WebNN Operators - Honry/onnxruntime GitHub Wiki
Operators Support Table
The following table shows ONNX
operators and the supported opset domain/versions in WebNN EP by ONNX Runtime Web. For example,
7-12, 13+ means ONNX Runtime Web currently supports opset version 7 to 12, 13 and above.
(Note: ONNX Runtime only guarantees support for models stamped with opset version 7 or above for opset domain 'ai.onnx'.)
WebNN API provides two device types cpu and gpu to leverage different on-device accelerators. WebNN API implementation in Chromium uses XNNPack backend for cpu device type and DirectML backend for gpu device type. The op support status behind these two backends is inconsistent since XNNPack backend currently supports limited op scope.
| Operator | Opset | WebNN API | WebNN CPU | WebNN GPU | Comments |
|---|---|---|---|---|---|
| Abs | ai.onnx(7-12, 13+) | abs | ✓ | ✓ | |
| Add | ai.onnx(7-12, 13, 14+) | add | ✓ | ✓ | |
| ArgMax | ai.onnx(7-10, 11, 12, 13+) | argMax | ✗ | ✓ | |
| ArgMin | ai.onnx(7-10, 11, 12, 13+) | argMin | ✗ | ✓ | |
| AveragePool | ai.onnx(7-9, 10, 11, 12-18, 19+) | averagePool2d | ✓ | ✓ | Only supports 4-D input, 2-D 'kernel_shape', 'count_include_pad' value is 0 |
| BatchNormalization | ai.onnx(7-8, 9-13, 14, 15+) | batchNormalization | ✗ | ✓ | Only supports 'training_mode' value is 0, one output |
| Cast | ai.onnx(7-8, 9-12, 13-18, 19-20, 21+) | cast | ✗ | ✓ | |
| Ceil | ai.onnx(7-12, 13+) | ceil | ✓ | ✓ | |
| Clip | ai.onnx(7-10, 11, 12, 13+) | clamp | ✓ | ✓ | |
| Concat | ai.onnx(7-10, 11-12, 13+) | concat | ✓ | ✓ | |
| Conv | ai.onnx(7-10, 11+) | conv2d | ✓ | ✓ | Only supports 3-D or 4-D input and 'W' (weight). WebNN CPU requires the 'W' (weight) input to be a constant. |
| ConvInteger | ai.onnx(10+) | conv2dInteger | ✗ | ✓ | Only supports 3-D or 4-D input and 'W' (weight). |
| ConvTranspose | ai.onnx(7-10, 11+) | convTranspose2d | ✓ | ✓ | Only supports 3-D or 4-D input and 'W' (weight). WebNN CPU requires the 'W' (weight) input to be a constant. |
| Cos | ai.onnx(7+) | cos | ✗ | ✓ | |
| Div | ai.onnx(7-12, 13, 14+) | div | ✓ | ✓ | |
| DequantizeLinear | ai.onnx(10-12, 13-18, 19-20, 21+) | dequantizeLinear | ✗ | ✓ | |
| DynamicQuantizeLinear | ai.onnx(11+) | dynamicQuantizeLinear | ✗ | ✓ | |
| Elu | ai.onnx(7+) | elu | ✓ | ✓ | |
| Equal | ai.onnx(7-10, 11-12, 13-18, 19+) | equal | ✗ | ✓ | |
| Erf | ai.onnx(7-9, 10-12, 13+) | erf | ✗ | ✓ | |
| Exp | ai.onnx(7-12, 13+) | exp | ✗ | ✓ | |
| Expand | ai.onnx(8-12, 13+) | expand | ✗ | ✓ | 'shape' input should be a constant. |
| Flatten | ai.onnx(7-8, 9-10, 11-12, 13-20, 21+) | reshape | ✓ | ✓ | |
| Floor | ai.onnx(7-12, 13+) | floor | ✓ | ✓ | |
| Gather | ai.onnx(7-10, 11-12, 13+) | gather | ✗ | ✓ | |
| Gemm | ai.onnx(7-8, 9-10, 11-12, 13+) | gemm | ✓ | ✓ | Only supports 1-D 'C' input |
| GlobalAveragePool | ai.onnx(7+) | averagePool2d | ✓ | ✓ | Only supports 4-D input |
| GlobalMaxPool | ai.onnx(7+) | maxPool2d | ✓ | ✓ | Only supports 4-D input |
| GlobalLpPool | ai.onnx(7+) | l2Pool2d | ✗ | ✓ | Only supports 4-D input, 'p' value is 2 |
| Greater | ai.onnx(7-8, 9-12, 13+) | greater | ✗ | ✓ | |
| GreaterOrEqual | ai.onnx(12-15, 16+) | greaterOrEqual | ✗ | ✓ | |
| HardSigmoid | ai.onnx(7+) | hardSigmoid | ✗ | ✓ | |
| HardSwish | ai.onnx(14+) | hardSwish | ✓ | ✓ | |
| Identity | ai.onnx(7-13, 14-15, 16-18, 19-20, 21+) | identity | ✗ | ✓ | |
| InstanceNormalization | ai.onnx(7+) | instanceNormalization | ✗ | ✓ | |
| LayerNormalization | ai.onnx(7-16, 17+) | layerNormalization | ✗ | ✓ | |
| LeakyRelu | ai.onnx(7-15, 16+) | leakyRelu | ✓ | ✓ | |
| Less | ai.onnx(7-8, 9-12, 13+) | lesser | ✗ | ✓ | |
| LessOrEqual | ai.onnx(12-15, 16+) | lesserOrEqual | ✗ | ✓ | |
| Log | ai.onnx(7-12, 13+) | log | ✗ | ✓ | |
| LpPool | ai.onnx(7-10, 11-17, 18+) | l2Pool2d | ✗ | ✓ | Only supports 4-D input, 2-D 'kernel_shape', 'p' value is 2 |
| MatMul | ai.onnx(7-8, 9-12, 13+) | matmul | ✓ | ✓ | WebNN CPU doesn't support broadcasting for MatMul |
| MatMulInteger | ai.onnx(10+) | matmulInteger | ✗ | ✓ | |
| Max | ai.onnx(7, 8-11, 12, 13+) | max | ✓ | ✓ | |
| MaxPool | ai.onnx(7, 8-9, 10, 11, 12+) | maxPool2d | ✓ | ✓ | Only supports 4-D input, 2-D 'kernel_shape', 'storage_order' != 1, one output |
| Min | ai.onnx(7, 8-11, 12, 13+) | min | ✓ | ✓ | |
| Mul | ai.onnx(7-12, 13, 14+) | mul | ✓ | ✓ | |
| Neg | ai.onnx(7-12, 13+) | neg | ✓ | ✓ | |
| Not | ai.onnx(7+) | logicalnot | ✗ | ✓ | |
| Pad | ai.onnx(7-10, 11-12, 13-17, 18, 19-20, 21+) | pad | ✓ | ✓ | modes == 'wrap' is not supported |
| Pow | ai.onnx(7-11, 12, 13-14, 15+) | pow | ✗ | ✓ | |
| PRelu | ai.onnx(7-8, 9-15, 16+) | prelu | ✓ | ✓ | WebNN CPU restricts slope to be a static value |
| Reciprocal | ai.onnx(7-12, 13+) | reciprocal | ✗ | ✓ | |
| ReduceL1 | ai.onnx(7-10, 11-12, 13-17, 18+) | reduceL1 | ✗ | ✓ | Input 'axes' if present should be a constant |
| ReduceL2 | ai.onnx(7-10, 11-12, 13-17, 18+) | reduceL2 | ✗ | ✓ | Input 'axes' if present should be a constant |
| ReduceLogSum | ai.onnx(7-10, 11-12, 13-17, 18+) | reduceLogSum | ✗ | ✓ | Input 'axes' if present should be a constant |
| ReduceLogSumExp | ai.onnx(7-10, 11-12, 13-17, 18+) | reduceLogSumExp | ✗ | ✓ | Input 'axes' if present should be a constant |
| ReduceMax | ai.onnx(7-10, 11, 12, 13-17, 18-19, 20+) | reduceMax | ✗ | ✓ | Input 'axes' if present should be a constant |
| ReduceMean | ai.onnx(7-10, 11-12, 13-17, 18+) | reduceMean | ✓ | ✓ | Input 'axes' if present should be a constant |
| ReduceMin | ai.onnx(7-10, 11, 12, 13-17, 18-19, 20+) | reduceMin | ✗ | ✓ | Input 'axes' if present should be a constant |
| ReduceProd | ai.onnx(7-10, 11-12, 13-17, 18+) | reduceProduct | ✗ | ✓ | Input 'axes' if present should be a constant |
| ReduceSum | ai.onnx(7-10, 11-12, 13+) | reduceSum | ✗ | ✓ | Input 'axes' if present should be a constant |
| ReduceSumSquare | ai.onnx(7-10, 11-12, 13-17, 18+) | reduceSumSquare | ✗ | ✓ | Input 'axes' if present should be a constant |
| Relu | ai.onnx(7-12, 13, 14+) | relu | ✓ | ✓ | |
| Reshape | ai.onnx(7-12, 13, 14-18, 19-20, 21+) | reshape | ✓ | ✓ | Input 'shape' should be a constant, 0 dimension value in 'shape' is not supported |
| Resize | ai.onnx(11-12, 13-17, 18, 19+) | resample2d | ✓ | ✓ | Only supports 4-D input, exclude_outside !=0, input 'scales' and 'sizes' if present must be a constant, WebNN CPU backend only supports 'linear' mode, WebNN GPU backend only supports 'linear' and 'nearest' modes |
| Shape | ai.onnx(7-12, 13-14, 15-18, 19-20, 21+) | slice | ✓ | ✓ | |
| Sigmoid | ai.onnx(7-12, 13+) | sigmoid | ✓ | ✓ | |
| Softplus | ai.onnx(7+) | softplus | ✗ | ✓ | |
| Softsign | ai.onnx(7+) | softsign | ✗ | ✓ | |
| Sin | ai.onnx(7+) | sin | ✗ | ✓ | |
| Slice | ai.onnx(7-9, 10, 11-12, 13+) | slice | ✓ | ✓ | Input 'starts', 'ends', 'axes', and 'steps' if present must be a constant, only supports 'steps' value 1 |
| Softmax | ai.onnx(7-10, 11-12, 13+) | softmax | ✓ | ✓ | Only supports input rank >= 2 |
| Split | ai.onnx(7-10, 11-12, 13-17, 18+) | split | ✓ | ✓ | Input 'split' if present should be a constant |
| Sqrt | ai.onnx(7-12, 13+) | sqrt | ✓ | ✓ | |
| Squeeze | ai.onnx(7-10, 11-12, 13-20, 21+) | reshape | ✓ | ✓ | Input 'axes' if present should be a constant |
| Sub | ai.onnx(7-12, 13, 14+) | sub | ✓ | ✓ | |
| Tan | ai.onnx(7+) | tan | ✗ | ✓ | |
| Tanh | ai.onnx(7-12, 13+) | tanh | ✓ | ✓ | |
| Transpose | ai.onnx(7-12, 13-20, 21+) | transpose | ✓ | ✓ | |
| Unsqueeze | ai.onnx(7-10, 11-12, 13-20, 21+) | reshape | ✓ | ✓ | |
| Where | ai.onnx(7-8, 9-15, 16+) | where | ✗ | ✓ |