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### Description This op is required in mobilenetv3-small-100. With this PR, mobilenetv3-small-100 model becomes less than 10 ms from over 100 ms on ADL.
4.6 KiB
4.6 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+) | |
| ArgMax | ai.onnx(1-10,11-12,13+) | |
| ArgMin | ai.onnx(1-10,11-12,13+) | |
| Asin | ai.onnx(7+) | |
| Asinh | ai.onnx(9+) | |
| Atan | ai.onnx(7+) | |
| Atanh | ai.onnx(9+) | |
| Attention | com.microsoft(1+) | need implementing mask and past/present |
| AveragePool | ai.onnx(7-9,10,11+); com.ms.internal.nhwc(7-9,10,11+) | need perf optimization; need implementing activation |
| BatchNormalization | ai.onnx(7-8,9-13,14,15+); com.ms.internal.nhwc(7-8,9-13,14,15+) | |
| BiasAdd | com.microsoft(1+) | |
| BiasSplitGelu | com.microsoft(1+) | |
| Cast | ai.onnx(6-8,9-12,13-18,19+) | |
| 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(1-10,11+) | need perf optimization; conv3d is not supported; need implementing activation |
| ConvTranspose | ai.onnx(1-10,11+); com.ms.internal.nhwc(1-10,11+) | need perf optimization; ConvTranspose3d is not supported; need implementing activation |
| Cos | ai.onnx(7+) | |
| Cosh | ai.onnx(9+) | |
| CumSum | ai.onnx(11-13,14+) | |
| Div | ai.onnx(7-12,13,14+) | |
| Einsum | ai.onnx(12+) | |
| Elu | ai.onnx(6+) | |
| Equal | ai.onnx(7-10,11-12,13-18,19+) | |
| Erf | ai.onnx(9-12,13+) | |
| Exp | ai.onnx(6-12,13+) | |
| Expand | ai.onnx(8-12,13+) | |
| Flatten | ai.onnx(1-8,9-10,11-12,13+) | |
| Floor | ai.onnx(6-12,13+) | |
| FusedConv | com.microsoft(1+) | |
| Gather | ai.onnx(1-10,11-12,13+) | |
| GatherElements | ai.onnx(11-12,13+) | |
| Gelu | com.microsoft(1+) | |
| Gemm | ai.onnx(7-8,9-10,11-12,13+) | |
| GlobalAveragePool | ai.onnx(1+); com.ms.internal.nhwc(1+) | |
| GlobalMaxPool | ai.onnx(1+); com.ms.internal.nhwc(1+) | |
| Greater | ai.onnx(7-8,9-12,13+) | |
| GreaterOrEqual | ai.onnx(12-15,16+) | |
| HardSigmoid | ai.onnx(6+) | |
| If | ai.onnx(1-10,11-12,13-18,19+) | |
| InstanceNormalization | ai.onnx(6+); com.ms.internal.nhwc(6+) | |
| LayerNormalization | ai.onnx(17+) | |
| LeakyRelu | ai.onnx(6-15,16+) | |
| Less | ai.onnx(7-8,9-12,13+) | |
| LessOrEqual | ai.onnx(12-15,16+) | |
| Log | ai.onnx(6-12,13+) | |
| MatMul | ai.onnx(1-12,13+) | |
| MaxPool | ai.onnx(1-7,8-9,10,11,12+); com.ms.internal.nhwc(1-7,8-9,10,11,12+) | need perf optimization; need implementing activation |
| MemcpyFromHost | ai.onnx(1+) | |
| MemcpyToHost | ai.onnx(1+) | |
| Mul | ai.onnx(7-12,13,14+) | |
| MultiHeadAttention | com.microsoft(1+) | need implementing mask and past/present |
| Neg | ai.onnx(6-12,13+) | |
| Not | ai.onnx(1+) | |
| Pad | ai.onnx(2-10,11-12,13-17,18,19+) | |
| Pow | ai.onnx(7-11,12,13-14,15+) | |
| Range | ai.onnx(11+) | |
| 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 |
| Resize | ai.onnx(10,11-12,13-17,18,19+); com.ms.internal.nhwc(10,11-12,13-17,18,19+) | CoordinateTransformMode align_corners is not supported with downsampling |
| 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+) | |
| SkipLayerNormalization | com.microsoft(1+) | |
| Slice | ai.onnx(1-9,10,11-12,13+) | |
| Softmax | ai.onnx(1-10,11-12,13+) | |
| 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+) | |
| Tanh | ai.onnx(6-12,13+) | |
| ThresholdedRelu | ai.onnx(10+) | |
| Tile | ai.onnx(6-12,13+) | |
| Transpose | ai.onnx(1-12,13+) | need perf optimization |
| Unsqueeze | ai.onnx(1-10,11-12,13+) | |
| Where | ai.onnx(9-15,16+) |