| 26 | using baidu::paddle_serving::predictor::InferManager; |
| 27 | |
| 28 | int ClassifyOp::inference() { |
| 29 | const ReaderOutput* reader_out = |
| 30 | get_depend_argument<ReaderOutput>("image_reader_op"); |
| 31 | if (!reader_out) { |
| 32 | LOG(ERROR) << "Failed mutable depended argument, op:" |
| 33 | << "reader_op"; |
| 34 | return -1; |
| 35 | } |
| 36 | |
| 37 | const TensorVector* in = &reader_out->tensors; |
| 38 | |
| 39 | TensorVector* out = butil::get_object<TensorVector>(); |
| 40 | if (!out) { |
| 41 | LOG(ERROR) << "Failed get tls output object failed"; |
| 42 | return -1; |
| 43 | } |
| 44 | |
| 45 | if (in->size() != 1) { |
| 46 | LOG(ERROR) << "Samples should have been packed into a single tensor"; |
| 47 | return -1; |
| 48 | } |
| 49 | |
| 50 | int batch_size = in->at(0).shape[0]; |
| 51 | // call paddle fluid model for inferencing |
| 52 | if (InferManager::instance().infer( |
| 53 | IMAGE_CLASSIFICATION_MODEL_NAME, in, out, batch_size)) { |
| 54 | LOG(ERROR) << "Failed do infer in fluid model: " |
| 55 | << IMAGE_CLASSIFICATION_MODEL_NAME; |
| 56 | return -1; |
| 57 | } |
| 58 | |
| 59 | if (out->size() != in->size()) { |
| 60 | LOG(ERROR) << "Output size not eq input size: " << in->size() |
| 61 | << out->size(); |
| 62 | return -1; |
| 63 | } |
| 64 | |
| 65 | // copy output tensor into response |
| 66 | ClassifyResponse* res = mutable_data<ClassifyResponse>(); |
| 67 | const paddle::PaddleTensor& out_tensor = (*out)[0]; |
| 68 | |
| 69 | #if 0 |
| 70 | int out_shape_size = out_tensor.shape.size(); |
| 71 | LOG(ERROR) << "out_tensor.shpae"; |
| 72 | for (int i = 0; i < out_shape_size; ++i) { |
| 73 | LOG(ERROR) << out_tensor.shape[i] << ":"; |
| 74 | } |
| 75 | |
| 76 | if (out_shape_size != 2) { |
| 77 | return -1; |
| 78 | } |
| 79 | #endif |
| 80 | |
| 81 | int sample_size = out_tensor.shape[0]; |
| 82 | #if 0 |
| 83 | LOG(ERROR) << "Output sample size " << sample_size; |
| 84 | #endif |
| 85 | for (uint32_t si = 0; si < sample_size; si++) { |