputeGraphPtr &graph);

///
/// @ingroup ge
/// @brief Update Data node in Subgraph.
/// @param [in] const NodePtr &data: data in Subgraph.
/// @param [in] size_t index: The batch index.
/// @param [in] size_t batch_index: The batch index.
/// @return 0: SUCCESS / others: FAILED
///
Status UpdateSubgraphData(const NodePtr &data, size_t index);
Status UpdateSubgraphData(const NodePtr &data, size_t batch_index);

///
/// @ingroup ge
@@ -122,13 +143,12 @@ class MultiBatchClonePass : public GraphPass {

///
/// @ingroup ge
/// @brief Set max shape to Data node in root graph.
/// @param [in] const std::vector<int64_t> &shapes: dims of shape.
/// @param [in] const NodePtr &data: data in Root/Case graph.
/// @param [in] GeShape &data_shape: dims of data node.
/// @brief Create nodes for root graph.
/// @param [in] const ComputeGraphPtr &graph: Original graph.
/// @return 0: SUCCESS / others: FAILED
///
Status SetShapeToData(const std::vector<int64_t> &shapes, const NodePtr &data, GeShape &data_shape);
Status CreateOriGraph(const ComputeGraphPtr &graph);
NodePtr CreateDataNode(const ComputeGraphPtr &graph, const OutDataAnchorPtr &out_data_anchor, size_t data_index);

///
/// @ingroup ge
@@ -168,6 +188,10 @@ class MultiBatchClonePass : public GraphPass {
std::map<string, vector<vector<int64_t>>> data_to_dynamic_info_;

NodePtr case_node_;
size_t data_count_from_getnext_ = 0;
bool getnext_sink_dynamic_dims_ = false;
NodePtr shape_node_;
std::set<NodePtr> out_control_nodes_;
};
} // namespace ge
#endif // GE_GRAPH_PASSES_MULTI_BATCH_CLONE_PASS_H_

+ 4
- 0
ge/graph/passes/unused_args_clean_pass.cc View File

@@ -204,6 +204,10 @@ Status UnusedArgsCleanPass::RemoveInputTensor(const map<ComputeGraphPtr, map<uin
GE_CHK_GRAPH_STATUS_RET(GraphUtils::RemoveEdge(out_anchor, old_anchor), "Remove edge failed");
GELOGI("Remove edge: %s %s", out_node->GetName().c_str(), func_node->GetName().c_str());

if (out_node->GetInDataNodes().size() == 0 && out_node->GetOutAllNodes().size() == 0) {
GE_CHK_GRAPH_STATUS_RET(out_node->GetOwnerComputeGraph()->RemoveNode(out_node), "Remove node failed: %s",
out_node->GetName().c_str());
}
return SUCCESS;
}
} // namespace ge

+ 5
- 7
ge/graph/preprocess/multi_batch_copy_graph.cc View File

@@ -1692,13 +1692,11 @@ Status MultiBatchGraphCopyer::LinkToNodeOutBranch(const NodePtr &node) {
}

Status ProcessMultiBatch(ComputeGraphPtr &graph) {
if (GetLocalOmgContext().dynamic_node_type.empty()) {
const char *multi_batch_with_switchn = std::getenv("MULTI_BATCH_WITH_SWITCHN");
if (multi_batch_with_switchn == nullptr) {
PassManager pass_manager;
GE_CHK_STATUS_RET(pass_manager.AddPass("MultiBatchClonePass", new (std::nothrow) MultiBatchClonePass));
return pass_manager.Run(graph);
}
const char *multi_batch_with_switchn = std::getenv("MULTI_BATCH_WITH_SWITCHN");
if (multi_batch_with_switchn == nullptr) {
PassManager pass_manager;
GE_CHK_STATUS_RET(pass_manager.AddPass("MultiBatchClonePass", new (std::nothrow) MultiBatchClonePass));
return pass_manager.Run(graph);
}
if (!GetLocalOmgContext().need_multi_batch) {
GELOGI("No need to process_multi for no_train graph.");


+ 2
- 3
ge/graph/preprocess/multi_batch_options.cc View File

@@ -99,9 +99,8 @@ Status DistinguishGetNextAndData(ComputeGraphPtr &graph, vector<NodePtr> &data_n
}
GELOGI("Data count is %zu, getnext nosink count is %zu, getnext sink count is %zu.", data_nodes.size(),
getnext_nosink_nodes.size(), getnext_sink_nodes.size());
GE_IF_BOOL_EXEC(!graph->SetExtAttr(kExtAttrDataNodes, data_nodes), GELOGW("Set data nodes attr failed.");)
GE_IF_BOOL_EXEC(!graph->SetExtAttr(kExtAttrGetNextNoSink, getnext_nosink_nodes),
GELOGW("Set getnext nosink nodes attr failed.");)
GetLocalOmgContext().data_nodes = data_nodes;
GetLocalOmgContext().getnext_nosink_nodes = getnext_nosink_nodes;
return SUCCESS;
}



+ 3
- 0
inc/framework/omg/omg_inner_types.h View File

@@ -26,6 +26,7 @@
#include <vector>
#include "framework/common/fmk_error_codes.h"
#include "register/register_fmk_types.h"
#include "graph/node.h"

using domi::DOMI_TENSOR_ND;
using domi::DOMI_TENSOR_RESERVED;
@@ -120,6 +121,8 @@ struct OmgContext {
std::vector<std::vector<int64_t>> user_real_input_dims;
std::vector<int64_t> cur_dynamic_dims;
bool need_multi_batch = false;
std::vector<NodePtr> data_nodes;
std::vector<NodePtr> getnext_nosink_nodes;
};
} // namespace ge



+ 1
- 1
metadef

@@ -1 +1 @@
Subproject commit 44bcbb5ea25ada1a5393aa4c7f554d40b6859b18
Subproject commit fe37bc343ea52c76d35e9e9ec83cea0151bfa900

+ 1
- 1
parser

@@ -1 +1 @@
Subproject commit 5b93b050dd7ca5b77c3001a790031d877fa10956
Subproject commit 336cd3107253d3fe41cfb9fec2db62b5f3d8a33b

+ 1
- 0
tests/ut/ge/CMakeLists.txt View File

@@ -627,6 +627,7 @@ set(PASS_TEST_FILES
"graph/passes/net_output_pass_unittest.cc"
"graph/passes/no_use_reshape_remove_pass_unittest.cc"
"graph/passes/infershape_pass_unittest.cc"
"graph/passes/multi_batch_clone_pass_unittest.cc"
)

set(KERNEL_TEST_FILES


+ 101
- 0
tests/ut/ge/graph/load/davinci_model_unittest.cc View File

@@ -32,6 +32,18 @@ class UtestDavinciModel : public testing::Test {
void SetUp() {}

void TearDown() {}
public:
NodePtr MakeNode(const ComputeGraphPtr &graph, uint32_t in_num, uint32_t out_num, string name, string type) {
GeTensorDesc test_desc(GeShape(), FORMAT_NCHW, DT_FLOAT);
auto op_desc = std::make_shared<OpDesc>(name, type);
for (auto i = 0; i < in_num; ++i) {
op_desc->AddInputDesc(test_desc);
}
for (auto i = 0; i < out_num; ++i) {
op_desc->AddOutputDesc(test_desc);
}
return graph->AddNode(op_desc);
}
};

TEST_F(UtestDavinciModel, init_success) {
@@ -324,5 +336,94 @@ TEST_F(UtestDavinciModel, SyncVarData_test) {
EXPECT_NE(model.SyncVarData(), SUCCESS);
}

TEST_F(UtestDavinciModel, InitRealSizeAndShapeInfo_succ1) {
DavinciModel model(0, nullptr);
model.ge_model_ = make_shared<GeModel>();
ComputeGraphPtr graph = make_shared<ComputeGraph>("default");

GeTensorDesc tensor(GeShape(), FORMAT_NCHW, DT_FLOAT);
OpDescPtr op_output = CreateOpDesc("output_ascend_mbatch_batch_1", NETOUTPUT);
op_output->AddInputDesc(tensor);
op_output->SetInputOffset({1024});
NodePtr node_output = graph->AddNode(op_output);
EXPECT_EQ(model.InitRealSizeAndShapeInfo(graph, node_output), SUCCESS);
}

TEST_F(UtestDavinciModel, InitRealSizeAndShapeInfo_succ2) {
DavinciModel model(0, nullptr);
ComputeGraphPtr graph = std::make_shared<ComputeGraph>("test_graph");

OpDescPtr data1 = CreateOpDesc("data1", DATA);
GeTensorDesc shape_desc(GeShape({4,3,224,224}), FORMAT_NCHW, DT_FLOAT);
data1->AddInputDesc(shape_desc);
data1->AddOutputDesc(shape_desc);
NodePtr data1_node = graph->AddNode(data1);

OpDescPtr case_node = CreateOpDesc("case1", CASE);
GeTensorDesc tensor(GeShape(), FORMAT_NCHW, DT_FLOAT);
case_node->AddInputDesc(tensor);
case_node->AddOutputDesc(tensor);
NodePtr case1_node = graph->AddNode(case_node);

OpDescPtr output = CreateOpDesc("output1", NETOUTPUT);
output->AddInputDesc(tensor);
output->SetSrcName( { "case1" } );
output->SetSrcIndex( { 0 } );
NodePtr output_node = graph->AddNode(output);

GraphUtils::AddEdge(data1_node->GetOutDataAnchor(0), case1_node->GetInDataAnchor(0));
GraphUtils::AddEdge(case1_node->GetOutDataAnchor(0), output_node->GetInDataAnchor(0));
(void)AttrUtils::SetStr(output_node->GetOpDesc(), ATTR_ALL_GEARS_INFO, "1;2;4;8");
(void)AttrUtils::SetBool(case_node, ATTR_INSERT_BY_MBATCH, true);

model.is_getnext_sink_dynamic_ = false;
model.is_online_infer_dynamic_ = true;
auto ret = model.InitRealSizeAndShapeInfo(graph, output_node);
// GetGearAndRealOutShapeInfo without ATTR_NAME_DYNAMIC_OUTPUT_DIMS
EXPECT_EQ(ret, SUCCESS);
vector<string> dynamic_output_dims = {"0,0,1,1,0,2,2,0,4,3,0,8"};
(void)AttrUtils::SetListStr(output_node->GetOpDesc(), ATTR_NAME_DYNAMIC_OUTPUT_DIMS, dynamic_output_dims);
ret = model.InitRealSizeAndShapeInfo(graph, output_node);
EXPECT_EQ(ret, SUCCESS);
}

TEST_F(UtestDavinciModel, InitRealSizeAndShapeInfo_succ3) {
DavinciModel model(0, nullptr);
ComputeGraphPtr graph = std::make_shared<ComputeGraph>("test_graph");

OpDescPtr data1 = CreateOpDesc("data1", DATA);
GeTensorDesc shape_desc(GeShape({4,3,224,224}), FORMAT_NCHW, DT_FLOAT);
data1->AddInputDesc(shape_desc);
data1->AddOutputDesc(shape_desc);
NodePtr data1_node = graph->AddNode(data1);

OpDescPtr shape_node = CreateOpDesc("ascend_mbatch_get_dynamic_dims_node", GETDYNAMICDIMS);
GeTensorDesc in_tensor(GeShape(), FORMAT_NCHW, DT_FLOAT);
GeTensorDesc out_tensor(GeShape({4,3}), FORMAT_NCHW, DT_FLOAT);
shape_node->AddInputDesc(in_tensor);
shape_node->AddOutputDesc(out_tensor);
NodePtr get_dynamic_dims_node = graph->AddNode(shape_node);

OpDescPtr output = CreateOpDesc("output1", NETOUTPUT);
GeTensorDesc tensor(GeShape(), FORMAT_NCHW, DT_FLOAT);
output->AddInputDesc(tensor);
output->SetSrcName( { "data1", "ascend_mbatch_get_dynamic_dims_node" } );
output->SetSrcIndex( { 0, 1 } );
NodePtr output_node = graph->AddNode(output);
GraphUtils::AddEdge(data1_node->GetOutDataAnchor(0), output_node->GetInDataAnchor(0));
GraphUtils::AddEdge(get_dynamic_dims_node->GetOutDataAnchor(0), output_node->GetInDataAnchor(1));

(void)AttrUtils::SetStr(output_node->GetOpDesc(), ATTR_ALL_GEARS_INFO, "1,3;;4,3;,3");

model.is_getnext_sink_dynamic_ = true;
model.is_online_infer_dynamic_ = false;
auto ret = model.InitRealSizeAndShapeInfo(graph, output_node);
EXPECT_EQ(ret, SUCCESS);
model.runtime_param_.mem_base = (uint8_t *)0x08000000;
model.runtime_param_.mem_size = 4;
ret = model.InitRealSizeAndShapeInfo(graph, output_node);
EXPECT_EQ(ret, SUCCESS);
}

} // namespace ge

+ 247
- 0
tests/ut/ge/graph/passes/multi_batch_clone_pass_unittest.cc View File

@@ -0,0 +1,247 @@
/**
* Copyright 2021 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 "graph/passes/multi_batch_clone_pass.h"

#include <gtest/gtest.h>
#include <set>
#include <string>

#include "inc/pass_manager.h"
#include "graph/utils/tensor_utils.h"
#include "graph/common/local_context.h"
#include "graph/passes/multi_batch_pass.h"
#include "graph/preprocess/multi_batch_copy_graph.h"
#include "graph/preprocess/insert_op/util_insert_aipp_op.h"
#include "framework/omg/omg_inner_types.h"
#include "register/op_registry.h"


namespace ge{
class UtestMultiBatchClonePass : public testing::Test {
protected:
void SetUp() {
SetLocalOmgContext(domi::GetContext());
GetLocalOmgContext().dynamic_image_size.clear();
GetLocalOmgContext().dynamic_batch_size.clear();
}
void TearDown() {
GetLocalOmgContext().dynamic_image_size.clear();
GetLocalOmgContext().dynamic_batch_size.clear();
GetLocalOmgContext().dynamic_node_type.clear();
}

public:
NodePtr MakeNode(const ComputeGraphPtr &graph, uint32_t in_num, uint32_t out_num, string name, string type) {
GeTensorDesc test_desc(GeShape(), FORMAT_NCHW, DT_FLOAT);
auto op_desc = std::make_shared<OpDesc>(name, type);
for (auto i = 0; i < in_num; ++i) {
op_desc->AddInputDesc(test_desc);
}
for (auto i = 0; i < out_num; ++i) {
op_desc->AddOutputDesc(test_desc);
}
return graph->AddNode(op_desc);
}

NodePtr MakeConstNode(const ComputeGraphPtr &graph) {
static uint32_t index = 0;
GeTensorDesc test_desc(GeShape(), FORMAT_NCHW, DT_FLOAT);
auto op_desc = std::make_shared<OpDesc>("dynamic_const_" + std::to_string(index++), "Const");
op_desc->AddOutputDesc(test_desc);
return graph->AddNode(op_desc);
}

void make_original_graph(const ComputeGraphPtr &graph) {
auto conv2d_node = MakeNode(graph, 3, 1, "conv1", "Conv2D");
{
auto data1 = MakeNode(graph, 1, 1, "data", "Data");
GeTensorDesc tensor_desc(GeShape({-1,3,224,224}), FORMAT_NCHW, DT_FLOAT);
data1->GetOpDesc()->UpdateInputDesc(0, tensor_desc);
data1->GetOpDesc()->UpdateOutputDesc(0, tensor_desc);
AttrUtils::SetInt(data1->GetOpDesc(), ATTR_NAME_INDEX, 0);
GetLocalOmgContext().user_input_dims = {std::make_pair(data1->GetOpDesc()->GetName(), vector<int64_t>{-1,3,224,224})};

GraphUtils::AddEdge(data1->GetOutDataAnchor(0), conv2d_node->GetInDataAnchor(0));
auto const1 = MakeConstNode(graph);
GraphUtils::AddEdge(const1->GetOutDataAnchor(0), conv2d_node->GetInDataAnchor(1));
auto const2 = MakeConstNode(graph);
GraphUtils::AddEdge(const2->GetOutDataAnchor(0), conv2d_node->GetInDataAnchor(2));
}

auto bn_conv1 = MakeNode(graph, 4, 1, "bn_conv1", "BNInference");
{
GraphUtils::AddEdge(conv2d_node->GetOutDataAnchor(0), bn_conv1->GetInDataAnchor(0));
auto const1 = MakeConstNode(graph);
GraphUtils::AddEdge(const1->GetOutDataAnchor(0), bn_conv1->GetInDataAnchor(1));
auto const2 = MakeConstNode(graph);
GraphUtils::AddEdge(const2->GetOutDataAnchor(0), bn_conv1->GetInDataAnchor(2));
auto const3= MakeConstNode(graph);
GraphUtils::AddEdge(const3->GetOutDataAnchor(0), bn_conv1->GetInDataAnchor(3));
}

auto scale_conv1 = MakeNode(graph, 4, 1, "scale1", "Scale");
{
GraphUtils::AddEdge(bn_conv1->GetOutDataAnchor(0), scale_conv1->GetInDataAnchor(0));
auto const1 = MakeConstNode(graph);
GraphUtils::AddEdge(const1->GetOutDataAnchor(0), scale_conv1->GetInDataAnchor(1));
auto const2 = MakeConstNode(graph);
GraphUtils::AddEdge(const2->GetOutDataAnchor(0), scale_conv1->GetInDataAnchor(2));
}

auto output_node = MakeNode(graph, 1, 0, "output1", "NetOutput");
GraphUtils::AddEdge(scale_conv1->GetOutDataAnchor(0), output_node->GetInDataAnchor(0));
}

void GraphWithJustData(const ComputeGraphPtr &graph) {
auto conv2d_node = MakeNode(graph, 3, 1, "conv1", "Conv2D");
{
auto data1 = MakeNode(graph, 1, 1, "data", "Data");
GeTensorDesc tensor_desc(GeShape({-1,3,224,224}), FORMAT_NCHW, DT_FLOAT);
data1->GetOpDesc()->UpdateInputDesc(0, tensor_desc);
data1->GetOpDesc()->UpdateOutputDesc(0, tensor_desc);
AttrUtils::SetInt(data1->GetOpDesc(), ATTR_NAME_INDEX, 0);
GetLocalOmgContext().user_input_dims = {std::make_pair(data1->GetOpDesc()->GetName(), vector<int64_t>{-1,3,224,224})};

GraphUtils::AddEdge(data1->GetOutDataAnchor(0), conv2d_node->GetInDataAnchor(0));
auto const1 = MakeConstNode(graph);
GraphUtils::AddEdge(const1->GetOutDataAnchor(0), conv2d_node->GetInDataAnchor(1));
auto const2 = MakeConstNode(graph);
GraphUtils::AddEdge(const2->GetOutDataAnchor(0), conv2d_node->GetInDataAnchor(2));
}

auto output_node = MakeNode(graph, 1, 0, "output1", "NetOutput");
GraphUtils::AddEdge(conv2d_node->GetOutDataAnchor(0), output_node->GetInDataAnchor(0));
}

void GraphWithGetNextNosink(const ComputeGraphPtr &graph) {
auto conv2d_node = MakeNode(graph, 3, 1, "conv1", "Conv2D");
{
auto data1 = MakeNode(graph, 1, 1, "IteratorGetNext_data", "Data");
GeTensorDesc tensor_desc(GeShape({-1,3,224,224}), FORMAT_NCHW, DT_FLOAT);
data1->GetOpDesc()->UpdateInputDesc(0, tensor_desc);
data1->GetOpDesc()->UpdateOutputDesc(0, tensor_desc);
AttrUtils::SetInt(data1->GetOpDesc(), ATTR_NAME_INDEX, 0);
GetLocalOmgContext().user_input_dims = {std::make_pair(data1->GetOpDesc()->GetName(), vector<int64_t>{-1,3,224,224})};

GraphUtils::AddEdge(data1->GetOutDataAnchor(0), conv2d_node->GetInDataAnchor(0));
auto const1 = MakeConstNode(graph);
GraphUtils::AddEdge(const1->GetOutDataAnchor(0), conv2d_node->GetInDataAnchor(1));
auto const2 = MakeConstNode(graph);
GraphUtils::AddEdge(const2->GetOutDataAnchor(0), conv2d_node->GetInDataAnchor(2));
}

auto output_node = MakeNode(graph, 1, 0, "output1", "NetOutput");
GraphUtils::AddEdge(conv2d_node->GetOutDataAnchor(0), output_node->GetInDataAnchor(0));
}

// getnext has one data and has one out of shape
void GraphWithGetNextSink(const ComputeGraphPtr &graph) {
auto conv2d_node = MakeNode(graph, 3, 1, "conv1", "Conv2D");
{
auto data1 = MakeNode(graph, 1, 2, "data", "IteratorV2");
GeTensorDesc tensor_desc(GeShape({-1,3,224,224}), FORMAT_NCHW, DT_FLOAT);
GeTensorDesc shape_desc(GeShape({4,3,224,224}), FORMAT_NCHW, DT_FLOAT);
data1->GetOpDesc()->UpdateOutputDesc(0, tensor_desc);
data1->GetOpDesc()->UpdateOutputDesc(1, shape_desc);
AttrUtils::SetInt(data1->GetOpDesc(), ATTR_NAME_INDEX, 0);
GetLocalOmgContext().user_input_dims = {std::make_pair(data1->GetOpDesc()->GetName(), vector<int64_t>{-1,3,224,224})};

GraphUtils::AddEdge(data1->GetOutDataAnchor(0), conv2d_node->GetInDataAnchor(0));
auto identity = MakeNode(graph, 1, 0, "identity", "Identity");
GraphUtils::AddEdge(data1->GetOutDataAnchor(1), identity->GetInDataAnchor(0));
auto const1 = MakeConstNode(graph);
GraphUtils::AddEdge(const1->GetOutDataAnchor(0), conv2d_node->GetInDataAnchor(1));
auto const2 = MakeConstNode(graph);
GraphUtils::AddEdge(const2->GetOutDataAnchor(0), conv2d_node->GetInDataAnchor(2));
}

auto output_node = MakeNode(graph, 1, 0, "output1", "NetOutput");
GraphUtils::AddEdge(conv2d_node->GetOutDataAnchor(0), output_node->GetInDataAnchor(0));
}
};

// graph is nullptr
TEST_F(UtestMultiBatchClonePass, graph_nullptr) {
PassManager pass_manager;
pass_manager.AddPass("MultiBatchClonePass", new (std::nothrow) MultiBatchClonePass);
ComputeGraphPtr graph;
EXPECT_EQ(pass_manager.Run(graph), PARAM_INVALID);
}

// graph with subgraph
TEST_F(UtestMultiBatchClonePass, graph_with_subgraph) {
PassManager pass_manager;
pass_manager.AddPass("MultiBatchClonePass", new (std::nothrow) MultiBatchClonePass);
ComputeGraphPtr graph = std::make_shared<ComputeGraph>("test_graph");
make_original_graph(graph);
EXPECT_EQ(pass_manager.Run(graph), SUCCESS);

ComputeGraphPtr owner = std::make_shared<ComputeGraph>("test_owner");
auto func_node = MakeNode(owner, 3, 1, "test_if", "If");
graph->SetParentNode(func_node);
graph->SetParentGraph(owner);
EXPECT_EQ(pass_manager.Run(graph), SUCCESS);
}

//graph is uncompute graph, not need to do multi batch
TEST_F(UtestMultiBatchClonePass, uncompute_graph) {
MultiBatchClonePass multi_batch_clone;
ComputeGraphPtr graph = std::make_shared<ComputeGraph>("test_graph");
make_original_graph(graph);
GetLocalOmgContext().need_multi_batch = false;
EXPECT_EQ(multi_batch_clone.Run(graph), SUCCESS);
}


//compute_graph with data from DATA
TEST_F(UtestMultiBatchClonePass, compute_graph_with_data) {
MultiBatchClonePass multi_batch_clone;
ComputeGraphPtr graph = std::make_shared<ComputeGraph>("test_graph");
GraphWithJustData(graph);
GetLocalOmgContext().need_multi_batch = true;
EXPECT_EQ(multi_batch_clone.Run(graph), SUCCESS);
GetLocalOmgContext().dynamic_node_type = DATA;
GetLocalOmgContext().dynamic_dims = "1;2;4;8";
EXPECT_EQ(multi_batch_clone.Run(graph), SUCCESS);
EXPECT_EQ(GetLocalOmgContext().data_nodes.size(), 1);
}

//compute_graph with data from GetNext_nosink
TEST_F(UtestMultiBatchClonePass, compute_graph_with_getnext_nosink) {
MultiBatchClonePass multi_batch_clone;
ComputeGraphPtr graph = std::make_shared<ComputeGraph>("test_graph");
GraphWithGetNextNosink(graph);
GetLocalOmgContext().need_multi_batch = true;
GetLocalOmgContext().dynamic_node_type = GETNEXT;
GetLocalOmgContext().dynamic_dims = "1;2;4;8";
EXPECT_EQ(multi_batch_clone.Run(graph), SUCCESS);
EXPECT_EQ(GetLocalOmgContext().getnext_nosink_nodes.size(), 1);
}

//compute_graph with data from GetNext_nosink
TEST_F(UtestMultiBatchClonePass, compute_graph_with_getnext_sink) {
MultiBatchClonePass multi_batch_clone;
ComputeGraphPtr graph = std::make_shared<ComputeGraph>("test_graph");
GraphWithGetNextSink(graph);
GetLocalOmgContext().need_multi_batch = true;
GetLocalOmgContext().dynamic_node_type = GETNEXT;
GetLocalOmgContext().dynamic_dims = "1;2;4;8";
EXPECT_EQ(multi_batch_clone.Run(graph), SUCCESS);
EXPECT_EQ(GetLocalOmgContext().getnext_nosink_nodes.size(), 0);
}

}

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