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[WebNN] Remove workarounds for TFLite backend #23406

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[WebNN] Remove workarounds for TFLite backend #23406

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208 changes: 105 additions & 103 deletions js/web/docs/webnn-operators.md
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Expand Up @@ -6,108 +6,110 @@ operators and the supported opset domain/versions in **WebNN EP** by ONNX Runtim

(**Note**: ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'.)

[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 TFLite XNNPack delegate 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.
The [WebNN API](https://webmachinelearning.github.io/webnn) is available in the latest versions of Chrome and Edge on Windows,
Linux, macOS, Android, and ChromeOS behind an <i>"Enables WebNN API"</i> flag. The operator support status may vary across these
platforms. Check the [WebNN status](https://webmachinelearning.github.io/webnn-status/) for the latest implementation details.


| Operator | Opset | WebNN API | WebNN CPU | WebNN GPU | Comments |
|:------:|:------:|:------:|:-:|:-:|:------|
| Abs | ai.onnx(7-12, 13+) | abs | ✓ | ✓ | |
| Add | ai.onnx(7-12, 13, 14+) | add | ✓ | ✓ | |
| And | ai.onnx(7+) | logicalAnd | ✗ | ✓ | |
| 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 | ✓ | ✓ | WebNN CPU backend doesn't support casting to uint64 data type |
| Ceil | ai.onnx(7-12, 13+) | ceil | ✓ | ✓ | |
| Clip | ai.onnx(7-10, 11, 12, 13+) | clamp | ✓ | ✓ | WebNN CPU backend only supports 3 specific ranges: [0.0, infinity], [-1.0, 1.0], [0.0, 6.0] (Chromium issue: https://issues.chromium.org/issues/326156496) |
| 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) |
| ConvTranspose | ai.onnx(7-10, 11+) | convTranspose2d | ✓ | ✓ | Only supports 3-D or 4-D input and 'W' (weight). WebNN CPU backend only supports default dilations and group |
| Cos | ai.onnx(7+) | cos | ✓ | ✓ | |
| CumSum | ai.onnx(11-13, 14+) | cumulativeSum | ✓ | ✓ | 'axis' input should be a constant |
| Div | ai.onnx(7-12, 13, 14+) | div | ✓ | ✓ | |
| DequantizeLinear | ai.onnx(10-12, 13-18, 19-20, 21-22, 23+) | dequantizeLinear | ✓ | ✓ | The shape of x_scale should be a subsample of the shape of input |
| Dropout | ai.onnx(7-9, 10-11, 12, 13-21, 22+) | identity | ✓ | ✓ | Only supports test mode |
| Einsum | ai.onnx(12+) | reshape, transpose, matmul, reduceSum, mul, triangular | ✓ | ✓ | |
| Elu | ai.onnx(7+) | elu | ✓ | ✓ | WebNN CPU backend only supports 'alpha' value is 1.0 |
| 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 | ✓ | ✓ | |
| GatherElements | ai.onnx(11-12, 13+) | gatherElements | ✗ | ✓ | |
| GatherND | ai.onnx(11, 12, 13+) | gatherND | ✓ | ✓ | Only supports 'batch_dims' == 0 |
| Gelu | ai.onnx(20+) | gelu | ✓ | ✓ | |
| 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 | ✓ | ✓ | |
| GRU | ai.onnx(7-13, 14-21, 22+) | gru | ✓ | ✓ | Only supports 'layout' == 0. 'clip' is not supported. The activation functions in 'activations' must be one of 'Relu', 'Tanh', 'Sigmoid'. Forward and backward activations must be the same if bidirectional. 'sequence_lens' if present should be constant with values equal to the first dimension length of input 'X' |
| 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 |
| LRN | ai.onnx(7-12, 13+) | pad, averagePool2d, transpose, add, mul, pow, div | ✓ | ✓ | |
| LSTM | ai.onnx(7-13, 14-21, 22+) | lstm | ✓ | ✓ | Only supports 'layout' == 0, 'input_forget' == 0. 'clip' is not supported. The activation functions in 'activations' must be one of 'Relu', 'Tanh', 'Sigmoid'. Forward and backward activations must be the same if bidirectional. 'sequence_lens' if present should be constant with values equal to the first dimension length of input 'X' |
| MatMul | ai.onnx(7-8, 9-12, 13+) | matmul | ✓ | ✓ | |
| 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 | ✓ | ✓ | |
| Or | ai.onnx(7+) | logicalOr | ✗ | ✓ | |
| 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 backend restricts the last dimension of input and slope to be same (Chromium issue: https://issues.chromium.org/issues/335517470) |
| QuantizeLinear | ai.onnx(10-12, 13-18, 19-20, 21-22, 23+) | quantizeLinear | ✓ | ✓ | The shape of x_scale should be a subsample of the shape of input |
| 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, antialias == 0, exclude_outside == 0, keep_aspect_ratio_policy == 'stretch', 'linear' and 'nearest' modes, input 'scales' and 'sizes' if present must be a constant |
| RotaryEmbedding | com.microsoft(1+) | add, concat, gather, mul, reshape, split | ✓ | ✓ | |
| ScatterElements | ai.onnx(11-12, 13-15, 16-17, 18+) | scatterElements | ✗ | ✓ | Only supports 'reduction' == 'none' |
| ScatterND | ai.onnx(11-12, 13-15, 16-17, 18+) | scatterND | ✗ | ✓ | Only supports 'reduction' == 'none' |
| Shape | ai.onnx(7-12, 13-14, 15-18, 19-20, 21+) | slice | ✓ | ✓ | |
| SimplifiedLayerNormalization | ai.onnx(1+) | pow, reduceMean, add, sqrt, div, mul | ✓ | ✓ | |
| Sigmoid | ai.onnx(7-12, 13+) | sigmoid | ✓ | ✓ | |
| Sign | ai.onnx(9-12, 13+) | sign | ✓ | ✓ | |
| SkipSimplifiedLayerNormalization | com.microsoft(1+) | pow, reduceMean, add, sqrt, div, mul | ✓ | ✓ | |
| 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, reverse | ✓ | ✓ | Input 'starts', 'ends', 'axes', and 'steps' if present must be a constant |
| Softmax | ai.onnx(7-10, 11-12, 13+) | softmax | ✓ | ✓ | |
| 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 | ✓ | ✓ | |
| Tile | ai.onnx(7-12, 13+) | tile | ✗ | ✓ | Input 'repeats' should be a constant |
| Transpose | ai.onnx(7-12, 13-20, 21+) | transpose | ✓ | ✓ | |
| Trilu | ai.onnx(14+) | triangular | ✓ | ✓ | Input 'k' (option 'diagonal' for WebNN) if present should be a constant |
| Unsqueeze | ai.onnx(7-10, 11-12, 13-20, 21+) | reshape | ✓ | ✓ | |
| Where | ai.onnx(7-8, 9-15, 16+) | where | ✓ | ✓ | |
| Xor | ai.onnx(7+) | logicalXor | ✗ | ✓ | |
| Operator | Opset | WebNN API | Comments |
|:------:|:------:|:------:|:------|
| Abs | ai.onnx(7-12, 13+) | abs | |
| Add | ai.onnx(7-12, 13, 14+) | add | |
| And | ai.onnx(7+) | logicalAnd | |
| 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) |
| ConvTranspose | ai.onnx(7-10, 11+) | convTranspose2d | Only supports 3-D or 4-D input and 'W' (weight) |
| Cos | ai.onnx(7+) | cos | |
| CumSum | ai.onnx(11-13, 14+) | cumulativeSum | 'axis' input should be a constant |
| Div | ai.onnx(7-12, 13, 14+) | div | |
| DequantizeLinear | ai.onnx(10-12, 13-18, 19-20, 21-22, 23+) | dequantizeLinear | The shape of x_scale should be a subsample of the shape of input |
| Dropout | ai.onnx(7-9, 10-11, 12, 13-21, 22+) | identity | Only supports test mode |
| Einsum | ai.onnx(12+) | reshape, transpose, matmul, reduceSum, mul, triangular | |
| 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 | |
| GatherElements | ai.onnx(11-12, 13+) | gatherElements | |
| GatherND | ai.onnx(11, 12, 13+) | gatherND | Only supports 'batch_dims' == 0 |
| Gelu | ai.onnx(20+) | gelu | |
| 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 | |
| GRU | ai.onnx(7-13, 14-21, 22+) | gru | Only supports 'layout' == 0. 'clip' is not supported. The activation functions in 'activations' must be one of 'Relu', 'Tanh', 'Sigmoid'. Forward and backward activations must be the same if bidirectional. 'sequence_lens' if present should be constant with values equal to the first dimension length of input 'X' |
| 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 |
| LRN | ai.onnx(7-12, 13+) | pad, averagePool2d, transpose, add, mul, pow, div | |
| LSTM | ai.onnx(7-13, 14-21, 22+) | lstm | Only supports 'layout' == 0, 'input_forget' == 0. 'clip' is not supported. The activation functions in 'activations' must be one of 'Relu', 'Tanh', 'Sigmoid'. Forward and backward activations must be the same if bidirectional. 'sequence_lens' if present should be constant with values equal to the first dimension length of input 'X' |
| MatMul | ai.onnx(7-8, 9-12, 13+) | matmul | |
| 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 | |
| Or | ai.onnx(7+) | logicalOr | |
| 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 | |
| QuantizeLinear | ai.onnx(10-12, 13-18, 19-20, 21-22, 23+) | quantizeLinear | The shape of x_scale should be a subsample of the shape of input |
| 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, antialias == 0, exclude_outside == 0, keep_aspect_ratio_policy == 'stretch', 'linear' and 'nearest' modes, input 'scales' and 'sizes' if present must be a constant |
| RotaryEmbedding | com.microsoft(1+) | add, concat, gather, mul, reshape, split | |
| ScatterElements | ai.onnx(11-12, 13-15, 16-17, 18+) | scatterElements | Only supports 'reduction' == 'none' |
| ScatterND | ai.onnx(11-12, 13-15, 16-17, 18+) | scatterND | Only supports 'reduction' == 'none' |
| Shape | ai.onnx(7-12, 13-14, 15-18, 19-20, 21+) | slice | |
| SimplifiedLayerNormalization | ai.onnx(1+) | pow, reduceMean, add, sqrt, div, mul | |
| Sigmoid | ai.onnx(7-12, 13+) | sigmoid | |
| Sign | ai.onnx(9-12, 13+) | sign | |
| SkipSimplifiedLayerNormalization | com.microsoft(1+) | pow, reduceMean, add, sqrt, div, mul | |
| 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, reverse | Input 'starts', 'ends', 'axes', and 'steps' if present must be a constant |
| Softmax | ai.onnx(7-10, 11-12, 13+) | softmax | |
| 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 | |
| Tile | ai.onnx(7-12, 13+) | tile | Input 'repeats' should be a constant |
| Transpose | ai.onnx(7-12, 13-20, 21+) | transpose | |
| Trilu | ai.onnx(14+) | triangular | Input 'k' (option 'diagonal' for WebNN) if present should be a constant |
| Unsqueeze | ai.onnx(7-10, 11-12, 13-20, 21+) | reshape | |
| Where | ai.onnx(7-8, 9-15, 16+) | where | |
| Xor | ai.onnx(7+) | logicalXor | |
28 changes: 0 additions & 28 deletions onnxruntime/core/providers/webnn/builders/impl/activation_op_builder.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -17,10 +17,6 @@ class ActivationOpBuilder : public BaseOpBuilder {
private:
Status AddToModelBuilderImpl(ModelBuilder& model_builder, const Node& node,
const logging::Logger& logger) const override ORT_MUST_USE_RESULT;

// Operator support related.
bool IsOpSupportedImpl(const InitializedTensorSet& initializers, const Node& node,
WebnnDeviceType device_type, const logging::Logger& logger) const override;
};

// Add operator related.
Expand Down Expand Up @@ -68,30 +64,6 @@ Status ActivationOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder,
return Status::OK();
}

// Operator support related.
bool ActivationOpBuilder::IsOpSupportedImpl(const InitializedTensorSet& /* initializers */,
const Node& node,
WebnnDeviceType device_type,
const logging::Logger& logger) const {
const auto& input_defs = node.InputDefs();
const auto& op_type = node.OpType();

std::vector<int64_t> input_shape;
if (!GetShape(*input_defs[0], input_shape, logger))
return false;

if (op_type == "Elu" && device_type == WebnnDeviceType::CPU) {
NodeAttrHelper helper(node);
float alpha = helper.Get("alpha", 1.0f);
if (alpha != 1.0f) {
LOGS(logger, VERBOSE) << "WebNN CPU backend only supports Elu's alpha == 1.0";
return false;
}
}

return true;
}

void CreateActivationOpBuilder(const std::string& op_type, OpBuilderRegistrations& op_registrations) {
if (op_registrations.op_builder_map.count(op_type) > 0)
return;
Expand Down
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