TensorRT 10.6 supports operators in the inclusive range of opset 9 to opset 22. Latest information of ONNX operators can be found here. More details and limitations are documented in the chart below.
TensorRT supports the following ONNX data types: DOUBLE, FLOAT32, FLOAT16, BFLOAT16, INT32, INT64, FP8, INT8, INT4, UINT8, and BOOL
Note: There is limited support for DOUBLE type. TensorRT will attempt to cast DOUBLE down to FLOAT, clamping values to
+-FLT_MAXif necessary.
Note: INT8, INT4, and FP8 are treated as
Quantized Typesin TensorRT, where support is available only through quantization from a floating-point type with higher precision. See section 7.4.2 of the developer guide for more information.
Note: UINT8 is only supported as network input or output tensor types.
| Operator | Supported | Supported Types | Restrictions |
|---|---|---|---|
| Abs | Y | FP32, FP16, BF16, INT32, INT64 | |
| Acos | Y | FP32, FP16, BF16 | |
| Acosh | Y | FP32, FP16, BF16 | |
| Add | Y | FP32, FP16, BF16, INT32, INT64 | |
| AffineGrid | N | ||
| And | Y | BOOL | |
| ArgMax | Y | FP32, FP16, BF16, INT32, INT64 | |
| ArgMin | Y | FP32, FP16, BF16, INT32, INT64 | |
| Asin | Y | FP32, FP16, BF16 | |
| Asinh | Y | FP32, FP16, BF16 | |
| Atan | Y | FP32, FP16, BF16 | |
| Atanh | Y | FP32, FP16, BF16 | |
| AveragePool | Y | FP32, FP16, BF16 | 2D or 3D Pooling only. dilations must be empty or all ones |
| BatchNormalization | Y | FP32, FP16, BF16 | |
| Bernoulli | N | ||
| BitShift | N | ||
| BitwiseAnd | N | ||
| BitwiseNot | N | ||
| BitwiseOr | N | ||
| BitwiseXor | N | ||
| BlackmanWindow | Y | ||
| Cast | Y | FP32, FP16, BF16, INT32, INT64, UINT8, BOOL | |
| CastLike | Y | FP32, FP16, BF16, INT32, INT64, UINT8, BOOL | |
| Ceil | Y | FP32, FP16, BF16 | |
| Col2Im | N | ||
| Celu | Y | FP32, FP16, BF16 | |
| CenterCropPad | N | ||
| Clip | Y | FP32, FP16, BF16 | |
| Compress | N | ||
| Concat | Y | FP32, FP16, BF16, INT32, INT64, BOOL | |
| ConcatFromSequence | N | ||
| Constant | Y | FP32, FP16, BF16, INT32, INT64, BOOL | sparse_value, value_string, and value_strings attributes are unsupported. |
| ConstantOfShape | Y | FP32, FP16, BF16, INT32, INF64, BOOL | |
| Conv | Y | FP32, FP16, BF16 | |
| ConvInteger | N | ||
| ConvTranspose | Y | FP32, FP16, BF16 | |
| Cos | Y | FP32, FP16, BF16 | |
| Cosh | Y | FP32, FP16, BF16 | |
| CumSum | Y | FP32, FP16, BF16 | axis must be an initializer |
| DFT | N | ||
| DeformConv | Y | FP32, FP16 | input must have 1D or 2D spatial dimensions. pads for the beginning and end along each spatial axis must be the same |
| DepthToSpace | Y | FP32, FP16, BF16, INT32, INT64 | |
| DequantizeLinear | Y | INT8, FP8, INT4 | x_zero_point must be zero |
| Det | N | ||
| Div | Y | FP32, FP16, BF16, INT32, INT64 | |
| Dropout | Y | FP32, FP16, BF16 | is_traning must be an initializer and evaluate to False. |
| DynamicQuantizeLinear | N | ||
| Einsum | Y | FP32, FP16, BF16 | |
| Elu | Y | FP32, FP16, BF16 | |
| Equal | Y | FP32, FP16, BF16, INT32, INT64 | |
| Erf | Y | FP32, FP16, BF16 | |
| Exp | Y | FP32, FP16, BF16 | |
| Expand | Y | FP32, FP16, BF16, INT32, INT64, BOOL | |
| EyeLike | Y | FP32, FP16, BF16, INT32, INT64, BOOL | input must have static dimensions |
| Flatten | Y | FP32, FP16, BF16, INT32, INT64, BOOL | |
| Floor | Y | FP32, FP16, BF16 | |
| Gather | Y | FP32, FP16, BF16, INT32, INT64, BOOL | |
| GatherElements | Y | FP32, FP16, BF16, INT32, INT64, BOOL | |
| GatherND | Y | FP32, FP16, BF16, INT32, INT64, BOOL | |
| Gelu | Y | FP32, FP16, BF16, INT8, INT32, INT64 | |
| Gemm | Y | FP32, FP16, BF16 | |
| GlobalAveragePool | Y | FP32, FP16, BF16 | |
| GlobalLpPool | Y | FP32, FP16, BF16 | |
| GlobalMaxPool | Y | FP32, FP16, BF16 | |
| Greater | Y | FP32, FP16, BF16, INT32, INT64 | |
| GreaterOrEqual | Y | FP32, FP16, BF16, INT32, INT64 | |
| GridSample | Y | FP32, FP16 | Input must be 4D input. |
| GroupNormalization | Y | FP32, FP16, BF16 | |
| GRU | Y | FP32, FP16, BF16 | For bidirectional GRUs, activation functions must be the same for both the forward and reverse pass |
| HammingWindow | Y | ||
| HannWindow | Y | ||
| HardSigmoid | Y | FP32, FP16, BF16 | |
| HardSwish | Y | FP32, FP16, BF16 | |
| Hardmax | Y | FP32, FP16, BF16 | axis dimension of input must be a build-time constant |
| Identity | Y | FP32, FP16, BF16, INT32, INT64, BOOL | |
| If | Y | FP32, FP16, BF16, INT32, INT64, BOOL | Output tensors of the two conditional branches must have the same rank and must have different names |
| ImageScaler | Y | FP32, FP16, BF16 | |
| ImageDecoder | N | ||
| InstanceNormalization | Y | FP32, FP16, BF16 | |
| IsInf | Y | FP32, FP16, BF16 | |
| IsNaN | Y | FP32, FP16, BF16, INT32, INT64 | |
| LayerNormalization | Y | FP32, FP16, BF16 | Only the first output Y is supported. |
| LeakyRelu | Y | FP32, FP16, BF16 | |
| Less | Y | FP32, FP16, BF16, INT32, INT64 | |
| LessOrEqual | Y | FP32, FP16, BF16, INT32, INT64 | |
| Log | Y | FP32, FP16, BF16 | |
| LogSoftmax | Y | FP32, FP16, BF16 | |
| Loop | Y | FP32, FP16, BF16, INT32, INT64, BOOL | Scan output length cannot be dynamic. The shape of Loop carried dependencies must be the same across all loop iterations. |
| LRN | Y | FP32, FP16, BF16 | |
| LSTM | Y | FP32, FP16, BF16 | For bidirectional LSTMs, activation functions must be the same for both the forward and reverse pass. input_forget attribute must be 0. layout attribute must be 0. |
| LpNormalization | Y | FP32, FP16, BF16 | |
| LpPool | Y | FP32, FP16, BF16 | dilations must be empty or all ones |
| MatMul | Y | FP32, FP16, BF16 | |
| MatMulInteger | N | ||
| Max | Y | FP32, FP16, BF16, INT32, INT64 | |
| MaxPool | Y | FP32, FP16, BF16 | 2D or 3D pooling only. Indices output tensor unsupported. dilations must be empty or all ones |
| MaxRoiPool | N | ||
| MaxUnpool | N | ||
| Mean | Y | FP32, FP16, BF16, FP8, INT32, INT64 | |
| MeanVarianceNormalization | Y | FP32, FP16, BF16 | |
| MelWeightMatrix | N | ||
| Min | Y | FP32, FP16, BF16, INT32, INT64 | |
| Mish | Y | FP32, FP16 | |
| Mod | Y | FP32, FP16, BF16, INT32, INT64 | |
| Mul | Y | FP32, FP16, BF16, INT32, INT64 | |
| Multinomial | N | ||
| Neg | Y | FP32, FP16, BF16, INT32, INT64 | |
| NegativeLogLikelihoodLoss | N | ||
| NonMaxSuppression | Y | FP32, FP16 | |
| NonZero | Y | FP32, FP16 | |
| Not | Y | BOOL | |
| OneHot | Y | FP32, FP16, BF16, INT32, INT64, BOOL | depth must be a build-time constant |
| Optional | N | ||
| OptionalGetElement | N | ||
| OptionalHasElement | N | ||
| Or | Y | BOOL | |
| Pad | Y | FP32, FP16, BF16, INT32, INT64 | |
| ParametricSoftplus | Y | FP32, FP16, BF16 | |
| Pow | Y | FP32, FP16, BF16 | |
| PRelu | Y | FP32, FP16, BF16 | |
| QLinearConv | N | ||
| QLinearMatMul | N | ||
| QuantizeLinear | Y | FP32, FP16, BF16 | y_zero_point must be 0 |
| RandomNormal | Y | FP32, FP16, BF16 | seed value is ignored by TensorRT |
| RandomNormalLike | Y | FP32, FP16, BF16 | seed value is ignored by TensorRT |
| RandomUniform | Y | FP32, FP16, BF16 | seed value is ignored by TensorRT |
| RandomUniformLike | Y | FP32, FP16, BF16 | seed value is ignored by TensorRT |
| Range | Y | FP32, FP16, BF16, INT32, INT64 | |
| Reciprocal | Y | FP32, FP16, BF16 | |
| ReduceL1 | Y | FP32, FP16, BF16, INT32, INT64 | axes must be an initializer |
| ReduceL2 | Y | FP32, FP16, BF16, INT32, INT64 | axes must be an initializer |
| ReduceLogSum | Y | FP32, FP16, BF16, INT32, INT64 | axes must be an initializer |
| ReduceLogSumExp | Y | FP32, FP16, BF16, INT32, INT64 | axes must be an initializer |
| ReduceMax | Y | FP32, FP16, BF16, INT32, INT64 | axes must be an initializer |
| ReduceMean | Y | FP32, FP16, BF16, INT32, INT64 | axes must be an initializer |
| ReduceMin | Y | FP32, FP16, BF16, INT32, INT64 | axes must be an initializer |
| ReduceProd | Y | FP32, FP16, BF16, INT32, INT64 | axes must be an initializer |
| ReduceSum | Y | FP32, FP16, BF16, INT32, INT64 | axes must be an initializer |
| ReduceSumSquare | Y | FP32, FP16, BF16, INT32, INT64 | axes must be an initializer |
| RegexFullMatch | N | ||
| Relu | Y | FP32, FP16, BF16, INT32, INT64 | |
| Reshape | Y | FP32, FP16, BF16, INT32, INT64, BOOL | |
| Resize | Y | FP32, FP16, BF16 | Supported resize transformation modes: half_pixel, pytorch_half_pixel, tf_half_pixel_for_nn, asymmetric, and align_corners.Supported resize modes: nearest, linear.Supported nearest modes: floor, ceil, round_prefer_floor, round_prefer_ceil.Supported aspect ratio policy: stretch.When scales is a tensor input, axes must be an iota vector of length rank(input).Antialiasing is not supported. |
| ReverseSequence | Y | FP32, FP16, BF16, INT32, INT64, BOOL | |
| RNN | Y | FP32, FP16, BF16 | For bidirectional RNNs, activation functions must be the same for both the forward and reverse pass |
| RoiAlign | Y | FP32, FP16 | |
| Round | Y | FP32, FP16, BF16 | |
| STFT | Y | FP32 | frame_step and window must be an initializer. Input must be real-valued. |
| ScaledTanh | Y | FP32, FP16, BF16 | |
| Scan | Y | FP32, FP16, BF16 | |
| Scatter | Y | FP32, FP16, BF16, INT32, INT64 | |
| ScatterElements | Y | FP32, FP16, BF16, INT32, INT64 | |
| ScatterND | Y | FP32, FP16, BF16, INT32, INT64 | reduction is not supported |
| Selu | Y | FP32, FP16, BF16, | |
| SequenceAt | N | ||
| SequenceConstruct | N | ||
| SequenceEmpty | N | ||
| SequenceErase | N | ||
| SequenceInsert | N | ||
| SequenceLength | N | ||
| SequenceMap | N | ||
| Shape | Y | FP32, FP16, BF16, INT32, INT64, BOOL | |
| Shrink | Y | FP32, FP16, BF16, INT32, INT64 | |
| Sigmoid | Y | FP32, FP16, BF16 | |
| Sign | Y | FP32, FP16, BF16, INT32, INT64 | |
| Sin | Y | FP32, FP16, BF16 | |
| Sinh | Y | FP32, FP16, BF16 | |
| Size | Y | FP32, FP16, BF16, INT32, INT64, BOOL | |
| Slice | Y | FP32, FP16, BF16, INT32, INT64, BOOL | |
| Softmax | Y | FP32, FP16, BF16 | |
| SoftmaxCrossEntropyLoss | N | ||
| Softplus | Y | FP32, FP16, BF16 | |
| Softsign | Y | FP32, FP16, BF16 | |
| SpaceToDepth | Y | FP32, FP16, BF16, INT32, INT64 | |
| Split | Y | FP32, FP16, BF16, INT32, INT64, BOOL | |
| SplitToSequence | N | ||
| Sqrt | Y | FP32, FP16, BF16 | |
| Squeeze | Y | FP32, FP16, BF16, INT32, INT64, BOOL | axes must be an initializer |
| StringConcat | N | ||
| StringNormalizer | N | ||
| StringSplit | N | ||
| Sub | Y | FP32, FP16, BF16, INT32, INT64 | |
| Sum | Y | FP32, FP16, BF16, INT32, INT64 | |
| Tan | Y | FP32, FP16, BF16 | |
| Tanh | Y | FP32, FP16, BF16 | |
| TfIdfVectorizer | N | ||
| ThresholdedRelu | Y | FP32, FP16, BF16 | |
| Tile | Y | FP32, FP16, BF16, INT32, INT64, BOOL | |
| TopK | Y | FP32, FP16, BF16, INT32, INT64 | sorted must be 1. K input must be less than 3840. |
| Transpose | Y | FP32, FP16, BF16, INT32, INT64, BOOL | |
| Trilu | Y | FP32, FP16, BF16, INT32, INT64, BOOL | |
| Unique | N | ||
| Unsqueeze | Y | FP32, FP16, BF16, INT32, INT64, BOOL | axes must be a constant tensor |
| Upsample | Y | FP32, FP16, BF16 | |
| Where | Y | FP32, FP16, BF16, INT32, INT64, BOOL | |
| Xor | Y | BOOL |