| 22 | namespace nvcaffeparser1 |
| 23 | { |
| 24 | ILayer* parseConcat(INetworkDefinition& network, const trtcaffe::LayerParameter& msg, CaffeWeightFactory& /*weightFactory*/, BlobNameToTensor& tensors) |
| 25 | { |
| 26 | const trtcaffe::ConcatParameter& p = msg.concat_param(); |
| 27 | bool hasAxis = p.has_axis(); // optional parameter |
| 28 | |
| 29 | if (hasAxis && p.axis() < 0) |
| 30 | { |
| 31 | std::cout << "Caffe parser: Concat negative axis is not supported." << std::endl; |
| 32 | return nullptr; |
| 33 | } |
| 34 | if (network.hasImplicitBatchDimension() && p.axis() == 0) |
| 35 | { |
| 36 | std::cout << "Caffe parser: Concat across batch axis with implicit batch dimensions is not supported." |
| 37 | << std::endl; |
| 38 | return nullptr; |
| 39 | } |
| 40 | |
| 41 | std::vector<ITensor*> ptrs; |
| 42 | for (unsigned int i = 0, n = msg.bottom_size(); i < n; i++) |
| 43 | { |
| 44 | ptrs.push_back(tensors[msg.bottom().Get(i)]); |
| 45 | } |
| 46 | |
| 47 | auto concat = network.addConcatenation(&ptrs[0], msg.bottom_size()); |
| 48 | |
| 49 | // If no axis is explicitly provided, do not call setAxis. |
| 50 | // Rely on the default axis setting inside TRT which takes into account NPCHW and higher dimensional input. |
| 51 | if (hasAxis) |
| 52 | { |
| 53 | concat->setAxis(p.axis() - static_cast<int>(network.hasImplicitBatchDimension())); |
| 54 | } |
| 55 | |
| 56 | return concat; |
| 57 | } |
| 58 | } //namespace nvcaffeparser1 |
nothing calls this directly
no test coverage detected