chore: import upstream snapshot with attribution

2026-07-13 13:33:03 +08:00
commit 5b57521aa1
8226 changed files with 3425766 additions and 0 deletions
@@ -0,0 +1,65 @@
+//
+//  TRTCommonExecution.cpp
+//  MNN
+//
+//  Created by MNN on 2019/02/28.
+//  Copyright © 2018, Alibaba Group Holding Limited
+//
+
+#include "TRTCommonExecution.hpp"
+namespace MNN {
+
+TRTCommonExecution::TRTCommonExecution(Backend *backend, const Op *op) : Execution(backend) {
+    mTrtBackend = (TRTBackend *)backend;
+    mOp         = op;
+}
+
+ErrorCode TRTCommonExecution::onResize(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
+    mInputs  = inputs;
+    mOutputs = outputs;
+    // if(mOp->name() != nullptr){
+    //     MNN_PRINT("layer info: Type:%s name:%s \n", EnumNameOpType(mOp->type()), mOp->name()->c_str());
+    // }
+    // MNN_PRINT(" ===========    layer info: Type:%s     =========== \n", EnumNameOpType(mOp->type()));
+    std::vector<ITensor *> nvTensors(inputs.size());
+    for (int i = 0; i < inputs.size(); ++i) {
+        nvTensors[i] = mTrtBackend->getTensorOps(inputs[i]);
+    }
+
+    // printf("inputs size : %d \n", inputs.size());
+    // printf("outputs size : %d \n", outputs.size());
+    // printf("nvTensors input size : %d \n", nvTensors.size());
+
+    // printf("input : \n");
+    // for(int n = 0; n < nvTensors.size(); n++){
+    //     auto dims = nvTensors[n]->getDimensions();
+    //     for(int i = 0; i < dims.nbDims; i++){
+    //         printf("%d ", dims.d[i]);
+    //     }
+    //     printf("\n");
+    //     for(int i = 0; i < dims.nbDims; i++){
+    //         printf("%d ", inputs[n]->shape()[i]);
+    //     }
+    //     printf("\n");
+    // }
+    
+    auto outputsTRT = this->onEncode(nvTensors);
+    // printf("output : \n");
+    // auto out_dims = outputsTRT[0]->getDimensions();
+    // for(int i = 0; i < out_dims.nbDims; i++){
+    //     printf("%d ", out_dims.d[i]);
+    // }
+    // printf("\n");
+    // for(int i = 0; i < outputs[0]->dimensions(); i++){
+    //     printf("%d ", outputs[0]->shape()[i]);
+    // }
+    // printf("\n");
+    mTrtBackend->setTensorOps(outputs, std::move(outputsTRT));
+    return NO_ERROR;
+}
+
+ErrorCode TRTCommonExecution::onExecute(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
+    return NO_ERROR;
+}
+
+}; // namespace MNN