mirror of
https://github.com/saymrwulf/onnxruntime.git
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2c39d0c502
WebNN CPU backend implementation has been migrated from XNNPack to TFLite, currently TFLite has not supported WebNN's convTranspose2d yet, just disable it for now.
92 lines
7.5 KiB
Markdown
92 lines
7.5 KiB
Markdown
## Operators Support Table
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The following table shows ONNX
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operators and the supported opset domain/versions in **WebNN EP** by ONNX Runtime Web. For example,
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`7-12, 13+` means ONNX Runtime Web currently supports opset version 7 to 12, 13 and above.
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(**Note**: ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'.)
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[WebNN API](https://webmachinelearning.github.io/webnn) 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](https://webmachinelearning.github.io/webnn-status/) behind these two backends is inconsistent since XNNPack backend currently supports limited op scope.
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| Operator | Opset | WebNN API | WebNN CPU | WebNN GPU | Comments |
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|:------:|:------:|:------:|:-:|:-:|:------|
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| Abs | ai.onnx(7-12, 13+) | abs | ✓ | ✓ | |
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| Add | ai.onnx(7-12, 13, 14+) | add | ✓ | ✓ | |
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| ArgMax | ai.onnx(7-10, 11, 12, 13+) | argMax | ✗ | ✓ | |
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| ArgMin | ai.onnx(7-10, 11, 12, 13+) | argMin | ✗ | ✓ | |
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| 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 |
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| BatchNormalization | ai.onnx(7-8, 9-13, 14, 15+) | batchNormalization | ✗ | ✓ | Only supports 'training_mode' value is 0, one output |
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| Cast | ai.onnx(7-8, 9-12, 13-18, 19-20, 21+) | cast | ✗ | ✓ | |
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| Ceil | ai.onnx(7-12, 13+) | ceil | ✓ | ✓ | |
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| Clip | ai.onnx(7-10, 11, 12, 13+) | clamp | ✓ | ✓ | |
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| Concat | ai.onnx(7-10, 11-12, 13+) | concat | ✓ | ✓ | |
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| 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 |
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| ConvTranspose | ai.onnx(7-10, 11+) | convTranspose2d | ✓ | ✗ | Only supports 3-D or 4-D input and 'W' (weight). |
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| Cos | ai.onnx(7+) | cos | ✗ | ✓ | |
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| Div | ai.onnx(7-12, 13, 14+) | div | ✓ | ✓ | |
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| Elu | ai.onnx(7+) | elu | ✓ | ✓ | |
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| Equal | ai.onnx(7-10, 11-12, 13-18, 19+) | equal | ✗ | ✓ | |
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| Erf | ai.onnx(7-9, 10-12, 13+) | erf | ✗ | ✓ | |
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| Exp | ai.onnx(7-12, 13+) | exp | ✗ | ✓ | |
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| Expand | ai.onnx(8-12, 13+) | expand | ✗ | ✓ | 'shape' input should be a constant |
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| Flatten | ai.onnx(7-8, 9-10, 11-12, 13-20, 21+) | reshape | ✓ | ✓ | |
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| Floor | ai.onnx(7-12, 13+) | floor | ✓ | ✓ | |
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| Gather | ai.onnx(7-10, 11-12, 13+) | gather | ✗ | ✓ | |
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| Gelu | ai.onnx(20+) | gelu | ✗ | ✓ | |
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| Gemm | ai.onnx(7-8, 9-10, 11-12, 13+) | gemm | ✓ | ✓ | Only supports 1-D 'C' input |
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| GlobalAveragePool | ai.onnx(7+) | averagePool2d | ✓ | ✓ | Only supports 4-D input |
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| GlobalMaxPool | ai.onnx(7+) | maxPool2d | ✓ | ✓ | Only supports 4-D input |
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| GlobalLpPool| ai.onnx(7+) | l2Pool2d | ✗ | ✓ | Only supports 4-D input, 'p' value is 2 |
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| Greater | ai.onnx(7-8, 9-12, 13+) | greater | ✗ | ✓ | |
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| GreaterOrEqual | ai.onnx(12-15, 16+) | greaterOrEqual | ✗ | ✓ | |
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| HardSigmoid | ai.onnx(7+) | hardSigmoid | ✗ | ✓ | |
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| HardSwish | ai.onnx(14+) | hardSwish | ✓ | ✓ | |
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| Identity | ai.onnx(7-13, 14-15, 16-18, 19-20, 21+) | identity | ✗ | ✓ | |
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| InstanceNormalization | ai.onnx(7+) | instanceNormalization | ✗ | ✓ | |
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| LayerNormalization | ai.onnx(7-16, 17+) | layerNormalization | ✗ | ✓ | |
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| LeakyRelu | ai.onnx(7-15, 16+) | leakyRelu | ✓ | ✓ | |
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| Less | ai.onnx(7-8, 9-12, 13+) | lesser | ✗ | ✓ | |
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| LessOrEqual | ai.onnx(12-15, 16+) | lesserOrEqual | ✗ | ✓ | |
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| Log | ai.onnx(7-12, 13+) | log | ✗ | ✓ | |
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| LpPool | ai.onnx(7-10, 11-17, 18+) | l2Pool2d | ✗ | ✓ | Only supports 4-D input, 2-D 'kernel_shape', 'p' value is 2 |
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| MatMul | ai.onnx(7-8, 9-12, 13+) | matmul | ✓ | ✓ | WebNN CPU doesn't support broadcasting for MatMul |
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| Max | ai.onnx(7, 8-11, 12, 13+) | max | ✓ | ✓ | |
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| MaxPool | ai.onnx(7, 8-9, 10, 11, 12+) | maxPool2d | ✓ | ✓ | Only supports 4-D input, 2-D 'kernel_shape', 'storage_order' != 1, one output |
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| Min | ai.onnx(7, 8-11, 12, 13+) | min | ✓ | ✓ | |
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| Mul | ai.onnx(7-12, 13, 14+) | mul | ✓ | ✓ | |
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| Neg | ai.onnx(7-12, 13+) | neg | ✓ | ✓ | |
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| Not | ai.onnx(7+) | logicalnot | ✗ | ✓ | |
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| Pad | ai.onnx(7-10, 11-12, 13-17, 18, 19-20, 21+) | pad | ✓ | ✓ | modes == 'wrap' is not supported |
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| Pow | ai.onnx(7-11, 12, 13-14, 15+) | pow | ✗ | ✓ | |
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| PRelu | ai.onnx(7-8, 9-15, 16+) | prelu | ✓ | ✓ | WebNN CPU restricts slope to be a static value |
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| Reciprocal | ai.onnx(7-12, 13+) | reciprocal | ✗ | ✓ | |
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| ReduceL1 | ai.onnx(7-10, 11-12, 13-17, 18+) | reduceL1 | ✗ | ✓ | Input 'axes' if present should be a constant |
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| ReduceL2 | ai.onnx(7-10, 11-12, 13-17, 18+) | reduceL2 | ✗ | ✓ | Input 'axes' if present should be a constant |
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| ReduceLogSum| ai.onnx(7-10, 11-12, 13-17, 18+) | reduceLogSum| ✗ | ✓ | Input 'axes' if present should be a constant |
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| ReduceLogSumExp | ai.onnx(7-10, 11-12, 13-17, 18+) | reduceLogSumExp | ✗ | ✓ | Input 'axes' if present should be a constant |
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| ReduceMax | ai.onnx(7-10, 11, 12, 13-17, 18-19, 20+) | reduceMax | ✗ | ✓ | Input 'axes' if present should be a constant |
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| ReduceMean | ai.onnx(7-10, 11-12, 13-17, 18+) | reduceMean | ✓ | ✓ | Input 'axes' if present should be a constant |
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| ReduceMin | ai.onnx(7-10, 11, 12, 13-17, 18-19, 20+) | reduceMin | ✗ | ✓ | Input 'axes' if present should be a constant |
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| ReduceProd | ai.onnx(7-10, 11-12, 13-17, 18+) | reduceProduct | ✗ | ✓ | Input 'axes' if present should be a constant |
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| ReduceSum | ai.onnx(7-10, 11-12, 13+) | reduceSum | ✗ | ✓ | Input 'axes' if present should be a constant |
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| ReduceSumSquare | ai.onnx(7-10, 11-12, 13-17, 18+) | reduceSumSquare | ✗ | ✓ | Input 'axes' if present should be a constant |
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| Relu | ai.onnx(7-12, 13, 14+) | relu | ✓ | ✓ | |
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| 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 |
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| 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 |
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| Shape | ai.onnx(7-12, 13-14, 15-18, 19-20, 21+) | slice | ✓ | ✓ | |
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| Sigmoid | ai.onnx(7-12, 13+) | sigmoid | ✓ | ✓ | |
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| Softplus | ai.onnx(7+) | softplus | ✗ | ✓ | |
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| Softsign | ai.onnx(7+) | softsign | ✗ | ✓ | |
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| Sin | ai.onnx(7+) | sin | ✗ | ✓ | |
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| 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 |
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| Softmax | ai.onnx(7-10, 11-12, 13+) | softmax | ✓ | ✓ | Only supports input rank >= 2 |
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| Split | ai.onnx(7-10, 11-12, 13-17, 18+) | split | ✓ | ✓ | Input 'split' if present should be a constant, WebNN CPU backend only supports up to 4 outputs |
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| Sqrt | ai.onnx(7-12, 13+) | sqrt | ✓ | ✓ | |
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| Squeeze | ai.onnx(7-10, 11-12, 13-20, 21+) | reshape | ✓ | ✓ | Input 'axes' if present should be a constant |
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| Sub | ai.onnx(7-12, 13, 14+) | sub | ✓ | ✓ | |
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| Tan | ai.onnx(7+) | tan | ✗ | ✓ | |
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| Tanh | ai.onnx(7-12, 13+) | tanh | ✓ | ✓ | |
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| Transpose | ai.onnx(7-12, 13-20, 21+) | transpose | ✓ | ✓ | |
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| Unsqueeze | ai.onnx(7-10, 11-12, 13-20, 21+) | reshape | ✓ | ✓ | |
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| Where | ai.onnx(7-8, 9-15, 16+) | where | ✗ | ✓ | |
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