Lines Matching refs:outs
184 const std::vector<uint32_t>& outs = operation.outputs; in Create() local
206 for (size_t k = 0; k < outs.size(); k++) { in Create()
207 if (isScalarType(operands[outs[k]].type)) continue; in Create()
208 const int t = outs[k]; in Create()
564 const hardware::hidl_vec<uint32_t>& outs = operation.outputs; in VisitAbsNode() local
566 NN_DRIVER_RETURN_IF_ERROR(CheckTensorFloatType(operands[outs[0]].type)); in VisitAbsNode()
571 /*output_id=*/xnnpackTensors[outs[0]], /*flags=*/0); in VisitAbsNode()
584 const hardware::hidl_vec<uint32_t>& outs = operation.outputs; in VisitAddNode() local
588 NN_DRIVER_RETURN_IF_ERROR(CheckTensorFloatType(operands[outs[0]].type)); in VisitAddNode()
601 /*output_id=*/xnnpackTensors[outs[0]], /*flags=*/0); in VisitAddNode()
615 const hardware::hidl_vec<uint32_t>& outs = operation.outputs; in VisitAveragePool2DNode() local
617 NN_DRIVER_RETURN_IF_ERROR(CheckTensorFloatType(operands[outs[0]].type)); in VisitAveragePool2DNode()
675 /*output_id=*/xnnpackTensors[outs[0]], /*flags=*/0); in VisitAveragePool2DNode()
683 /*output_id=*/xnnpackTensors[outs[0]], flags); in VisitAveragePool2DNode()
698 const hardware::hidl_vec<uint32_t>& outs = operation.outputs; in VisitConv2DNode() local
704 NN_DRIVER_RETURN_IF_ERROR(CheckTensorFloatType(operands[outs[0]].type)); in VisitConv2DNode()
782 /*output_id=*/xnnpackTensors[outs[0]], flags); in VisitConv2DNode()
797 const hardware::hidl_vec<uint32_t>& outs = operation.outputs; in VisitDepthwiseConv2DNode() local
803 NN_DRIVER_RETURN_IF_ERROR(CheckTensorFloatType(operands[outs[0]].type)); in VisitDepthwiseConv2DNode()
884 /*output_id=*/xnnpackTensors[outs[0]], flags); in VisitDepthwiseConv2DNode()
897 const hardware::hidl_vec<uint32_t>& outs = operation.outputs; in VisitDivNode() local
901 NN_DRIVER_RETURN_IF_ERROR(CheckTensorFloatType(operands[outs[0]].type)); in VisitDivNode()
914 /*output_id=*/xnnpackTensors[outs[0]], /*flags=*/0); in VisitDivNode()
928 const hardware::hidl_vec<uint32_t>& outs = operation.outputs; in VisitFullyConnectedNode() local
935 NN_DRIVER_RETURN_IF_ERROR(CheckTensorFloatType(operands[outs[0]].type)); in VisitFullyConnectedNode()
949 /*output_id=*/xnnpackTensors[outs[0]], in VisitFullyConnectedNode()
964 const hardware::hidl_vec<uint32_t>& outs = operation.outputs; in VisitFloorNode() local
966 NN_DRIVER_RETURN_IF_ERROR(CheckTensorFloatType(operands[outs[0]].type)); in VisitFloorNode()
972 /*output_id=*/xnnpackTensors[outs[0]], /*flags=*/0); in VisitFloorNode()
986 const hardware::hidl_vec<uint32_t>& outs = operation.outputs; in VisitHardSwishNode() local
988 NN_DRIVER_RETURN_IF_ERROR(CheckTensorFloatType(operands[outs[0]].type)); in VisitHardSwishNode()
993 /*output_id=*/xnnpackTensors[outs[0]], /*flags=*/0); in VisitHardSwishNode()
1007 const hardware::hidl_vec<uint32_t>& outs = operation.outputs; in VisitLogisticNode() local
1009 NN_DRIVER_RETURN_IF_ERROR(CheckTensorFloatType(operands[outs[0]].type)); in VisitLogisticNode()
1014 /*output_id=*/xnnpackTensors[outs[0]], /*flags=*/0); in VisitLogisticNode()
1028 const hardware::hidl_vec<uint32_t>& outs = operation.outputs; in VisitMaxPool2DNode() local
1030 NN_DRIVER_RETURN_IF_ERROR(CheckTensorFloatType(operands[outs[0]].type)); in VisitMaxPool2DNode()
1088 /*output_id=*/xnnpackTensors[outs[0]], /*flags=*/0); in VisitMaxPool2DNode()
1097 /*output_id=*/xnnpackTensors[outs[0]], flags); in VisitMaxPool2DNode()
1112 const hardware::hidl_vec<uint32_t>& outs = operation.outputs; in VisitMaximumNode() local
1116 NN_DRIVER_RETURN_IF_ERROR(CheckTensorFloatType(operands[outs[0]].type)); in VisitMaximumNode()
1129 /*output_id=*/xnnpackTensors[outs[0]], /*flags=*/0); in VisitMaximumNode()
1143 const hardware::hidl_vec<uint32_t>& outs = operation.outputs; in VisitMeanNode() local
1149 NN_DRIVER_RETURN_IF_ERROR(CheckTensorFloatType(operands[outs[0]].type)); in VisitMeanNode()
1150 NN_DRIVER_RETURN_IF_ERROR(CheckTensorShape(operands[outs[0]].dimensions, 4)); in VisitMeanNode()
1173 /*output_id=*/xnnpackTensors[outs[0]], /*flags=*/0); in VisitMeanNode()
1187 const hardware::hidl_vec<uint32_t>& outs = operation.outputs; in VisitMinimumNode() local
1191 NN_DRIVER_RETURN_IF_ERROR(CheckTensorFloatType(operands[outs[0]].type)); in VisitMinimumNode()
1204 /*output_id=*/xnnpackTensors[outs[0]], /*flags=*/0); in VisitMinimumNode()
1217 const hardware::hidl_vec<uint32_t>& outs = operation.outputs; in VisitMulNode() local
1221 NN_DRIVER_RETURN_IF_ERROR(CheckTensorFloatType(operands[outs[0]].type)); in VisitMulNode()
1234 /*output_id=*/xnnpackTensors[outs[0]], /*flags=*/0); in VisitMulNode()
1247 const hardware::hidl_vec<uint32_t>& outs = operation.outputs; in VisitNegNode() local
1249 NN_DRIVER_RETURN_IF_ERROR(CheckTensorFloatType(operands[outs[0]].type)); in VisitNegNode()
1255 /*output_id=*/xnnpackTensors[outs[0]], /*flags=*/0); in VisitNegNode()
1269 const hardware::hidl_vec<uint32_t>& outs = operation.outputs; in VisitPreluNode() local
1275 NN_DRIVER_RETURN_IF_ERROR(CheckTensorFloatType(operands[outs[0]].type)); in VisitPreluNode()
1277 CheckTensorShape(operands[outs[0]].dimensions, 1, XNN_MAX_TENSOR_DIMS)); in VisitPreluNode()
1283 /*output_id=*/xnnpackTensors[outs[0]], /*flags=*/0); in VisitPreluNode()
1296 const hardware::hidl_vec<uint32_t>& outs = operation.outputs; in VisitPadNode() local
1301 NN_DRIVER_RETURN_IF_ERROR(CheckTensorFloatType(operands[outs[0]].type)); in VisitPadNode()
1303 CheckTensorShape(operands[outs[0]].dimensions, 1, XNN_MAX_TENSOR_DIMS)); in VisitPadNode()
1319 /*output_id=*/xnnpackTensors[outs[0]], /*flags=*/0); in VisitPadNode()
1345 const hardware::hidl_vec<uint32_t>& outs = operation.outputs; in VisitReshapeNode() local
1350 NN_DRIVER_RETURN_IF_ERROR(CheckTensorFloatType(operands[outs[0]].type)); in VisitReshapeNode()
1352 CheckTensorShape(operands[outs[0]].dimensions, 0, XNN_MAX_TENSOR_DIMS)); in VisitReshapeNode()
1356 for (uint32_t i = 0; i < operands[outs[0]].dimensions.size(); i++) { in VisitReshapeNode()
1357 new_shape[i] = static_cast<size_t>(operands[outs[0]].dimensions[i]); in VisitReshapeNode()
1360 subgraph, static_cast<size_t>(operands[outs[0]].dimensions.size()), in VisitReshapeNode()
1363 /*output_id=*/xnnpackTensors[outs[0]], /*flags=*/0); in VisitReshapeNode()
1377 const hardware::hidl_vec<uint32_t>& outs = operation.outputs; in VisitResizeBilinearNode() local
1380 NN_DRIVER_RETURN_IF_ERROR(CheckTensorFloatType(operands[outs[0]].type)); in VisitResizeBilinearNode()
1381 NN_DRIVER_RETURN_IF_ERROR(CheckTensorShape(operands[outs[0]].dimensions, 4)); in VisitResizeBilinearNode()
1433 /*output_id=*/xnnpackTensors[outs[0]], flags); in VisitResizeBilinearNode()
1448 const hardware::hidl_vec<uint32_t>& outs = operation.outputs; in VisitReluNode() local
1450 NN_DRIVER_RETURN_IF_ERROR(CheckTensorFloatType(operands[outs[0]].type)); in VisitReluNode()
1456 /*output_id=*/xnnpackTensors[outs[0]], /*flags=*/0); in VisitReluNode()
1470 const hardware::hidl_vec<uint32_t>& outs = operation.outputs; in VisitSqrtNode() local
1472 NN_DRIVER_RETURN_IF_ERROR(CheckTensorFloatType(operands[outs[0]].type)); in VisitSqrtNode()
1478 /*output_id=*/xnnpackTensors[outs[0]], /*flags=*/0); in VisitSqrtNode()
1491 const hardware::hidl_vec<uint32_t>& outs = operation.outputs; in VisitSubNode() local
1495 NN_DRIVER_RETURN_IF_ERROR(CheckTensorFloatType(operands[outs[0]].type)); in VisitSubNode()
1508 /*output_id=*/xnnpackTensors[outs[0]], /*flags=*/0); in VisitSubNode()
1522 const hardware::hidl_vec<uint32_t>& outs = operation.outputs; in VisitSoftmaxNode() local
1525 NN_DRIVER_RETURN_IF_ERROR(CheckTensorFloatType(operands[outs[0]].type)); in VisitSoftmaxNode()
1543 /*output_id=*/xnnpackTensors[outs[0]], /*flags=*/0); in VisitSoftmaxNode()