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03ce0a5693
### Description Added Slice operator support to JSEP. ### Motivation and Context <!-- - Why is this change required? What problem does it solve? - If it fixes an open issue, please link to the issue here. -->
3 KiB
3 KiB
Operators Support Table
The following table shows ONNX
operators and the supported opset domain/versions in WebGPU EP by ONNX Runtime Web. For example,
4-6, 8+ means ONNX Runtime Web currently support opset version 4 to 6, 8 and above.
This file is automatically generated from the def files via this script. Do not modify directly.
| Operator | Opset | Comments |
|---|---|---|
| Abs | ai.onnx(6-12,13+) | |
| Acos | ai.onnx(7+) | |
| Acosh | ai.onnx(9+) | |
| Add | ai.onnx(7-12,13,14+) | |
| Asin | ai.onnx(7+) | |
| Asinh | ai.onnx(9+) | |
| Atan | ai.onnx(7+) | |
| Atanh | ai.onnx(9+) | |
| AveragePool | ai.onnx(7-9,10,11+); com.ms.internal.nhwc(11+) | need perf optimization; need implementing activation |
| Ceil | ai.onnx(6-12,13+) | |
| Clip | ai.onnx(6-10,11,12,13+) | |
| Concat | ai.onnx(1-3,4-10,11-12,13+) | |
| Conv | ai.onnx(1-10,11+); com.ms.internal.nhwc(11+) | need perf optimization; conv3d not supported; need implementing activation |
| ConvTranspose | ai.onnx(1-10,11+); com.ms.internal.nhwc(11+) | |
| Cos | ai.onnx(7+) | |
| Cosh | ai.onnx(9+) | |
| Div | ai.onnx(7-12,13,14+) | |
| Elu | ai.onnx(6+) | |
| Erf | ai.onnx(9-12,13+) | |
| Exp | ai.onnx(6-12,13+) | |
| Expand | ai.onnx(8-12,13+) | |
| Floor | ai.onnx(6-12,13+) | |
| Gemm | ai.onnx(7-8,9-10,11+) | |
| GlobalAveragePool | ai.onnx(1+); com.ms.internal.nhwc(1+) | |
| GlobalMaxPool | ai.onnx(1+); com.ms.internal.nhwc(1+) | |
| LeakyRelu | ai.onnx(6-15,16+) | |
| MatMul | ai.onnx(1-12,13+) | |
| MaxPool | ai.onnx(1-7,8-9,10,11,12+); com.ms.internal.nhwc(11,12+) | need perf optimization; need implementing activation |
| MemcpyFromHost | ai.onnx(1+) | |
| MemcpyToHost | ai.onnx(1+) | |
| Mul | ai.onnx(7-12,13,14+) | |
| Neg | ai.onnx(6-12,13+) | |
| Pow | ai.onnx(7-11,12,13-14,15+) | |
| Reciprocal | ai.onnx(6-12,13+) | |
| ReduceL1 | ai.onnx(1-10,11-12,13-17,18+) | |
| ReduceL2 | ai.onnx(1-10,11-12,13-17,18+) | |
| ReduceLogSum | ai.onnx(1-10,11-12,13-17,18+) | |
| ReduceLogSumExp | ai.onnx(1-10,11-12,13-17,18+) | |
| ReduceMax | ai.onnx(1-10,11,12,13-17,18+) | |
| ReduceMean | ai.onnx(1-10,11-12,13-17,18+) | |
| ReduceMin | ai.onnx(1-10,11,12,13-17,18+) | |
| ReduceProd | ai.onnx(1-10,11-12,13-17,18+) | |
| ReduceSum | ai.onnx(1-10,11-12,13+) | |
| ReduceSumSquare | ai.onnx(1-10,11-12,13-17,18+) | |
| Relu | ai.onnx(6-12,13,14+) | |
| Reshape | ai.onnx(5-12,13,14+) | no GPU kernel |
| Shape | ai.onnx(1-12,13-14,15+) | no GPU kernel; an ORT warning is generated - need to fix |
| Sigmoid | ai.onnx(6-12,13+) | |
| Sin | ai.onnx(7+) | |
| Sinh | ai.onnx(9+) | |
| Slice | ai.onnx(1-9,10,11-12,13+) | |
| Split | ai.onnx(1,2-10,11-12,13-17,18+) | |
| Sqrt | ai.onnx(6-12,13+) | |
| Squeeze | ai.onnx(1-10,11-12,13+) | |
| Sub | ai.onnx(7-12,13,14+) | |
| Tan | ai.onnx(7+) | |
| ThresholdedRelu | ai.onnx(10+) | |
| Transpose | ai.onnx(1-12,13+) | need perf optimization |
| Unsqueeze | ai.onnx(1-10,11-12,13+) |