Download build/webgpu/manifest.json from webgpu-kernels/ai.onnx.IsInf: direct link, hf CLI and curl.
- Browser
- Download file 3.78 kB
-
https://huggingface.co/kernels/webgpu-kernels/ai.onnx.IsInf/resolve/v1/build/webgpu/manifest.json
- Command line
-
hf download hf://webgpu-kernels/ai.onnx.IsInf@v1/build/webgpu/manifest.json
-
curl -L -o manifest.json https://huggingface.co/kernels/webgpu-kernels/ai.onnx.IsInf/resolve/v1/build/webgpu/manifest.json
3.78 kB
| { | |
| "domain": "ai.onnx", | |
| "name": "IsInf", | |
| "sinceVersion": 20, | |
| "inputs": { "x": { "onnx": "X", "dtype": "T" } }, | |
| "outputs": { "y": { "onnx": "Y", "dtype": "B", "rank": "ranks.x", "shape": "shapes.x" } }, | |
| "attributes": { "detect_negative": { "default": 1 }, "detect_positive": { "default": 1 } }, | |
| "attributeConstraints": { "detect_negative": { "values": [0, 1] }, "detect_positive": { "values": [0, 1] } }, | |
| "typeConstraints": { "T": ["float32", "float16"], "B": ["bool"] }, | |
| "tunables": { "WORKGROUP_SIZE": { "default": 256 } }, | |
| "derive": { "scalar": "dtypes.T" }, | |
| "when": ["numel(shapes.x) == numel(shapes.y)", "ranks.y == ranks.x"], | |
| "bindings": { "y": { "elementType": "u32" } }, | |
| "variants": [ | |
| { | |
| "id": "detect_neither", | |
| "priority": 30, | |
| "when": ["attrs.detect_negative == 0", "attrs.detect_positive == 0"], | |
| "passes": [ | |
| { | |
| "id": "main", | |
| "name": "IsInf.DetectNeither", | |
| "shader": "detect-neither.wgsl.jinja", | |
| "bindings": [ | |
| "y", | |
| { "name": "params", "struct": [{ "name": "count", "type": "u32", "value": "numel(shapes.y)" }] } | |
| ], | |
| "dispatch": { | |
| "x": "min(ceilDiv((ceilDiv(numel(shapes.y), 4)), (tunables.WORKGROUP_SIZE)), 65535)", | |
| "y": "ceilDiv(ceilDiv((ceilDiv(numel(shapes.y), 4)), (tunables.WORKGROUP_SIZE)), 65535)", | |
| "z": 1 | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "id": "same_layout_vec4", | |
| "priority": 20, | |
| "when": ["attrs.detect_negative == 1 or attrs.detect_positive == 1", "numel(shapes.x) > 0", "numel(shapes.x) % 4 == 0", "f16Ok(dtypes.T)"], | |
| "derive": { "vectorScalar": "\"vec4<\" ~ dtypes.T ~ \">\"", "outVec": "\"vec4<\" ~ dtypes.B ~ \">\"" }, | |
| "passes": [ | |
| { | |
| "id": "main", | |
| "name": "IsInf.Vec4", | |
| "shader": "unary-vec4.wgsl.jinja", | |
| "derive": { | |
| "detectNegative": "attrs.detect_negative", | |
| "detectPositive": "attrs.detect_positive", | |
| "vec4PerThread": "4 if numel(shapes.y) * dtypeBytes(tensorDtypes.y) <= 16777216 else 1" | |
| }, | |
| "bindings": [ | |
| { "arg": "x", "elementType": "$vectorScalar" }, | |
| { "arg": "y", "elementType": "$outVec" }, | |
| { "name": "params", "struct": [{ "name": "count", "type": "u32", "value": "numel(shapes.y) / 4" }] } | |
| ], | |
| "dispatch": { | |
| "x": "min(ceilDiv((ceilDiv(numel(shapes.y) / 4, 4 if numel(shapes.y) * dtypeBytes(tensorDtypes.y) <= 16777216 else 1)), (tunables.WORKGROUP_SIZE)), 65535)", | |
| "y": "ceilDiv(ceilDiv((ceilDiv(numel(shapes.y) / 4, 4 if numel(shapes.y) * dtypeBytes(tensorDtypes.y) <= 16777216 else 1)), (tunables.WORKGROUP_SIZE)), 65535)", | |
| "z": 1 | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "id": "elementwise", | |
| "when": ["f16Ok(dtypes.T)"], | |
| "passes": [ | |
| { | |
| "id": "main", | |
| "name": "IsInf", | |
| "shader": "unary-scalar.wgsl.jinja", | |
| "derive": { "itemsPerInvocation": 4 }, | |
| "bindings": [ | |
| "x", | |
| "y", | |
| { | |
| "name": "params", | |
| "struct": [ | |
| { "name": "count", "type": "u32", "value": "numel(shapes.y)" }, | |
| { "name": "detectNegative", "type": "u32", "value": "attrs.detect_negative" }, | |
| { "name": "detectPositive", "type": "u32", "value": "attrs.detect_positive" } | |
| ] | |
| } | |
| ], | |
| "dispatch": { | |
| "x": "min(ceilDiv((ceilDiv(numel(shapes.y), 4)), (tunables.WORKGROUP_SIZE)), 65535)", | |
| "y": "ceilDiv(ceilDiv((ceilDiv(numel(shapes.y), 4)), (tunables.WORKGROUP_SIZE)), 65535)", | |
| "z": 1 | |
| } | |
| } | |
| ] | |
| } | |
| ] | |
| } | |