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Merge pull request #13389 from dkurt:dnn_tf_eltwise_sub
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commit
92e86292dd
@ -98,7 +98,8 @@ public:
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{
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return backendId == DNN_BACKEND_OPENCV ||
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backendId == DNN_BACKEND_HALIDE ||
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(backendId == DNN_BACKEND_INFERENCE_ENGINE && (op != SUM || coeffs.empty()));
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(backendId == DNN_BACKEND_INFERENCE_ENGINE &&
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(preferableTarget != DNN_TARGET_MYRIAD || coeffs.empty()));
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}
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bool getMemoryShapes(const std::vector<MatShape> &inputs,
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@ -427,6 +428,7 @@ public:
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lp.type = "Eltwise";
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lp.precision = InferenceEngine::Precision::FP32;
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std::shared_ptr<InferenceEngine::EltwiseLayer> ieLayer(new InferenceEngine::EltwiseLayer(lp));
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ieLayer->coeff = coeffs;
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if (op == SUM)
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ieLayer->_operation = InferenceEngine::EltwiseLayer::Sum;
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else if (op == PROD)
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@ -939,7 +939,7 @@ void TFImporter::populateNet(Net dstNet)
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if (getDataLayout(name, data_layouts) == DATA_LAYOUT_UNKNOWN)
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data_layouts[name] = DATA_LAYOUT_NHWC;
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}
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else if (type == "BiasAdd" || type == "Add")
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else if (type == "BiasAdd" || type == "Add" || type == "Sub")
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{
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bool haveConst = false;
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for(int ii = 0; !haveConst && ii < layer.input_size(); ++ii)
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@ -953,6 +953,8 @@ void TFImporter::populateNet(Net dstNet)
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{
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Mat values = getTensorContent(getConstBlob(layer, value_id));
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CV_Assert(values.type() == CV_32FC1);
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if (type == "Sub")
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values *= -1.0f;
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int id;
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if (values.total() == 1) // is a scalar.
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@ -973,6 +975,12 @@ void TFImporter::populateNet(Net dstNet)
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else
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{
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layerParams.set("operation", "sum");
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if (type == "Sub")
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{
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static float subCoeffs[] = {1.f, -1.f};
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layerParams.set("coeff", DictValue::arrayReal<float*>(subCoeffs, 2));
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}
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int id = dstNet.addLayer(name, "Eltwise", layerParams);
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layer_id[name] = id;
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@ -985,36 +993,6 @@ void TFImporter::populateNet(Net dstNet)
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}
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}
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}
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else if (type == "Sub")
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{
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bool haveConst = false;
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for(int ii = 0; !haveConst && ii < layer.input_size(); ++ii)
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{
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Pin input = parsePin(layer.input(ii));
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haveConst = value_id.find(input.name) != value_id.end();
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}
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CV_Assert(haveConst);
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Mat values = getTensorContent(getConstBlob(layer, value_id));
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CV_Assert(values.type() == CV_32FC1);
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values *= -1.0f;
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int id;
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if (values.total() == 1) // is a scalar.
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{
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layerParams.set("shift", values.at<float>(0));
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id = dstNet.addLayer(name, "Power", layerParams);
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}
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else // is a vector
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{
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layerParams.blobs.resize(1, values);
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id = dstNet.addLayer(name, "Shift", layerParams);
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}
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layer_id[name] = id;
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// one input only
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connect(layer_id, dstNet, parsePin(layer.input(0)), id, 0);
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}
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else if (type == "MatMul")
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{
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CV_Assert(layer.input_size() == 2);
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@ -139,9 +139,10 @@ TEST_P(Test_TensorFlow_layers, padding)
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runTensorFlowNet("keras_pad_concat");
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}
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TEST_P(Test_TensorFlow_layers, eltwise_add_mul)
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TEST_P(Test_TensorFlow_layers, eltwise)
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{
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runTensorFlowNet("eltwise_add_mul");
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runTensorFlowNet("eltwise_sub");
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}
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TEST_P(Test_TensorFlow_layers, pad_and_concat)
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