533 lines
72 KiB
Markdown
533 lines
72 KiB
Markdown
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# RKNNToolkit2 OPs Support
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## Explanation of terms:
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**Remarks**:
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Operators' specifications must meet the remarks' requirements.
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**Broadcast rule**:
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- per-layer：
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shape(A) = (2, 3, 4, 5), shape(B) = (,), i.e. B is a scalar ==> shape(result) = (2, 3, 4, 5)
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- per-channel:
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shape(A) = (2, 3, 4, 5), shape(B) = (3,), ==> shape(result) = (2, 3, 4, 5)
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shape(A) = (2, 3, 4, 5), shape(B) = (1,3,1,1), ==> shape(result) = (2, 3, 4, 5)
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- per-element:
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shape(A) = (2, 3, 4, 5), shape(B) = (2,3,4,5) ==> shape(result) = (2, 3, 4, 5)
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- other:
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shape(A) = (2, 3, 4, 5), shape(B) = (5,) ==> shape(result) = (2, 3, 4, 5)
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**Input Size Restrictions Description**
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Assuming that input size is [N,H,W,C] (layout is NHWC)
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- Case 1: the first layer is **Convolution**, whose kernel size is [kernel_height, kernel_width]
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**W * kernel_height < 7168**
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**kernel_height * kernel_width < 128**
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- Case 2: first layer is not Convolution, and C == 1 or C == 3 or C == 4
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**W < 7168**
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- others:
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**No Restrictions**
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## ONNX OPs supported by RKNN Toolkit2
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According to [ONNX official instructions](https://github.com/microsoft/onnxruntime/blob/master/docs/Versioning.md 'ONNX Version Description'), the corresponding ONNX opset version is 12.
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The list of ONNX OPs supported by RKNN Toolkit2 is as follows:
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<br>(For more restrictions, please refer to [RKNN_Compiler_Support_Operator_List.pdf](https://github.com/rockchip-linux/rknpu2/tree/master/doc))
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| **Operators** | **Remarks** |
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| --------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| Abs | Not Supported |
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| Acos | Not Supported |
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| Acosh | Not Supported |
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| Add | |
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| And | Not Supported |
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| ArgMax | |
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| ArgMin | |
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| Asin | Not Supported |
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| Asinh | Not Supported |
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| Atan | Not Supported |
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| Atanh | Not Supported |
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| AveragePool | **NPU Limit:**<br />channel: [1, 8192]<br />stride height/width: [1, 8]<br />pad left/right/top/bottom: [0, 7]<br />auto_pad: NOTSET<br />count_include_pad: 1 <br />ceil_mode: 0 |
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| BatchNormalization | **NPU Limit:**<br />channel: [1, 8192]<br />height: [1, 8192]<br />width: [1, 8176] |
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| BitShift | Not Supported |
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| Cast | only support bool/int8/float |
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| Ceil | Not Supported |
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| Celu | Not Supported |
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| Clip | |
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| Compress | Not Supported |
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| Concat | |
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| ConcatFromSequence | Not Supported |
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| Constant | |
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| ConstantOfShape | |
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| Conv | **NPU Limit:**<br />kernel height/width: [1, 31]<br />stride height/width: [1, 7]<br />pad left/right/top/bottom: [0, 15] |
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| ConvInteger | Not Supported |
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| ConvTranspose | **NPU Limit:**<br />kernel height/width: [1, 31]<br />stride height/width: 2, 4, 8<br />pad left/right/top/bottom: [0, 15] |
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| Cos | Not Supported |
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| Cosh | Not Supported |
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| CumSum | Not Supported |
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| DepthToSpace | |
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| DequantizeLinear | |
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| Det | |
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| Div | **NPU Limit:**<br />support broadcast rule: per-element/other |
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| Dropout | |
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| Einsum | Not Supported |
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| Elu | channel: [1, 8192]<br />height: [1, 8192]<br />width: [1, 8176]<br /> |
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| Equal | |
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| Erf | Not Supported |
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| Exp | |
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| Expand | Not Supported |
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| EyeLike | only support constant input |
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| Flatten | |
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| Floor | Not Supported |
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| GRU | batchsize: 1 |
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| Gather | |
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| GatherElements | Not Supported |
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| GatherND | Not Supported |
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| Gemm | |
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| GlobalAveragePool | channel: [1, 8192]<br />kernel height/width: [1, 343]<br /> |
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| GlobalLpPool | Not Supported |
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| GlobalMaxPool | channel: [1, 8192]<br />kernel height/width: [1, 343]<br /> |
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| Greater | **NPU Limit:**<br />support broadcast rule: per-element/other |
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| GreaterOrEqual | |
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| HardSigmoid | |
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| HardSwish | |
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| Hardmax | Not Supported |
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| Identity | |
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| If | only support constant input |
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| InstanceNormalization | |
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| IsInf | Not Supported |
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| IsNaN | Not Supported |
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| LRN | |
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| LSTM | batchsize: 1<br />input_forget: 0 |
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| LeakyRelu | |
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| Less | **NPU Limit:**<br />support broadcast rule: per-element/other |
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| LessOrEqual | |
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| Log | Not Supported |
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| LogSoftmax | batchsize: 1 |
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| Loop | Not Supported |
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| LpNormalization | |
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| LpPool | Not Supported |
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| MatMul | |
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| MatMulInteger | Not Supported |
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| Max | **NPU Limit:**<br />channel: [1, 8192]<br />height: [1, 8192]<br />width: [1, 8176] |
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| MaxPool | **NPU Limit:**<br />channel: [1, 8192]<br />stride height/width: [1, 8]<br />pad left/right/top/bottom: [0, 7]<br />auto_pad: NOTSET<br />ceil_mode: 0<br />dilations: 1<br />storage_order: 0 |
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| MaxRoiPool | |
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| MaxUnpool | |
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| Mean | Not Supported |
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| Min | **NPU Limit:**<br />channel: [1, 8192]<br />height: [1, 8192]<br />width: [1, 8176] |
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| Mod | Not Supported |
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| Mul | **NPU Limit:**<br />support broadcast rule: per-layer/channel/element |
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| Multinomial | Not Supported |
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| Neg | Not Supported |
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| NonMaxSuppression | Not Supported |
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| NonZero | Not Supported |
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| Not | Not Supported |
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| OneHot | Not Supported |
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| Or | Not Supported |
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| PRelu | slope support broadcast rule: per-layer/channel |
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| Pad | **NPU Limit:**<br />width: [1, 8176]<br />mode: constant<br />pads n_begin/n_end/c_begin/c_end: 1 |
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| Pow | |
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| QLinearConv | Not Supported |
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| QLinearMatMul | Not Supported |
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| QuantizeLinear | |
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| RNN | Not Supported |
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| RandomNormal | Not Supported |
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| RandomNormalLike | Not Supported |
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| RandomUniform | Not Supported |
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| RandomUniformLike | Not Supported |
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| Range | Not Supported |
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| Reciprocal | Not Supported |
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| ReduceL1 | Not Supported |
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| ReduceL2 | Not Supported |
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| ReduceLogSum | Not Supported |
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| ReduceLogSumExp | Not Supported |
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| ReduceMax | |
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| ReduceMean | **NPU Limit:**<br />channel: [1, 8192]<br />height: [1, 8192]<br />width: [1, 8192] |
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| ReduceMin | |
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| ReduceProd | Not Supported |
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| ReduceSum | **NPU Limit:**<br />channel: [1, 8192]<br />height: [1, 8192]<br />width: [1, 8192] |
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| ReduceSumSquare | |
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| Relu | |
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| Reshape | **NPU Limit:**<br />channel: [1, 8192]<br />height: [1, 8192]<br />width: [1, 8176] |
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| Resize | **NPU Limit:**<br />channel: [1, 8192]<br />height: [1, 8192]<br />width: [1, 8176]<br />scales: [1, 8] |
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| ReverseSequence | |
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| RoiAlign | pool type: average<br />batchsize: 1 |
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| Round | Not Supported |
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| Scan | Not Supported |
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| ScatterElements | Not Supported |
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| ScatterND | Not Supported |
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| Selu | Not Supported |
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| SequenceAt | Not Supported |
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| SequenceConstruct | Not Supported |
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| SequenceEmpty | Not Supported |
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| SequenceErase | Not Supported |
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| SequenceInsert | Not Supported |
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| SequenceLength | Not Supported |
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| Shape | |
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| Shrink | Not Supported |
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| Sigmoid | |
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| Sign | Not Supported |
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| Sin | Not Supported |
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| Sinh | Not Supported |
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| Size | |
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| Slice | batchsize: 1<br />**NPU Limit:**<br />steps: 1 |
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| Softmax | batchsize: 1<br />**NPU Limit:**<br />channel: [1, 8192]<br />axis: 1 |
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| Softplus | |
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| Softsign | Not Supported |
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| SpaceToDepth | |
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| Split | |
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| SplitToSequence | Not Supported |
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| Sqrt | |
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| Squeeze | |
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| StringNormalizer | Not Supported |
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| Sub | **NPU Limit:**<br />support broadcast rule: per-layer/channel/element |
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| Sum | Not Supported |
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| Tan | Not Supported |
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| Tanh | |
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| TfIdfVectorizer | Not Supported |
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| ThresholdedRelu | Not Supported |
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| Tile | batchsize: 1<br />not support broadcast |
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| TopK | Not Supported |
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| Transpose | **NPU Limit:**<br />channel: [1, 8192]<br />height: [1, 8192]<br />width: [1, 8176] |
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| Trilu | Not Supported |
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| Unique | Not Supported |
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| Unsqueeze | |
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| Where | |
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| Xor | Not Supported | | |
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## Caffe OPs supported by RKNN Toolkit2
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Caffe protocols RKNN Toolkit2 uses only based on the officially modified protocol of berkeley.
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The protocol based on the official revision of berkeley comes from [berkeley caffe](https://github.com/BVLC/caffe/tree/master/src/caffe/proto 'Berkeley Caffe'), commit hash is 21d0608. On this basis RKNN Toolkit2 have added some OPs.
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Based on this protocol, the list of Caffe OPs supported by RKNN Toolkit2 is as follows:
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| **Operators** | **Remarks** |
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| ---------------------- | ------------------------------------------------------------------------------------------------------------- |
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| BatchNorm | same as onnx BatchNormalization |
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| bn (BatchNorm + Scale) | same as onnx BatchNormalization according to https://github.com/TimoSaemann/caffe-segnet-cudnn5 |
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| BNLL | |
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| Concat | same as onnx Concat |
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| Convolution | same as onnx Conv |
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| ConvolutionDepthwise | kernel height/width: [1, 8]<br />others same as onnx Conv |
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| Crop | |
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| Deconvolution | same as ConvTranspose |
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| Dropout | |
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| Eltwise | support broadcast rule: per-layer/channel/element |
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| Flatten | |
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| HardSigmoid | |
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| InnerProduct | same as onnx Gemm |
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| LRN | same as onnx LRN |
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| Lstm | same as onnx LSTM according to https://github.com/xmfbit/warpctc-caffe |
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| Normalize | |
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| Permute | same as onnx Transpose |
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| Power | |
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| Pooling | same as onnx pooling |
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| PRelu | same as onnx PRelu |
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| Proposal | batch: 1 |
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| Reduction | output dims <= 4 |
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| Relu | same as onnx Relu |
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| Relu6 | same as onnx Clip |
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| Reorg | |
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| Reshape | same as onnx Reshape |
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| Resize | bilinear; nearest |
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| Reverse | |
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| ROIPooling | same as MaxRoiPool according to https://github.com/twmht/caffe-pva-faster-rcnn |
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| Scale | same as onnx Mul |
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| Sigmoid | same as onnx Sigmoid |
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| Slice | same as onnx Split |
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| Softmax | same as onnx Softmax |
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| Split | same as onnx Slice |
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| TanH | same as onnx TanH |
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| Tile | same as onnx Tile |
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| Transpose | same as onnx Transpose |
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| Upsample | according to https://github.com/SeanQ88/caffe_upsample and https://github.com/TimoSaemann/caffe-segnet-cudnn5 |
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## Pytorch OPs supported by RKNN Toolkit2
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The Pytorch version supported by RKNN Toolkit2 is >1.6.0, models generated by other versions may not support.
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The list of Pytorch OPs supported by RKNN Toolkit2 is as follows:
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| **Operators** | **Remarks** |
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| ----------------------------- | ---------------------------------------------------------------------------------- |
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| aten::_convolution | same as onnx Conv |
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| aten::abs | Not supported |
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| aten::abs_ | Not supported |
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| aten::adaptive_avg_pool1d | Not supported |
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| aten::adaptive_avg_pool2d | same as onnx AveragePool |
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| aten::adaptive_max_pool1d | Not supported |
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| aten::adaptive_max_pool2d | same as onnx MaxPool |
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| aten::add | same as onnx Add |
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| aten::add_ | |
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| aten::addmm | same as onnx Gemm |
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| aten::affine_grid_generator | Not supported |
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| aten::alpha_dropout | |
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| aten::alpha_dropout_ | Not supported |
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| aten::arange | Not supported |
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| aten::avg_pool1d | Not supported |
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| aten::avg_pool2d | same as onnx AveragePool |
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| aten::avg_pool3d | Not supported |
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| aten::batch_norm | same as onnx BatchNormalization |
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| aten::bmm | same as onnx MatMul |
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| aten::cat | same as onnx Concat |
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| aten::celu | Not supported |
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| aten::celu_ | Not supported |
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| aten::chunk | |
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| aten::clamp | |
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| aten::clamp_ | |
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| aten::clamp_max | Not supported |
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| aten::clamp_max_ | Not supported |
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| aten::clamp_min | Not supported |
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| aten::clamp_min_ | Not supported |
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| aten::clone | |
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| aten::constant_pad_nd | same as onnx Pad |
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| aten::contiguous | |
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| aten::copy | |
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| aten::cos | Not supported |
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|
| aten::cos_ | Not supported |
|
|||
|
|
| aten::cumsum | Not supported |
|
|||
|
|
| aten::detach | |
|
|||
|
|
| aten::detach_ | Not supported |
|
|||
|
|
| aten::div | same as onnx Div |
|
|||
|
|
| aten::div_ | |
|
|||
|
|
| aten::dropout | |
|
|||
|
|
| aten::dropout_ | |
|
|||
|
|
| aten::einsum | Not supported |
|
|||
|
|
| aten::elu | same as onnx Elu |
|
|||
|
|
| aten::elu_ | |
|
|||
|
|
| aten::embedding | same as onnx Gather |
|
|||
|
|
| aten::empty | |
|
|||
|
|
| aten::eq | Not supported |
|
|||
|
|
| aten::eq_ | Not supported |
|
|||
|
|
| aten::erf | Not supported |
|
|||
|
|
| aten::erf_ | Not supported |
|
|||
|
|
| aten::erfc | Not supported |
|
|||
|
|
| aten::erfc_ | Not supported |
|
|||
|
|
| aten::exp | |
|
|||
|
|
| aten::exp_ | |
|
|||
|
|
| aten::expand | Not supported |
|
|||
|
|
| aten::expand_as | Not supported |
|
|||
|
|
| aten::expm1 | Not supported |
|
|||
|
|
| aten::expm1_ | Not supported |
|
|||
|
|
| aten::feature_dropout | |
|
|||
|
|
| aten::feature_dropout_ | Not supported |
|
|||
|
|
| aten::flatten | |
|
|||
|
|
| aten::floor | Not supported |
|
|||
|
|
| aten::floor_ | Not supported |
|
|||
|
|
| aten::floor_divide | Not supported |
|
|||
|
|
| aten::floor_divide_ | Not supported |
|
|||
|
|
| aten::gather | Not supported |
|
|||
|
|
| aten::ge | Not supported |
|
|||
|
|
| aten::ge_ | Not supported |
|
|||
|
|
| aten::gelu | |
|
|||
|
|
| aten::gelu_ | Not supported |
|
|||
|
|
| aten::grid_sampler | Not supported |
|
|||
|
|
| aten::gru | |
|
|||
|
|
| aten::gt | |
|
|||
|
|
| aten::gt_ | Not supported |
|
|||
|
|
| aten::hardshrink | Not supported |
|
|||
|
|
| aten::hardshrink_ | Not supported |
|
|||
|
|
| aten::hardswish | same as onnx HardSwish |
|
|||
|
|
| aten::hardswish_ | |
|
|||
|
|
| aten::hardtanh | |
|
|||
|
|
| aten::hardtanh_ | |
|
|||
|
|
| aten::index | Not supported |
|
|||
|
|
| aten::index_put | Not supported |
|
|||
|
|
| aten::index_put_ | Not supported |
|
|||
|
|
| aten::instance_norm | same as onnx InstanceNormalization |
|
|||
|
|
| aten::Int | |
|
|||
|
|
| aten::layer_norm | **NPU Limit**<br />channel: [1, 8192]<br />height: [1, 8192]<br />width: [1, 8192] |
|
|||
|
|
| aten::le | Not supported |
|
|||
|
|
| aten::le_ | Not supported |
|
|||
|
|
| aten::leaky_relu | same as onnx LeakyRelu |
|
|||
|
|
| aten::leaky_relu_ | |
|
|||
|
|
| aten::lerp | Not supported |
|
|||
|
|
| aten::lerp_ | Not supported |
|
|||
|
|
| aten::log | Not supported |
|
|||
|
|
| aten::log_ | Not supported |
|
|||
|
|
| aten::log10 | Not supported |
|
|||
|
|
| aten::log10_ | Not supported |
|
|||
|
|
| aten::log1p | Not supported |
|
|||
|
|
| aten::log1p_ | Not supported |
|
|||
|
|
| aten::log2 | Not supported |
|
|||
|
|
| aten::log2_ | Not supported |
|
|||
|
|
| aten::log_sigmoid | Not supported |
|
|||
|
|
| aten::log_softmax | Not supported |
|
|||
|
|
| aten::linear | same as onnx Gemm |
|
|||
|
|
| aten::lstm | same as onnx LSTM |
|
|||
|
|
| aten::lt | |
|
|||
|
|
| aten::lt_ | Not supported |
|
|||
|
|
| aten::matmul | same as onnx MatMul |
|
|||
|
|
| aten::max | |
|
|||
|
|
| aten::max_ | Not supported |
|
|||
|
|
| aten::max_pool1d | same as onnx MaxPool |
|
|||
|
|
| aten::max_pool1d_with_indices | |
|
|||
|
|
| aten::max_pool2d | same as onnx MaxPool |
|
|||
|
|
| aten::max_pool2d_with_indices | |
|
|||
|
|
| aten::mean | same as onnx ReduceMean |
|
|||
|
|
| aten::meshgrid | Not supported |
|
|||
|
|
| aten::min | |
|
|||
|
|
| aten::min_ | Not supported |
|
|||
|
|
| aten::mm | same as onnx MatMul |
|
|||
|
|
| aten::mul | same as onnx Mul |
|
|||
|
|
| aten::mul_ | |
|
|||
|
|
| aten::narrow | same as onnx Slice |
|
|||
|
|
| aten::ne | Not supported |
|
|||
|
|
| aten::ne_ | Not supported |
|
|||
|
|
| aten::neg | Not supported |
|
|||
|
|
| aten::neg_ | Not supported |
|
|||
|
|
| aten::new_full | Not supported |
|
|||
|
|
| aten::new_zeros | Not supported |
|
|||
|
|
| aten::nonzero | Not supported |
|
|||
|
|
| aten::norm | Not supported |
|
|||
|
|
| aten::ones | |
|
|||
|
|
| aten::ones_like | |
|
|||
|
|
| aten::pad | Not supported |
|
|||
|
|
| aten::permute | same as onnx Transpose |
|
|||
|
|
| aten::pow | |
|
|||
|
|
| aten::pow_ | Not supported |
|
|||
|
|
| aten::prelu | same as onnx PRelu |
|
|||
|
|
| aten::prelu_ | Not supported |
|
|||
|
|
| aten::reciprocal | |
|
|||
|
|
| aten::reciprocal_ | Not supported |
|
|||
|
|
| aten::reflection_pad1d | |
|
|||
|
|
| aten::reflection_pad2d | |
|
|||
|
|
| aten::relu | same as onnx Relu |
|
|||
|
|
| aten::relu_ | |
|
|||
|
|
| aten::repeat | |
|
|||
|
|
| aten::reshape | |
|
|||
|
|
| aten::reshape_ | Not supported |
|
|||
|
|
| torchvision::roi_align | Not supported |
|
|||
|
|
| aten::rsqrt | Not supported |
|
|||
|
|
| aten::rsqrt_ | Not supported |
|
|||
|
|
| aten::ScalarImplicit | |
|
|||
|
|
| aten::select | |
|
|||
|
|
| aten::selu | Not supported |
|
|||
|
|
| aten::selu_ | Not supported |
|
|||
|
|
| aten::sigmoid | same as onnx Sigmoid |
|
|||
|
|
| aten::sigmoid_ | |
|
|||
|
|
| aten::silu | |
|
|||
|
|
| aten::silu_ | |
|
|||
|
|
| aten::sin | Not supported |
|
|||
|
|
| aten::sin_ | Not supported |
|
|||
|
|
| aten::size | |
|
|||
|
|
| aten::slice | same as onnx Slice |
|
|||
|
|
| aten::softmax | same as onnx Softmax |
|
|||
|
|
| aten::softplus | |
|
|||
|
|
| aten::softshrink | Not supported |
|
|||
|
|
| aten::sort | Not supported |
|
|||
|
|
| aten::split | same as onnx Split |
|
|||
|
|
| aten::split_with_sizes | |
|
|||
|
|
| aten::sqrt | Not supported |
|
|||
|
|
| aten::sqrt_ | Not supported |
|
|||
|
|
| aten::squeeze | |
|
|||
|
|
| aten::squeeze_ | Not supported |
|
|||
|
|
| aten::stack | |
|
|||
|
|
| aten::sub | same as onnx Sub |
|
|||
|
|
| aten::sub_ | |
|
|||
|
|
| aten::sum | same as onnx ReduceSum |
|
|||
|
|
| aten::t | |
|
|||
|
|
| aten::t_ | Not supported |
|
|||
|
|
| aten::tanh | |
|
|||
|
|
| aten::tanh_ | |
|
|||
|
|
| aten::threshold | |
|
|||
|
|
| aten::threshold_ | |
|
|||
|
|
| aten::to | |
|
|||
|
|
| aten::topk | Not supported |
|
|||
|
|
| aten::transpose | |
|
|||
|
|
| aten::transpose_ | |
|
|||
|
|
| aten::true_divide | same as onnx Div |
|
|||
|
|
| aten::true_divide_ | Not supported |
|
|||
|
|
| aten::type_as | |
|
|||
|
|
| aten::unfold | Not supported |
|
|||
|
|
| aten::unsqueeze | |
|
|||
|
|
| aten::upsample_bilinear2d | |
|
|||
|
|
| aten::upsample_nearest2d | |
|
|||
|
|
| aten::view | |
|
|||
|
|
| aten::view_ | Not supported |
|
|||
|
|
| aten::view_as | Not supported |
|
|||
|
|
| aten::view_as_ | Not supported |
|
|||
|
|
| aten::zero_ | Not supported |
|
|||
|
|
| aten::zeros | |
|
|||
|
|
| aten::zeros_like | |
|
|||
|
|
|
|||
|
|
## TensorFlow OPs supported by RKNN Toolkit2
|
|||
|
|
|
|||
|
|
The pb files (contain OPs belows) generated by TensorFlow version 1.12 - 1.15 for 1.x and 2.3 - 2.5 for 2.x are supported by RKNN Toolkit2. For more information on TensorFlow version compatibility, please refer to [tensorflow official instructions on OP version](https://www.tensorflow.org/guide/versions 'Tensorflow official instructions on OP version') .
|
|||
|
|
The list of TensorFlow OPs supported by RKNN Toolkit2 is as follows:
|
|||
|
|
|
|||
|
|
| **Operators** | **Remarks** |
|
|||
|
|
| --------------------- | --------------------------------------------------------------- |
|
|||
|
|
| Add | same as onnx Add |
|
|||
|
|
| AvgPool | same as onnx AveragePool |
|
|||
|
|
| Concat | same as onnx Concat |
|
|||
|
|
| Conv2D | same as onnx Conv |
|
|||
|
|
| DepthToSpace | |
|
|||
|
|
| DepthwiseConv2d | kernel height/width: [1, 8]<br />others same as onnx Conv |
|
|||
|
|
| Div | same as onnx Div |
|
|||
|
|
| Dropout | |
|
|||
|
|
| Flatten | |
|
|||
|
|
| LeakyRelu | same as onnx LeakyRelu |
|
|||
|
|
| Less | same as onnx Less |
|
|||
|
|
| LRN | |
|
|||
|
|
| MatMul | |
|
|||
|
|
| MaxPool | same as onnx MaxPool |
|
|||
|
|
| Mean | output dims <= 4 |
|
|||
|
|
| Pad | same as onnx Pad |
|
|||
|
|
| Relu | same as onnx Relu |
|
|||
|
|
| Reshape | |
|
|||
|
|
| ResizeBilinear | |
|
|||
|
|
| ResizeNearestNeighbor | |
|
|||
|
|
| Sigmoid | |
|
|||
|
|
| Slice | |
|
|||
|
|
| Softmax | |
|
|||
|
|
| Softplus | channel: [1, 8192]<br />height: [1, 8192]<br />width: [1, 8176] |
|
|||
|
|
| SpaceToDepth | |
|
|||
|
|
| Split | |
|
|||
|
|
| Squeeze | |
|
|||
|
|
| StridedSlice | |
|
|||
|
|
| Tanh | same as onnx TanH |
|
|||
|
|
| Transpose | |
|
|||
|
|
|
|||
|
|
## Darknet OPs supported by RKNN Toolkit2
|
|||
|
|
The list of Darknet OPs supported by RKNN Toolkit2 is as follows:
|
|||
|
|
|
|||
|
|
| **Operators** | **Remarks** |
|
|||
|
|
| ----------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
|
|||
|
|
| add | same as onnx Add |
|
|||
|
|
| batchnormalize | same as onnx BatchNormalization |
|
|||
|
|
| concat | same as onnx Concat |
|
|||
|
|
| convolutional | same as onnx Conv |
|
|||
|
|
| depthwise_convolutional | kernel height/width: [1, 8]<br />others same as onnx Conv |
|
|||
|
|
| fullconnect | |
|
|||
|
|
| leakyrelu | same as onnx LeakyRelu |
|
|||
|
|
| mish | |
|
|||
|
|
| pooling | **AveragePool**: same as onnx AveragePool <br /> **GlobalAveragePool**: same as onnx GlobalAveragePool <br /> **MaxPool/GlobalMaxPool**: same as onnx MaxPool/GlobalMaxPool |
|
|||
|
|
| route | |
|
|||
|
|
| shortcut | |
|
|||
|
|
| softmax | |
|
|||
|
|
| upsampling | |
|