@@ -528,9 +528,19 @@ Status GeGenerator::GenerateModel(const Graph &graph, const string &file_name_pr | |||||
return SUCCESS; | return SUCCESS; | ||||
} | } | ||||
Status GeGenerator::BuildSingleOp(OpDescPtr &op_desc, const vector<GeTensor> &inputs, const vector<GeTensor> &outputs, | |||||
const string &model_file_name, OpEngineType engine_type, ModelBufferData &model_buff, | |||||
bool is_offline) { | |||||
namespace { | |||||
bool IsNeedConnectInputOpForSingleOp(GeTensorDesc &tensor_desc) { | |||||
bool is_need = true; | |||||
// format and dtype is all reserved, stand for Optional input. When singleop scene | |||||
if (tensor_desc.GetFormat() == FORMAT_RESERVED && tensor_desc.GetDataType() == DT_UNDEFINED) { | |||||
is_need = false; | |||||
} | |||||
return is_need; | |||||
} | |||||
} | |||||
Status GeGenerator::CheckForSingleOp(OpDescPtr &op_desc, const vector<GeTensor> &inputs, | |||||
const vector<GeTensor> &outputs) { | |||||
GE_CHECK_NOTNULL_EXEC(op_desc, return PARAM_INVALID); | GE_CHECK_NOTNULL_EXEC(op_desc, return PARAM_INVALID); | ||||
if (!inputs.empty() && (inputs.size() != op_desc->GetAllInputsSize())) { | if (!inputs.empty() && (inputs.size() != op_desc->GetAllInputsSize())) { | ||||
GELOGE(PARAM_INVALID, "Tensor size: %zu, Inputs size: %zu", inputs.size(), op_desc->GetAllInputsSize()); | GELOGE(PARAM_INVALID, "Tensor size: %zu, Inputs size: %zu", inputs.size(), op_desc->GetAllInputsSize()); | ||||
@@ -540,7 +550,17 @@ Status GeGenerator::BuildSingleOp(OpDescPtr &op_desc, const vector<GeTensor> &in | |||||
GELOGE(PARAM_INVALID, "Tensor size: %zu, Outputs size: %zu", outputs.size(), op_desc->GetOutputsSize()); | GELOGE(PARAM_INVALID, "Tensor size: %zu, Outputs size: %zu", outputs.size(), op_desc->GetOutputsSize()); | ||||
return PARAM_INVALID; | return PARAM_INVALID; | ||||
} | } | ||||
return SUCCESS; | |||||
} | |||||
Status GeGenerator::BuildSingleOp(OpDescPtr &op_desc, const vector<GeTensor> &inputs, const vector<GeTensor> &outputs, | |||||
const string &model_file_name, OpEngineType engine_type, ModelBufferData &model_buff, | |||||
bool is_offline) { | |||||
if (CheckForSingleOp(op_desc, inputs, outputs) != SUCCESS) { | |||||
GELOGE(PARAM_INVALID, "input param is invalid when build single op!"); | |||||
return PARAM_INVALID; | |||||
} | |||||
OmgContext &omg_context = (impl_ == nullptr) ? domi::GetContext() : impl_->omg_context_; | OmgContext &omg_context = (impl_ == nullptr) ? domi::GetContext() : impl_->omg_context_; | ||||
omg_context.is_dynamic_input = ContainsDynamicInpus(*op_desc); | omg_context.is_dynamic_input = ContainsDynamicInpus(*op_desc); | ||||
@@ -575,12 +595,18 @@ Status GeGenerator::BuildSingleOp(OpDescPtr &op_desc, const vector<GeTensor> &in | |||||
if (inputs.empty()) { | if (inputs.empty()) { | ||||
for (const auto &input_desc : op_desc->GetAllInputsDescPtr()) { | for (const auto &input_desc : op_desc->GetAllInputsDescPtr()) { | ||||
GE_CHECK_NOTNULL_EXEC(input_desc, return INTERNAL_ERROR); | GE_CHECK_NOTNULL_EXEC(input_desc, return INTERNAL_ERROR); | ||||
if (!IsNeedConnectInputOpForSingleOp(*input_desc)) { | |||||
continue; | |||||
} | |||||
GE_CHK_STATUS_RET_NOLOG(AddInputs(compute_graph, op_node, *input_desc, arg_index, false)); | GE_CHK_STATUS_RET_NOLOG(AddInputs(compute_graph, op_node, *input_desc, arg_index, false)); | ||||
arg_index++; | arg_index++; | ||||
} | } | ||||
} else { | } else { | ||||
for (const auto &in_desc : inputs) { | for (const auto &in_desc : inputs) { | ||||
GeTensorDesc input_desc = in_desc.GetTensorDesc(); | GeTensorDesc input_desc = in_desc.GetTensorDesc(); | ||||
if (!IsNeedConnectInputOpForSingleOp(input_desc)) { | |||||
continue; | |||||
} | |||||
GE_CHK_STATUS_RET_NOLOG(AddInputs(compute_graph, op_node, input_desc, arg_index, true)); | GE_CHK_STATUS_RET_NOLOG(AddInputs(compute_graph, op_node, input_desc, arg_index, true)); | ||||
arg_index++; | arg_index++; | ||||
} | } | ||||
@@ -226,16 +226,11 @@ bool SingleOpParser::Validate(const SingleOpDesc &op_desc) { | |||||
} | } | ||||
int index = 0; | int index = 0; | ||||
for (auto &tensor_desc : op_desc.input_desc) { | |||||
if (tensor_desc.type == DT_UNDEFINED) { | |||||
ErrorManager::GetInstance().ATCReportErrMessage("E10027", {"input", "index"}, {"input", std::to_string(index)}); | |||||
GELOGE(false, "Input's dataType is invalid when the index is %d", index); | |||||
return false; | |||||
} | |||||
if (tensor_desc.format == FORMAT_RESERVED) { | |||||
ErrorManager::GetInstance().ATCReportErrMessage("E10028", {"input", "index"}, {"input", std::to_string(index)}); | |||||
GELOGE(PARAM_INVALID, "Input's format is invalid when the index is %d", index); | |||||
for (auto &tensor_desc : op_desc.output_desc) { | |||||
if ((tensor_desc.type == DT_UNDEFINED && tensor_desc.format != FORMAT_RESERVED) || | |||||
(tensor_desc.type != DT_UNDEFINED && tensor_desc.format == FORMAT_RESERVED)){ | |||||
ErrorManager::GetInstance().ATCReportErrMessage("E10027", {"input", "index"}, {"output", std::to_string(index)}); | |||||
GELOGE(PARAM_INVALID, "Input's dataType or format is invalid when the index is %d", index); | |||||
return false; | return false; | ||||
} | } | ||||
++index; | ++index; | ||||
@@ -53,7 +53,7 @@ class GeGenerator { | |||||
Status GenerateOfflineModel(const Graph &graph, const std::string &file_name_prefix, | Status GenerateOfflineModel(const Graph &graph, const std::string &file_name_prefix, | ||||
const std::vector<GeTensor> &inputs = std::vector<GeTensor>()); | const std::vector<GeTensor> &inputs = std::vector<GeTensor>()); | ||||
Status GenerateOnlineModel(const Graph &graph, const vector<GeTensor> &inputs, ge::ModelBufferData& model); | |||||
Status GenerateOnlineModel(const Graph &graph, const vector<GeTensor> &inputs, ge::ModelBufferData &model); | |||||
Status GenerateInfershapeGraph(const Graph &graph); | Status GenerateInfershapeGraph(const Graph &graph); | ||||
@@ -77,16 +77,16 @@ class GeGenerator { | |||||
/// @param [in] engine_type: specific engine. | /// @param [in] engine_type: specific engine. | ||||
/// @param [out] model_buff: model buff of single op. | /// @param [out] model_buff: model buff of single op. | ||||
/// @return SUCCESS or FAILED | /// @return SUCCESS or FAILED | ||||
Status BuildSingleOpModel(OpDescPtr &op_desc, const vector<GeTensor> &inputs, | |||||
const vector<GeTensor> &outputs, OpEngineType engine_type, | |||||
ModelBufferData &model_buff); | |||||
Status BuildSingleOpModel(OpDescPtr &op_desc, const vector<GeTensor> &inputs, const vector<GeTensor> &outputs, | |||||
OpEngineType engine_type, ModelBufferData &model_buff); | |||||
private: | private: | ||||
Status GenerateModel(const Graph &graph, const string &file_name_prefix, | |||||
const vector<GeTensor> &inputs, ge::ModelBufferData& model, bool is_offline = true); | |||||
Status GenerateModel(const Graph &graph, const string &file_name_prefix, const vector<GeTensor> &inputs, | |||||
ge::ModelBufferData &model, bool is_offline = true); | |||||
Status BuildSingleOp(OpDescPtr &op_desc, const vector<GeTensor> &inputs, const vector<GeTensor> &outputs, | Status BuildSingleOp(OpDescPtr &op_desc, const vector<GeTensor> &inputs, const vector<GeTensor> &outputs, | ||||
const string &model_file_name, OpEngineType engine_type, | |||||
ModelBufferData &model_buff, bool is_offline = true); | |||||
const string &model_file_name, OpEngineType engine_type, ModelBufferData &model_buff, | |||||
bool is_offline = true); | |||||
Status CheckForSingleOp(OpDescPtr &op_desc, const vector<GeTensor> &inputs, const vector<GeTensor> &outputs); | |||||
class Impl; | class Impl; | ||||
@@ -1 +1 @@ | |||||
Subproject commit ae80e9e2369458d468c16fd95bb970922ff3a084 | |||||
Subproject commit 1cc55bcae09902b3d158993dd57bfbd1d3337066 |
@@ -1 +1 @@ | |||||
Subproject commit c1530c6083ea18c6c6c4c14b08253830e3982344 | |||||
Subproject commit db4e6070bb2cec01cead264a44ceae07e7f3048e |