Download build/webgpu/manifest.json from webgpu-kernels/ai.onnx.Sign: direct link, hf CLI and curl.
- Browser
- Download file 2.51 kB
-
https://huggingface.co/kernels/webgpu-kernels/ai.onnx.Sign/resolve/v1/build/webgpu/manifest.json
- Command line
-
hf download hf://webgpu-kernels/ai.onnx.Sign@v1/build/webgpu/manifest.json
-
curl -L -o manifest.json https://huggingface.co/kernels/webgpu-kernels/ai.onnx.Sign/resolve/v1/build/webgpu/manifest.json
2.51 kB
| { | |
| "domain": "ai.onnx", | |
| "name": "Sign", | |
| "sinceVersion": 13, | |
| "inputs": { "input": { "dtype": "T" } }, | |
| "outputs": { "output": { "dtype": "T", "rank": "ranks.input", "shape": "shapes.input" } }, | |
| "typeConstraints": { "T": ["float32", "float16", "int32", "uint32", "int16", "int8", "uint8"] }, | |
| "tunables": { "WORKGROUP_SIZE": { "default": 256 } }, | |
| "derive": { "scalar": "dtypes.T" }, | |
| "variants": [ | |
| { | |
| "id": "same_layout_vec4", | |
| "priority": 20, | |
| "when": ["numel(shapes.input) > 0", "numel(shapes.input) % 4 == 0", "numel(shapes.input) == numel(shapes.output)", "f16Ok(dtypes.T)"], | |
| "passes": [ | |
| { | |
| "id": "main", | |
| "name": "Sign.Vec4", | |
| "shader": "unary-vec4.wgsl.jinja", | |
| "derive": { | |
| "vectorScalar": "\"vec4<\" ~ dtypes.T ~ \">\"", | |
| "vec4PerThread": "4 if numel(shapes.output) * dtypeBytes(tensorDtypes.output) <= 16777216 else 1" | |
| }, | |
| "bindings": [ | |
| { "arg": "input", "name": "x", "elementType": "$vectorScalar" }, | |
| { "arg": "output", "name": "y", "elementType": "$vectorScalar" }, | |
| { "name": "params", "struct": [{ "name": "count", "type": "u32", "value": "numel(shapes.output) / 4" }] } | |
| ], | |
| "dispatch": { | |
| "x": "min(ceilDiv((ceilDiv(numel(shapes.output) / 4, 4 if numel(shapes.output) * dtypeBytes(tensorDtypes.output) <= 16777216 else 1)), (tunables.WORKGROUP_SIZE)), 65535)", | |
| "y": "ceilDiv(ceilDiv((ceilDiv(numel(shapes.output) / 4, 4 if numel(shapes.output) * dtypeBytes(tensorDtypes.output) <= 16777216 else 1)), (tunables.WORKGROUP_SIZE)), 65535)", | |
| "z": 1 | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "id": "elementwise", | |
| "when": ["numel(shapes.input) == numel(shapes.output) and (f16Ok(dtypes.T))"], | |
| "passes": [ | |
| { | |
| "id": "main", | |
| "name": "Sign", | |
| "shader": "unary-scalar.wgsl.jinja", | |
| "derive": { "itemsPerInvocation": 4 }, | |
| "bindings": [ | |
| "input", | |
| "output", | |
| { "name": "params", "struct": [{ "name": "count", "type": "u32", "value": "numel(shapes.output)" }] } | |
| ], | |
| "dispatch": { | |
| "x": "min(ceilDiv((ceilDiv(numel(shapes.output), 4)), (tunables.WORKGROUP_SIZE)), 65535)", | |
| "y": "ceilDiv(ceilDiv((ceilDiv(numel(shapes.output), 4)), (tunables.WORKGROUP_SIZE)), 65535)", | |
| "z": 1 | |
| } | |
| } | |
| ] | |
| } | |
| ], | |
| "bindings": {} | |
| } | |