onnxruntime/js/web/docs/webgpu-operators.md
Guenther Schmuelling 0df2e14038
js/webgpu: argmax,argmin,softmax support (#16882)
argmax and argmin are similar to reduce. Eventually we need to add
optimized flavors of the shader.

softmax is optimized but only works on the last axis for now which
should be the common use case.

todo: enable more ut for argmax/argmin
2023-08-02 18:16:19 -07:00

3.4 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+)
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 is not supported; need implementing activation
ConvTranspose ai.onnx(1-10,11+); com.ms.internal.nhwc(11+) need perf optimization; ConvTranspose3d is not supported; need implementing activation
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+)
Flatten ai.onnx(1-8,9-10,11-12,13+)
Floor ai.onnx(6-12,13+)
Gelu com.microsoft(1+)
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
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+)
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+)
ThresholdedRelu ai.onnx(10+)
Transpose ai.onnx(1-12,13+) need perf optimization
Unsqueeze ai.onnx(1-10,11-12,13+)