Download build/webgpu/manifest.json from webgpu-kernels/ai.onnx.BitCast: direct link, hf CLI and curl.
- Browser
- Download file 3.46 kB
-
https://huggingface.co/kernels/webgpu-kernels/ai.onnx.BitCast/resolve/v1/build/webgpu/manifest.json
- Command line
-
hf download hf://webgpu-kernels/ai.onnx.BitCast@v1/build/webgpu/manifest.json
-
curl -L -o manifest.json https://huggingface.co/kernels/webgpu-kernels/ai.onnx.BitCast/resolve/v1/build/webgpu/manifest.json
3.46 kB
| { | |
| "domain": "ai.onnx", | |
| "name": "BitCast", | |
| "sinceVersion": 26, | |
| "inputs": { "input": { "dtype": "T" } }, | |
| "outputs": { "output": { "dtype": "U", "rank": "ranks.input", "shape": "shapes.input" } }, | |
| "attributes": { "to": {} }, | |
| "attributeConstraints": { "to": { "required": true } }, | |
| "typeConstraints": { | |
| "T": ["float32", "int8", "int32", "uint8", "uint32"], | |
| "U": ["float32", "int8", "int32", "uint8", "uint32"] | |
| }, | |
| "tunables": { "WORKGROUP_SIZE": { "default": 256 } }, | |
| "derive": { | |
| "deviceWorkgroupCap": "min(device.limits.maxComputeInvocationsPerWorkgroup, device.limits.maxComputeWorkgroupSizeX)", | |
| "bitcastShapeOk": "ranks.input >= 0 and ranks.output == ranks.input and numel(shapes.input) == numel(shapes.output)", | |
| "bitcastTypeOk": "attrs.to == onnxDtypeCode(logicalDtypes.U) and (((tensorDtypes.input == \"int8\" or tensorDtypes.input == \"uint8\") and (tensorDtypes.output == \"int8\" or tensorDtypes.output == \"uint8\")) or (tensorDtypes.input != \"int8\" and tensorDtypes.input != \"uint8\" and tensorDtypes.output != \"int8\" and tensorDtypes.output != \"uint8\"))", | |
| "bitcastWorkgroupSize": "min(tunables.WORKGROUP_SIZE, deviceWorkgroupCap)", | |
| "bitcastDispatchFits": "ceilDiv(ceilDiv(numel(shapes.output), bitcastWorkgroupSize), min(device.limits.maxComputeWorkgroupsPerDimension, 65535)) <= min(device.limits.maxComputeWorkgroupsPerDimension, 65535)", | |
| "bitcastBaseOk": "bitcastShapeOk and bitcastTypeOk and bitcastDispatchFits", | |
| "inScalar": "dtypes.T", | |
| "outScalar": "dtypes.U", | |
| "inputIsInt8": "tensorDtypes.input == \"int8\"", | |
| "inputIsUint8": "tensorDtypes.input == \"uint8\"", | |
| "outputIsInt8": "tensorDtypes.output == \"int8\"", | |
| "outputIsUint8": "tensorDtypes.output == \"uint8\"" | |
| }, | |
| "when": ["bitcastBaseOk"], | |
| "variants": [ | |
| { | |
| "id": "slot32_vec4", | |
| "priority": 20, | |
| "when": ["numel(shapes.input) % 4 == 0"], | |
| "derive": { "inVec4": "\"vec4<\" ~ dtypes.T ~ \">\"", "outVec4": "\"vec4<\" ~ dtypes.U ~ \">\"" }, | |
| "passes": [ | |
| { | |
| "id": "main", | |
| "name": "BitCast.Vec4", | |
| "shader": "bitcast.wgsl.jinja", | |
| "derive": { "vectorizedSpec": true, "workgroupSizeSpec": "bitcastWorkgroupSize" }, | |
| "bindings": [ | |
| { "arg": "input", "elementType": "$inVec4" }, | |
| { "arg": "output", "elementType": "$outVec4" }, | |
| { "name": "params", "struct": [{ "name": "count", "type": "u32", "value": "numel(shapes.output) / 4" }] } | |
| ], | |
| "dispatch": { | |
| "x": "min(ceilDiv((numel(shapes.output) / 4), (bitcastWorkgroupSize)), 65535)", | |
| "y": "ceilDiv(ceilDiv((numel(shapes.output) / 4), (bitcastWorkgroupSize)), 65535)", | |
| "z": 1 | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "id": "slot32", | |
| "passes": [ | |
| { | |
| "id": "main", | |
| "name": "BitCast", | |
| "shader": "bitcast.wgsl.jinja", | |
| "derive": { "workgroupSizeSpec": "bitcastWorkgroupSize" }, | |
| "bindings": [ | |
| "input", | |
| "output", | |
| { "name": "params", "struct": [{ "name": "count", "type": "u32", "value": "numel(shapes.output)" }] } | |
| ], | |
| "dispatch": { | |
| "x": "min(ceilDiv((numel(shapes.output)), (bitcastWorkgroupSize)), 65535)", | |
| "y": "ceilDiv(ceilDiv((numel(shapes.output)), (bitcastWorkgroupSize)), 65535)", | |
| "z": 1 | |
| } | |
| } | |
| ] | |
| } | |
| ] | |
| } | |