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skipping missing layers and layer failures

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This commit is contained in:
Smirnov Egor 2021-06-21 11:11:14 +03:00
parent 25f908b320
commit dc5199feea
2 changed files with 41 additions and 8 deletions
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6
apps/model-diagnostics/model_diagnostics.cpp
View File

@ -1,6 +1,6 @@
/*************************************************
USAGE:
./model_diagnostics -m <onnx file location>
./model_diagnostics -m <model file location>
**************************************************/
#include <opencv2/dnn.hpp>
#include <opencv2/core/utils/filesystem.hpp>
@ -32,7 +32,7 @@ static std::string checkFileExists(const std::string& fileName)
}
std::string diagnosticKeys =
"{ model m | | Path to the model .onnx file. }"
"{ model m | | Path to the model file. }"
"{ config c | | Path to the model configuration file. }"
"{ framework f | | [Optional] Name of the model framework. }";
@ -41,7 +41,7 @@ std::string diagnosticKeys =
int main( int argc, const char** argv )
{
CommandLineParser argParser(argc, argv, diagnosticKeys);
argParser.about("Use this tool to run the diagnostics of provided ONNX model"
argParser.about("Use this tool to run the diagnostics of provided ONNX/TF model"
"to obtain the information about its support (supported layers).");
if (argc == 1)

41
modules/dnn/src/tensorflow/tf_importer.cpp
View File

@ -32,6 +32,8 @@ namespace cv {
namespace dnn {
CV__DNN_INLINE_NS_BEGIN
extern bool DNN_DIAGNOSTICS_RUN;
#if HAVE_PROTOBUF
using ::google::protobuf::RepeatedField;
@ -471,6 +473,7 @@ public:
TFImporter(Net& net, const char *dataModel, size_t lenModel,
const char *dataConfig = NULL, size_t lenConfig = 0);
protected:
std::unique_ptr<Net> utilNet;
Net& dstNet;
void populateNet();
@ -2337,7 +2340,8 @@ void TFImporter::parseCustomLayer(tensorflow::GraphDef& net, const tensorflow::N
}
TFImporter::TFImporter(Net& net, const char *model, const char *config)
: dstNet(net), dispatch(buildDispatchMap())
: utilNet(DNN_DIAGNOSTICS_RUN ? new Net : nullptr),
dstNet(DNN_DIAGNOSTICS_RUN ? *utilNet : net), dispatch(buildDispatchMap())
{
if (model && model[0])
{
@ -2358,7 +2362,8 @@ TFImporter::TFImporter(
const char *dataModel, size_t lenModel,
const char *dataConfig, size_t lenConfig
)
: dstNet(net), dispatch(buildDispatchMap())
: utilNet(DNN_DIAGNOSTICS_RUN ? new Net : nullptr),
dstNet(DNN_DIAGNOSTICS_RUN ? *utilNet : net), dispatch(buildDispatchMap())
{
if (dataModel != NULL && lenModel > 0)
{
@ -2615,6 +2620,11 @@ DataLayout TFImporter::predictOutputDataLayout(const tensorflow::NodeDef& layer)
return it->second;
}
Ptr<Layer> dummy_constructor(LayerParams & params)
{
return new Layer(params);
}
void TFImporter::populateNet()
{
CV_Assert(netBin.ByteSize() || netTxt.ByteSize());
@ -2757,9 +2767,9 @@ void TFImporter::parseNode(const tensorflow::NodeDef& layer)
const std::string& name = layer.name();
const std::string& type = layer.op();
LayerParams layerParams;
try
{
LayerParams layerParams;
if (layers_to_ignore.find(name) != layers_to_ignore.end())
{
@ -2777,14 +2787,37 @@ void TFImporter::parseNode(const tensorflow::NodeDef& layer)
}
else
{
if (DNN_DIAGNOSTICS_RUN && !LayerFactory::createLayerInstance(type, layerParams))
{
CV_LOG_ERROR(NULL, "DNN/TF: Node='" << name << "' of type='"<< type
<< "' is not supported. This error won't be displayed again.");
LayerFactory::registerLayer(type, dummy_constructor);
}
parseCustomLayer(net, layer, layerParams);
}
}
catch (const std::exception& e)
{
CV_LOG_ERROR(NULL, "DNN/TF: Can't parse layer for node='" << name << "'. Exception: " << e.what());
if (!DNN_DIAGNOSTICS_RUN)
{
CV_LOG_ERROR(NULL, "DNN/TF: Can't parse layer for node='" << name << "' of type='" << type
<< "'. Exception: " << e.what());
throw;
}
else
{
CV_LOG_ERROR(NULL, "DNN/TF: Can't parse layer for node='" << name << "' of type='" << type
<< "'. Exception: " << e.what());
// internal layer failure (didnt call addLayer)
if (dstNet.getLayerId(name) == -1)
{
int id = dstNet.addLayer(name, type, layerParams);
layer_id[name] = id;
}
}
}
}
} // namespace