使用ncnn 模型时，需要在 TNN 初始化参数 NetworkConfig 中指明 ModelType 为 MODEL_TYPE_NCNN。
具体代码参考：
ModelConfig model_config;
model_config.model_type = MODEL_TYPE_NCNN;
TNN net;
Status ret = net.Init(model_config);
auto instance = net.CreateInst(network_config, ret);
TNN Instance 在创建时需要声明默认InputShape，通常ncnn.param 的Input 层中会说明。如果其中未指明的话，需要在创建Instance 代码中指明。 具体参考:
InputShapesMap input_shape;
input_shape["input_name"] = {1, 3, 224, 224};
auto instance = net.CreateInst(network_config, ret, input_shape);
其他方面使用与正常调用流程相同，可具体参考其他文档。
Demo示例中可将examples/samples/TNNSDKSample.h中的宏TNN_SDK_USE_NCNN_MODEL设置为1来运行ncnn模型。
目前对NCNN OP 支持情况如下, Int8 模型适配还在进行中。
| Operators | NCNN | TNN |
|---|---|---|
| MemoryData | ✅ | ✅ |
| AbsVal | ✅ | ✅ |
| ArgMax | ✅ | ✅ |
| BatchNorm | ✅ | ✅ |
| Bias | TODO | |
| BinaryOp | ✅ | ✅ |
| BNLL | TODO | |
| Cast | TODO | |
| Clip | ✅ | ✅ |
| Concat | ✅ | ✅ |
| Convolution | ✅ | ✅ |
| ConvolutionDepthWise | ✅ | ✅ |
| Crop | ✅ | ✅ |
| Deconvolution | ✅ | ✅ |
| DeconvolutionDepthWise | ✅ | ✅ |
| Dequantize | TODO | |
| DetectionOutput | partial | ✅ |
| Dropout | ✅ | ✅ |
| Eltwise | ✅ | ✅ |
| ELU | ✅ | ✅ |
| Embed | TODO | |
| Exp | TODO | ✅ |
| ExpandDims | TODO | |
| Flatten | ✅ | ✅ |
| HardSigmoid | ✅ | ✅ |
| HardSwish | ✅ | ✅ |
| InnerProduct | ✅ | ✅ |
| InstanceNorm | ✅ | ✅ |
| Interp | ✅ | ✅ |
| Log | TODO | |
| LRN | ✅ | ✅ |
| MVN | TODO | |
| Noop | TODO | |
| Normalize | ✅ | ✅ |
| Packing | TODO | |
| Padding | ✅ | ✅ |
| Permute | ✅ | ✅ |
| Pooling | ✅ | ✅ |
| Power | TODO | ✅ |
| PReLU | ✅ | ✅ |
| PriorBox | ✅ | ✅ |
| Proposal | TODO | |
| PSROIPooling | TODO | |
| Quantize | TODO | |
| Reduction | ✅ | ✅ |
| ReLU | ✅ | ✅ |
| Reorg | ✅ | ✅ |
| Requantize | TODO | |
| Reshape | ✅ | ✅ |
| ROIAlign | TODO | |
| ROIPooling | TODO | ✅ |
| Scale | ✅ | ✅ |
| SELU | ✅ | ✅ |
| ShuffleChannel | ✅ | ✅ |
| Sigmoid | ✅ | ✅ |
| Slice | ✅ | ✅ |
| Softmax | ✅ | ✅ |
| Split | ✅ | ✅ |
| SPP | TODO | |
| Squeeze | TODO | |
| TanH | ✅ | ✅ |
| Threshold | TODO | |
| Tile | TODO | |
| UnaryOp | ✅ | ✅ |
| RNN | TODO | |
| LSTM | TODO |