38 KiB
Executable File
38 KiB
Executable File
RKNNToolkit2 OPs Support
ONNX OPs supported by RKNN Toolkit2
According to ONNX official instructions, the corresponding ONNX opset version is 12.
The list of ONNX OPs supported by RKNN Toolkit2 is as follows:
(For more restrictions, please refer to RKNN_Compiler_Support_Operator_List.pdf)
| Operators | Remarks |
|---|---|
| Abs | Not Supported |
| Acos | Not Supported |
| Acosh | Not Supported |
| Add | |
| And | Not Supported |
| ArgMax | |
| ArgMin | |
| Asin | Not Supported |
| Asinh | Not Supported |
| Atan | Not Supported |
| Atanh | Not Supported |
| AveragePool | |
| BatchNormalization | |
| BitShift | Not Supported |
| Cast | |
| Ceil | Not Supported |
| Celu | Not Supported |
| Clip | |
| Compress | Not Supported |
| Concat | |
| ConcatFromSequence | Not Supported |
| Constant | |
| ConstantOfShape | |
| Conv | |
| ConvInteger | Not Supported |
| ConvTranspose | |
| Cos | |
| Cosh | Not Supported |
| CumSum | Not Supported |
| DepthToSpace | |
| DequantizeLinear | |
| Det | Not Supported |
| Div | |
| Dropout | |
| Einsum | Not Supported |
| Elu | |
| Equal | |
| Erf | Not Supported |
| Exp | |
| Expand | Not Supported |
| EyeLike | only support constant input |
| Flatten | |
| Floor | Not Supported |
| GRU | batchsize: 1 |
| Gather | |
| GatherElements | Not Supported |
| GatherND | Not Supported |
| Gemm | |
| GlobalAveragePool | |
| GlobalLpPool | Not Supported |
| GlobalMaxPool | |
| Greater | |
| GreaterOrEqual | |
| HardSigmoid | |
| HardSwish | |
| Hardmax | Not Supported |
| Identity | |
| If | only support constant input |
| InstanceNormalization | |
| IsInf | Not Supported |
| IsNaN | Not Supported |
| LRN | |
| LSTM | |
| LeakyRelu | |
| Less | |
| LessOrEqual | |
| Log | Not Supported |
| LogSoftmax | batchsize: 1 |
| Loop | Not Supported |
| LpNormalization | |
| LpPool | Not Supported |
| MatMul | |
| MatMulInteger | Not Supported |
| Max | |
| MaxPool | |
| MaxRoiPool | |
| MaxUnpool | |
| Mean | Not Supported |
| Min | |
| Mod | Not Supported |
| Mul | |
| Multinomial | Not Supported |
| Neg | Not Supported |
| NonMaxSuppression | Not Supported |
| NonZero | Not Supported |
| Not | Not Supported |
| OneHot | Not Supported |
| Or | Not Supported |
| PRelu | |
| Pad | |
| Pow | |
| QLinearConv | Not Supported |
| QLinearMatMul | Not Supported |
| QuantizeLinear | |
| RNN | Not Supported |
| RandomNormal | Not Supported |
| RandomNormalLike | Not Supported |
| RandomUniform | Not Supported |
| RandomUniformLike | Not Supported |
| Range | Not Supported |
| Reciprocal | Not Supported |
| ReduceL1 | Not Supported |
| ReduceL2 | Not Supported |
| ReduceLogSum | Not Supported |
| ReduceLogSumExp | Not Supported |
| ReduceMax | |
| ReduceMean | |
| ReduceMin | |
| ReduceProd | Not Supported |
| ReduceSum | |
| ReduceSumSquare | Not Supported |
| Relu | |
| Reshape | |
| Resize | mode: nearest2d/bilinear |
| ReverseSequence | |
| RoiAlign | pool type: average batchsize: 1 |
| Round | Not Supported |
| Scan | Not Supported |
| ScatterElements | Not Supported |
| ScatterND | |
| Selu | Not Supported |
| SequenceAt | Not Supported |
| SequenceConstruct | Not Supported |
| SequenceEmpty | Not Supported |
| SequenceErase | Not Supported |
| SequenceInsert | Not Supported |
| SequenceLength | Not Supported |
| Shape | |
| Shrink | Not Supported |
| Sigmoid | |
| Sign | Not Supported |
| Sin | |
| Sinh | Not Supported |
| Size | |
| Slice | batchsize: 1 |
| Softmax | batchsize: 1 |
| Softplus | |
| Softsign | Not Supported |
| SpaceToDepth | |
| Split | |
| SplitToSequence | Not Supported |
| Sqrt | |
| Squeeze | |
| StringNormalizer | Not Supported |
| Sub | |
| Sum | Not Supported |
| Tan | Not Supported |
| Tanh | |
| TfIdfVectorizer | Not Supported |
| ThresholdedRelu | Not Supported |
| Tile | batchsize: 1 not support broadcast |
| TopK | Not Supported |
| Transpose | |
| Trilu | Not Supported |
| Unique | Not Supported |
| Unsqueeze | |
| Where | |
| Xor | Not Supported |
Pytorch OPs supported by RKNN Toolkit2
The Pytorch version supported by RKNN Toolkit2 is >1.6.0, models generated by other versions may not support.
The list of Pytorch OPs supported by RKNN Toolkit2 is as follows:
| Operators | Remarks |
|---|---|
| aten::_convolution | same as onnx Conv |
| aten::abs | Not supported |
| aten::abs_ | Not supported |
| aten::adaptive_avg_pool1d | Not supported |
| aten::adaptive_avg_pool2d | same as onnx AveragePool |
| aten::adaptive_max_pool1d | Not supported |
| aten::adaptive_max_pool2d | same as onnx MaxPool |
| aten::add | same as onnx Add |
| aten::add_ | |
| aten::addmm | same as onnx Gemm |
| aten::affine_grid_generator | Not supported |
| aten::alpha_dropout | |
| aten::alpha_dropout_ | Not supported |
| aten::arange | Not supported |
| aten::avg_pool1d | Not supported |
| aten::avg_pool2d | same as onnx AveragePool |
| aten::avg_pool3d | Not supported |
| aten::batch_norm | same as onnx BatchNormalization |
| aten::bmm | same as onnx MatMul |
| aten::cat | same as onnx Concat |
| aten::celu | Not supported |
| aten::celu_ | Not supported |
| aten::chunk | |
| aten::clamp | |
| aten::clamp_ | |
| aten::clamp_max | Not supported |
| aten::clamp_max_ | Not supported |
| aten::clamp_min | |
| aten::clamp_min_ | Not supported |
| aten::clone | |
| aten::constant_pad_nd | same as onnx Pad |
| aten::contiguous | |
| aten::copy | |
| aten::cos | Not supported |
| 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 | |
| aten::expand_as | Not supported |
| aten::expm1 | Not supported |
| aten::expm1_ | Not supported |
| aten::feature_dropout | |
| aten::feature_dropout_ | Not supported |
| aten::flatten | |
| aten::flip | Not supported |
| 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 | |
| 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::maximum | |
| 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::minimum | |
| aten::min_ | Not supported |
| aten::mish | |
| aten::mm | same as onnx MatMul |
| aten::mul | same as onnx Mul |
| aten::mul_ | |
| aten::narrow | same as onnx Slice |
| aten::ne | |
| 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::prod | |
| aten::reciprocal | |
| aten::reciprocal_ | Not supported |
| aten::reflection_pad1d | |
| aten::reflection_pad2d | |
| aten::relu | same as onnx Relu |
| aten::relu6 | same as onnx Relu |
| aten::relu_ | |
| aten::relu6_ | |
| 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::where | |
| aten::zero_ | Not supported |
| aten::zeros | |
| aten::zeros_like |
Caffe OPs supported by RKNN Toolkit2
Caffe protocols RKNN Toolkit2 uses only based on the officially modified protocol of berkeley.
The protocol based on the official revision of berkeley comes from berkeley caffe, commit hash is 21d0608. On this basis RKNN Toolkit2 have added some OPs.
Based on this protocol, the list of Caffe OPs supported by RKNN Toolkit2 is as follows:
| Operators | Remarks |
|---|---|
| BatchNorm | same as onnx BatchNormalization |
| bn (BatchNorm + Scale) | same as onnx BatchNormalization according to https://github.com/TimoSaemann/caffe-segnet-cudnn5 |
| BNLL | |
| Concat | same as onnx Concat |
| Convolution | same as onnx Conv |
| ConvolutionDepthwise | kernel height/width: [1, 8] others same as onnx Conv |
| Crop | |
| Deconvolution | same as ConvTranspose |
| Dropout | |
| Eltwise | |
| Flatten | |
| HardSigmoid | |
| InnerProduct | same as onnx Gemm |
| LRN | same as onnx LRN |
| Lstm | same as onnx LSTM according to https://github.com/xmfbit/warpctc-caffe |
| Normalize | |
| Permute | same as onnx Transpose |
| Power | |
| Pooling | same as onnx pooling |
| PRelu | same as onnx PRelu |
| Proposal | batch: 1 |
| Reduction | output dims <= 4 |
| Relu | same as onnx Relu |
| Relu6 | same as onnx Clip |
| Reorg | |
| Reshape | same as onnx Reshape |
| Resize | bilinear; nearest |
| Reverse | |
| ROIPooling | same as MaxRoiPool according to https://github.com/twmht/caffe-pva-faster-rcnn |
| Scale | same as onnx Mul |
| Sigmoid | same as onnx Sigmoid |
| Slice | same as onnx Split |
| Softmax | same as onnx Softmax |
| Split | same as onnx Slice |
| TanH | same as onnx TanH |
| Tile | same as onnx Tile |
| Transpose | same as onnx Transpose |
| Upsample | according to https://github.com/SeanQ88/caffe_upsample and https://github.com/TimoSaemann/caffe-segnet-cudnn5 |
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 . 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] 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 | same as onnx Softplus |
| 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] others same as onnx Conv |
| fullconnect | |
| leakyrelu | same as onnx LeakyRelu |
| mish | |
| pooling | AveragePool: same as onnx AveragePool GlobalAveragePool: same as onnx GlobalAveragePool MaxPool/GlobalMaxPool: same as onnx MaxPool/GlobalMaxPool |
| route | |
| shortcut | |
| softmax | |
| upsampling |