TensorRT 7.2 supports operators up to Opset 11. Latest information of ONNX operators can be found here
TensorRT supports the following ONNX data types: FLOAT32, FLOAT16, INT8, and BOOL
*There is limited support for INT32 and INT64 types. TensorRT will attempt to cast down INT64 to INT32 where possible. If not possible, TensorRT will throw an error. See the TensorRT layer support matrix for more information on data type support.
| Operator | Supported? | Restrictions |
|---|---|---|
| Abs | Y | |
| Acos | Y | |
| Acosh | Y | |
| Add | Y | |
| And | Y | |
| ArgMax | Y | |
| ArgMin | Y | |
| Asin | Y | |
| Asinh | Y | |
| Atan | Y | |
| Atanh | Y | |
| AveragePool | Y | 2D or 3D Pooling only |
| BatchNormalization | Y | |
| BitShift | N | |
| Cast | Y | Cast is only supported for TRT types |
| Ceil | Y | |
| Celu | Y | |
| Clip | Y | min and max clip values must be an initializer |
| Compress | N | |
| Concat | Y | |
| ConcatFromSequence | N | |
| Constant | Y | |
| ConstantOfShape | Y | |
| Conv | Y | 2D or 3D convolutions only |
| ConvInteger | N | |
| ConvTranspose | Y | 2D or 3D deconvolutions only. Weights must be an initializer |
| Cos | Y | |
| Cosh | Y | |
| CumSum | Y | Axis must be an initializer |
| DepthToSpace | Y | |
| DequantizeLinear | Y | Scales and zero-point value must be initializers |
| Det | N | |
| Div | Y | |
| Dropout | N | |
| Elu | Y | |
| Equal | Y | |
| Erf | Y | |
| Exp | Y | |
| Expand | Y | |
| EyeLike | N | |
| Flatten | Y | |
| Floor | Y | |
| Gather | Y | |
| GatherElements | N | |
| GatherND | N | |
| Gemm | Y | |
| GlobalAveragePool | Y | |
| GlobalLpPool | Y | |
| GlobalMaxPool | Y | |
| Greater | Y | |
| GreaterOrEqual | Y | |
| GRU | Y | |
| HardSigmoid | Y | |
| Hardmax | N | |
| Identity | Y | |
| If | N | |
| ImageScaler | Y | |
| InstanceNormalization | Y | Scales and biases must be an initializer |
| IsInf | N | |
| IsNaN | N | |
| LeakyRelu | Y | |
| Less | Y | |
| LessOrEqual | Y | |
| Log | Y | |
| LogSoftmax | Y | |
| Loop | Y | |
| LRN | Y | |
| LSTM | Y | |
| LpNormalization | Y | |
| LpPool | Y | |
| MatMul | Y | |
| MatMulInteger | N | |
| Max | Y | |
| MaxPool | Y | |
| MaxRoiPool | N | |
| MaxUnpool | N | |
| Mean | Y | |
| Min | Y | |
| Mod | N | |
| Mul | Y | |
| Multinomial | N | |
| Neg | Y | |
| NonMaxSuppression | N | |
| NonZero | N | |
| Not | Y | |
| OneHot | N | |
| Or | Y | |
| Pad | Y | Zero-padding on last 2 dimensions only |
| ParametricSoftplus | Y | |
| Pow | Y | |
| PRelu | Y | |
| QLinearConv | N | |
| QLinearMatMul | N | |
| QuantizeLinear | Y | Scales and zero-point value must be initializers |
| RNN | N | |
| RandomNormal | N | |
| RandomNormalLike | N | |
| RandomUniform | Y | |
| RandomUniformLike | Y | |
| Range | Y | Float inputs are only supported if start, limit and delta inputs are initializers |
| Reciprocal | N | |
| ReduceL1 | Y | |
| ReduceL2 | Y | |
| ReduceLogSum | Y | |
| ReduceLogSumExp | Y | |
| ReduceMax | Y | |
| ReduceMean | Y | |
| ReduceMin | Y | |
| ReduceProd | Y | |
| ReduceSum | Y | |
| ReduceSumSquare | Y | |
| Relu | Y | |
| Reshape | Y | |
| Resize | Y | Asymmetric coordinate transformation mode only. Nearest or Linear resizing mode only. "floor" mode only for resize_mode attribute. |
| ReverseSequence | Y | |
| RNN | Y | |
| RoiAlign | N | |
| Round | N | |
| ScaledTanh | Y | |
| Scan | Y | |
| Scatter | N | |
| ScatterElements | N | |
| ScatterND | N | |
| Selu | Y | |
| SequenceAt | N | |
| SequenceConstruct | N | |
| SequenceEmpty | N | |
| SequenceErase | N | |
| SequenceInsert | N | |
| SequenceLength | N | |
| Shape | Y | |
| Shrink | N | |
| Sigmoid | Y | |
| Sign | N | |
| Sin | Y | |
| Sinh | Y | |
| Size | Y | |
| Slice | Y | Slice axes must be an initializer |
| Softmax | Y | |
| Softplus | Y | |
| Softsign | Y | |
| SpaceToDepth | Y | |
| Split | Y | |
| SplitToSequence | N | |
| Sqrt | Y | |
| Squeeze | Y | |
| StringNormalizer | N | |
| Sub | Y | |
| Sum | Y | |
| Tan | Y | |
| Tanh | Y | |
| TfIdfVectorizer | N | |
| ThresholdedRelu | Y | |
| Tile | Y | |
| TopK | Y | |
| Transpose | Y | |
| Unique | N | |
| Unsqueeze | Y | |
| Upsample | Y | |
| Where | Y | |
| Xor | N |