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Element-wise subtraction from TensorFlow

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This commit is contained in:
Dmitry Kurtaev 2018-12-07 13:38:05 +03:00
parent 492a072ea8
commit 8422dda2c7
3 changed files with 14 additions and 33 deletions
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4
modules/dnn/src/layers/eltwise_layer.cpp
View File

@ -98,7 +98,8 @@ public:
{ {
return backendId == DNN_BACKEND_OPENCV || return backendId == DNN_BACKEND_OPENCV ||
backendId == DNN_BACKEND_HALIDE || backendId == DNN_BACKEND_HALIDE ||
(backendId == DNN_BACKEND_INFERENCE_ENGINE && (op != SUM || coeffs.empty())); (backendId == DNN_BACKEND_INFERENCE_ENGINE &&
(preferableTarget != DNN_TARGET_MYRIAD || coeffs.empty()));
} }
bool getMemoryShapes(const std::vector<MatShape> &inputs, bool getMemoryShapes(const std::vector<MatShape> &inputs,
@ -427,6 +428,7 @@ public:
lp.type = "Eltwise"; lp.type = "Eltwise";
lp.precision = InferenceEngine::Precision::FP32; lp.precision = InferenceEngine::Precision::FP32;
std::shared_ptr<InferenceEngine::EltwiseLayer> ieLayer(new InferenceEngine::EltwiseLayer(lp)); std::shared_ptr<InferenceEngine::EltwiseLayer> ieLayer(new InferenceEngine::EltwiseLayer(lp));
ieLayer->coeff = coeffs;
if (op == SUM) if (op == SUM)
ieLayer->_operation = InferenceEngine::EltwiseLayer::Sum; ieLayer->_operation = InferenceEngine::EltwiseLayer::Sum;
else if (op == PROD) else if (op == PROD)

40
modules/dnn/src/tensorflow/tf_importer.cpp
View File

@ -939,7 +939,7 @@ void TFImporter::populateNet(Net dstNet)
if (getDataLayout(name, data_layouts) == DATA_LAYOUT_UNKNOWN) if (getDataLayout(name, data_layouts) == DATA_LAYOUT_UNKNOWN)
data_layouts[name] = DATA_LAYOUT_NHWC; data_layouts[name] = DATA_LAYOUT_NHWC;
} }
else if (type == "BiasAdd" || type == "Add") else if (type == "BiasAdd" || type == "Add" || type == "Sub")
{ {
bool haveConst = false; bool haveConst = false;
for(int ii = 0; !haveConst && ii < layer.input_size(); ++ii) for(int ii = 0; !haveConst && ii < layer.input_size(); ++ii)
@ -953,6 +953,8 @@ void TFImporter::populateNet(Net dstNet)
{ {
Mat values = getTensorContent(getConstBlob(layer, value_id)); Mat values = getTensorContent(getConstBlob(layer, value_id));
CV_Assert(values.type() == CV_32FC1); CV_Assert(values.type() == CV_32FC1);
if (type == "Sub")
values *= -1.0f;
int id; int id;
if (values.total() == 1) // is a scalar. if (values.total() == 1) // is a scalar.
@ -973,6 +975,12 @@ void TFImporter::populateNet(Net dstNet)
else else
{ {
layerParams.set("operation", "sum"); layerParams.set("operation", "sum");
if (type == "Sub")
{
static float subCoeffs[] = {1.f, -1.f};
layerParams.set("coeff", DictValue::arrayReal<float*>(subCoeffs, 2));
}
int id = dstNet.addLayer(name, "Eltwise", layerParams); int id = dstNet.addLayer(name, "Eltwise", layerParams);
layer_id[name] = id; layer_id[name] = id;
@ -985,36 +993,6 @@ void TFImporter::populateNet(Net dstNet)
} }
} }
} }
else if (type == "Sub")
{
bool haveConst = false;
for(int ii = 0; !haveConst && ii < layer.input_size(); ++ii)
{
Pin input = parsePin(layer.input(ii));
haveConst = value_id.find(input.name) != value_id.end();
}
CV_Assert(haveConst);
Mat values = getTensorContent(getConstBlob(layer, value_id));
CV_Assert(values.type() == CV_32FC1);
values *= -1.0f;
int id;
if (values.total() == 1) // is a scalar.
{
layerParams.set("shift", values.at<float>(0));
id = dstNet.addLayer(name, "Power", layerParams);
}
else // is a vector
{
layerParams.blobs.resize(1, values);
id = dstNet.addLayer(name, "Shift", layerParams);
}
layer_id[name] = id;
// one input only
connect(layer_id, dstNet, parsePin(layer.input(0)), id, 0);
}
else if (type == "MatMul") else if (type == "MatMul")
{ {
CV_Assert(layer.input_size() == 2); CV_Assert(layer.input_size() == 2);

3
modules/dnn/test/test_tf_importer.cpp
View File

@ -139,9 +139,10 @@ TEST_P(Test_TensorFlow_layers, padding)
runTensorFlowNet("keras_pad_concat"); runTensorFlowNet("keras_pad_concat");
} }
TEST_P(Test_TensorFlow_layers, eltwise_add_mul) TEST_P(Test_TensorFlow_layers, eltwise)
{ {
runTensorFlowNet("eltwise_add_mul"); runTensorFlowNet("eltwise_add_mul");
runTensorFlowNet("eltwise_sub");
} }
TEST_P(Test_TensorFlow_layers, pad_and_concat) TEST_P(Test_TensorFlow_layers, pad_and_concat)