Skip to content

Maajid/implement read network #64

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
wants to merge 4 commits into from
Closed

Maajid/implement read network #64

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
07264f9
Implemented ReadNetwork() method
MaajidKhan Jan 13, 2021
b78f964
Using the InferenceEngineException
MaajidKhan Jan 14, 2021
442bb82
Fixes compilation issue with ov_2021.1
MaajidKhan Jan 14, 2021
15e6ead
Merge branch 'master' into maajid/Implement_Read_Network
suryasidd Jan 20, 2021
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
22 changes: 17 additions & 5 deletions onnxruntime/core/providers/openvino/backend_utils.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -47,11 +47,6 @@ struct static_cast_int64 {

std::shared_ptr<InferenceEngine::CNNNetwork>
CreateCNNNetwork(const Provider_ModelProto& model_proto, const GlobalContext& global_context, const SubGraphContext& subgraph_context, std::map<std::string, std::shared_ptr<ngraph::Node>>& const_outputs_map) {
#if (defined OPENVINO_2020_2) || (defined OPENVINO_2020_3)
ORT_UNUSED_PARAMETER(const_outputs_map);
#endif

std::istringstream model_stream{model_proto.SerializeAsString()};
std::shared_ptr<ngraph::Function> ng_function;

#ifndef NDEBUG
Expand All @@ -60,6 +55,9 @@ CreateCNNNetwork(const Provider_ModelProto& model_proto, const GlobalContext& gl
}
#endif

#if (defined OPENVINO_2020_2) || (defined OPENVINO_2020_3)
ORT_UNUSED_PARAMETER(const_outputs_map);
std::istringstream model_stream{model_proto.SerializeAsString()};
try {
ng_function = ngraph::onnx_import::import_onnx_model(model_stream);
LOGS_DEFAULT(INFO) << "ONNX Import Done";
Expand All @@ -68,6 +66,20 @@ CreateCNNNetwork(const Provider_ModelProto& model_proto, const GlobalContext& gl
} catch (...) {
ORT_THROW(log_tag + "[OpenVINO-EP] Unknown exception while importing model to nGraph Func");
}
#else
InferenceEngine::CNNNetwork cnn_network;
const std::string model = model_proto.SerializeAsString();
InferenceEngine::Blob::Ptr blob = {nullptr};
try {
cnn_network = global_context.ie_core.ReadNetwork(model, blob);
LOGS_DEFAULT(INFO) << "Read network Done";
} catch (const InferenceEngine::details::InferenceEngineException& e) {
ORT_THROW(log_tag + "[OpenVINO-EP] Exception while Reading network: " + std::string(e.what()));
} catch (...) {
ORT_THROW(log_tag + "[OpenVINO-EP] Unknown exception while Reading network");
}
ng_function = cnn_network.getFunction();
#endif

if (global_context.device_type.find("GPU") != std::string::npos &&
subgraph_context.precision == InferenceEngine::Precision::FP16) {
Expand Down
17 changes: 9 additions & 8 deletions onnxruntime/core/providers/openvino/ov_versions/capability_2021_1.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -272,16 +272,17 @@ static bool IsUnsupportedOpMode(const Node* node, const GraphViewer& graph_viewe
return true;
}
} else if (optype == "Max" || optype == "Min" || optype == "Mean" || optype == "Sum") {
if (GetInputCount(node, initializers) == 1)
if (GetInputCount(node, initializers) == 1) {
return true;
if (optype == "Max" || optype == "Min") {
for (size_t i = 0; i < node->InputDefs().size(); i++) {
auto dtype = node->InputDefs()[i]->TypeAsProto()->tensor_type().elem_type();
if (dtype == ONNX_NAMESPACE::TensorProto_DataType::TensorProto_DataType_UINT8 ||
dtype == ONNX_NAMESPACE::TensorProto_DataType::TensorProto_DataType_INT16)
return true;
}
}
if (optype == "Max" || optype == "Min") {
for (size_t i = 0; i < node->InputDefs().size(); i++) {
auto dtype = node->InputDefs()[i]->TypeAsProto()->tensor_type().elem_type();
if (dtype == ONNX_NAMESPACE::TensorProto_DataType::TensorProto_DataType_UINT8 ||
dtype == ONNX_NAMESPACE::TensorProto_DataType::TensorProto_DataType_INT16)
return true;
}
}
} else if (optype == "Clip") {
//Only float 16, float and double data types are supported
const bool data_is_float = node->InputDefs()[0]->Type()->find("float") != std::string::npos;
Expand Down