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@ -275,13 +275,13 @@ public: |
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InferenceEngine::Blob::Ptr weights; |
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if (blobs.empty()) |
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{ |
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auto onesBlob = InferenceEngine::make_shared_blob<float>(InferenceEngine::Precision::FP32, |
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InferenceEngine::Layout::C, |
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{(size_t)numChannels}); |
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onesBlob->allocate(); |
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std::vector<float> ones(numChannels, 1); |
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onesBlob->set(ones); |
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weights = onesBlob; |
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weights = InferenceEngine::make_shared_blob<float>(InferenceEngine::Precision::FP32, |
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InferenceEngine::Layout::C, |
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{(size_t)numChannels}); |
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weights->allocate(); |
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Mat weightsMat = infEngineBlobToMat(weights).reshape(1, numChannels); |
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Mat(numChannels, 1, CV_32F, Scalar(1)).copyTo(weightsMat); |
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l.getParameters()["channel_shared"] = false; |
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} |
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else |
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@ -290,11 +290,7 @@ public: |
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weights = wrapToInfEngineBlob(blobs[0], {(size_t)numChannels}, InferenceEngine::Layout::C); |
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l.getParameters()["channel_shared"] = blobs[0].total() == 1; |
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} |
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#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2019R1) |
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l.getParameters()["weights"] = weights; |
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#else |
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l.addConstantData("weights", weights); |
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#endif |
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addConstantData("weights", weights, l); |
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l.getParameters()["across_spatial"] = acrossSpatial; |
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return Ptr<BackendNode>(new InfEngineBackendNode(l)); |
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} |
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