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"domain": "com.microsoft",
"name": "GatherBlockQuantized",
"sinceVersion": 1,
"inputs": {
"dataT": { "onnx": "data", "dtype": "T1", "rank": 2 },
"indicesT": { "onnx": "indices", "dtype": "Tind", "rank": 1, "storage": "uint32", "narrowing": "checked" },
"scalesT": { "onnx": "scales", "dtype": "T2", "rank": 2 },
"zeroPointsT": { "onnx": "zero_points", "dtype": "T1", "rank": 2, "optional": true }
},
"outputs": {
"outputT": {
"onnx": "output",
"dtype": "T2",
"rank": 2,
"shape": "[dim(shapes.indicesT, 0), dim(shapes.dataT, 1) * (8 / attrs.bits)]"
}
},
"attributes": {
"bits": { "default": 4 },
"block_size": { "default": 128 },
"gather_axis": { "default": 0 },
"quantize_axis": { "default": 1 }
},
"attributeConstraints": {
"bits": { "values": [4, 8] },
"gather_axis": { "values": [0] },
"quantize_axis": { "values": [1] }
},
"typeConstraints": { "T1": ["uint8"], "T2": ["float32"], "Tind": ["int64"] },
"tunables": { "WORKGROUP_SIZE": { "default": 64 } },
"derive": {
"deviceWorkgroupCap": "min(device.limits.maxComputeInvocationsPerWorkgroup, device.limits.maxComputeWorkgroupSizeX)",
"bits": "attrs.bits",
"blockSize": "attrs.block_size",
"blockSizeOk": "blockSize >= 16 and pow2ceil(blockSize) == blockSize",
"outBlocks": "ceilDiv(dim(shapes.outputT, 1), blockSize)",
"zeroPointCols": "ceilDiv(outBlocks, 2) if bits == 4 else outBlocks",
"workgroupSize": "min(tunables.WORKGROUP_SIZE, deviceWorkgroupCap)",
"commonShapeValid": "blockSizeOk and ranks.dataT == 2 and ranks.indicesT == 1 and ranks.scalesT == 2 and ranks.outputT == 2 and tensorDtypes.indicesT == \"uint32\" and tensorDtypes.scalesT == \"float32\" and tensorDtypes.outputT == \"float32\" and dim(shapes.outputT, 0) == dim(shapes.indicesT, 0) and dim(shapes.scalesT, 0) == dim(shapes.dataT, 0) and dim(shapes.scalesT, 1) == outBlocks",
"q4ShapeValid": "commonShapeValid and tensorDtypes.dataT == \"uint8\" and dim(shapes.outputT, 1) == dim(shapes.dataT, 1) * 2",
"q8ShapeValid": "commonShapeValid and tensorDtypes.dataT == \"uint8\" and dim(shapes.outputT, 1) == dim(shapes.dataT, 1)",
"zeroPointsValid": "present.zeroPointsT and ranks.zeroPointsT == 2 and tensorDtypes.zeroPointsT == \"uint8\" and dim(shapes.zeroPointsT, 0) == dim(shapes.dataT, 0) and dim(shapes.zeroPointsT, 1) == zeroPointCols",
"noZeroMode": "not present.zeroPointsT",
"zeroMode": "zeroPointsValid",
"hasZero": "zeroMode",
"indexScalar": "\"u32\"",
"scaleScalar": "\"f32\"",
"zeroPointElement": "\"u32\"",
"workgroupFits": "workgroupSize > 0",
"foldedDispatchFits": "ceil(ceil(numel(shapes.outputT) / min(device.limits.maxComputeWorkgroupsPerDimension, 65535)) / workgroupSize) <= min(device.limits.maxComputeWorkgroupsPerDimension, 65535)"
},
"when": ["foldedDispatchFits", "workgroupFits"],
"bindings": {
"data": { "arg": "dataT", "elementType": "$dataElement" },
"indices": { "arg": "indicesT", "elementType": "$indexScalar" },
"scales": { "arg": "scalesT", "elementType": "$scaleScalar" },
"output": { "arg": "outputT", "elementType": "$outputElement" },
"params": {
"struct": [
{ "name": "indexCount", "type": "u32", "value": "dim(shapes.indicesT, 0)" },
{ "name": "cols", "type": "u32", "value": "dim(shapes.outputT, 1)" },
{ "name": "blocks", "type": "u32", "value": "dim(shapes.scalesT, 1)" },
{ "name": "blockSize", "type": "u32", "value": "blockSize" },
{ "name": "rows", "type": "u32", "value": "dim(shapes.dataT, 0)" }
]
},
"params_main": {
"name": "params",
"struct": [
{ "name": "indexCount", "type": "u32", "value": "dim(shapes.indicesT, 0)" },
{ "name": "packedCols", "type": "u32", "value": "dim(shapes.dataT, 1)" },
{ "name": "blocks", "type": "u32", "value": "dim(shapes.scalesT, 1)" },
{ "name": "blockSize", "type": "u32", "value": "blockSize" },
{ "name": "rows", "type": "u32", "value": "dim(shapes.dataT, 0)" }
]
},
"zero_points": { "arg": "zeroPointsT", "elementType": "$zeroPointElement" },
"params__uniform": {
"name": "params",
"struct": [
{ "name": "indexCount", "type": "u32", "value": "dim(shapes.indicesT, 0)" },
{ "name": "packedCols", "type": "u32", "value": "dim(shapes.dataT, 1)" },
{ "name": "blocks", "type": "u32", "value": "dim(shapes.scalesT, 1)" },
{ "name": "zeroPointCols", "type": "u32", "value": "zeroPointCols" },
{ "name": "blockSize", "type": "u32", "value": "blockSize" },
{ "name": "rows", "type": "u32", "value": "dim(shapes.dataT, 0)" }
]
},
"params_q8_zero_tail4": {
"name": "params",
"struct": [
{ "name": "indexCount", "type": "u32", "value": "dim(shapes.indicesT, 0)" },
{ "name": "cols", "type": "u32", "value": "dim(shapes.outputT, 1)" },
{ "name": "packedCols", "type": "u32", "value": "dim(shapes.dataT, 1)" },
{ "name": "blocks", "type": "u32", "value": "dim(shapes.scalesT, 1)" },
{ "name": "blockSize", "type": "u32", "value": "blockSize" },
{ "name": "rows", "type": "u32", "value": "dim(shapes.dataT, 0)" }
]
}
},
"variants": [
{
"id": "q8_no_zero_vec4",
"priority": 10,
"when": ["q8ShapeValid", "noZeroMode", "bits == 8", "blockSize % 4 == 0", "dim(shapes.outputT, 1) % 4 == 0"],
"derive": { "scalarTail": false, "dataElement": "\"vec4<u32>\"", "outputElement": "\"vec4<f32>\"" },
"passes": [
{
"id": "main",
"shader": "gather-block-quantized-q8-vec4.wgsl.jinja",
"bindings": ["data", "indices", "scales", "output", "params"],
"dispatch": {
"x": "min(ceilDiv((dim(shapes.indicesT, 0) * (dim(shapes.outputT, 1) / 4)), (workgroupSize)), 65535)",
"y": "ceilDiv(ceilDiv((dim(shapes.indicesT, 0) * (dim(shapes.outputT, 1) / 4)), (workgroupSize)), 65535)",
"z": 1
}
}
]
},
{
"id": "q8_zero_vec4",
"priority": 10,
"when": ["q8ShapeValid", "zeroMode", "bits == 8", "blockSize % 4 == 0", "dim(shapes.outputT, 1) % 4 == 0"],
"derive": { "scalarTail": false, "dataElement": "\"vec4<u32>\"", "outputElement": "\"vec4<f32>\"" },
"passes": [
{
"id": "main",
"shader": "gather-block-quantized-q8-vec4.wgsl.jinja",
"bindings": ["data", "indices", "scales", "zero_points", "output", "params"],
"dispatch": {
"x": "min(ceilDiv((dim(shapes.indicesT, 0) * (dim(shapes.outputT, 1) / 4)), (workgroupSize)), 65535)",
"y": "ceilDiv(ceilDiv((dim(shapes.indicesT, 0) * (dim(shapes.outputT, 1) / 4)), (workgroupSize)), 65535)",
"z": 1
}
}
]
},
{
"id": "q4_no_zero_pair",
"priority": 10,
"when": ["q4ShapeValid", "noZeroMode", "bits == 4"],
"derive": { "dataElement": "\"u32\"", "outputElement": "\"vec2<f32>\"" },
"passes": [
{
"id": "main",
"shader": "gather-block-quantized-q4-pair.wgsl.jinja",
"bindings": ["data", "indices", "scales", "output", "params_main"],
"dispatch": {
"x": "min(ceilDiv((dim(shapes.indicesT, 0) * dim(shapes.dataT, 1)), (workgroupSize)), 65535)",
"y": "ceilDiv(ceilDiv((dim(shapes.indicesT, 0) * dim(shapes.dataT, 1)), (workgroupSize)), 65535)",
"z": 1
}
}
]
},
{
"id": "q4_zero_pair",
"priority": 10,
"when": ["q4ShapeValid", "zeroMode", "bits == 4"],
"derive": { "dataElement": "\"u32\"", "outputElement": "\"vec2<f32>\"" },
"passes": [
{
"id": "main",
"shader": "gather-block-quantized-q4-pair.wgsl.jinja",
"bindings": ["data", "indices", "scales", "zero_points", "output", "params__uniform"],
"dispatch": {
"x": "min(ceilDiv((dim(shapes.indicesT, 0) * dim(shapes.dataT, 1)), (workgroupSize)), 65535)",
"y": "ceilDiv(ceilDiv((dim(shapes.indicesT, 0) * dim(shapes.dataT, 1)), (workgroupSize)), 65535)",
"z": 1
}
}
]
},
{
"id": "q8_no_zero_tail4",
"priority": 5,
"when": ["q8ShapeValid", "noZeroMode", "bits == 8"],
"derive": { "scalarTail": true, "dataElement": "\"u32\"", "outputElement": "\"f32\"" },
"passes": [
{
"id": "main",
"shader": "gather-block-quantized-q8-vec4.wgsl.jinja",
"bindings": ["data", "indices", "scales", "output", "params_q8_zero_tail4"],
"dispatch": {
"x": "min(ceilDiv((dim(shapes.indicesT, 0) * ceilDiv(dim(shapes.outputT, 1), 4)), (workgroupSize)), 65535)",
"y": "ceilDiv(ceilDiv((dim(shapes.indicesT, 0) * ceilDiv(dim(shapes.outputT, 1), 4)), (workgroupSize)), 65535)",
"z": 1
}
}
]
},
{
"id": "q8_zero_tail4",
"priority": 5,
"when": ["q8ShapeValid", "zeroMode", "bits == 8"],
"derive": { "scalarTail": true, "dataElement": "\"u32\"", "outputElement": "\"f32\"" },
"passes": [
{
"id": "main",
"shader": "gather-block-quantized-q8-vec4.wgsl.jinja",
"bindings": ["data", "indices", "scales", "zero_points", "output", "params_q8_zero_tail4"],
"dispatch": {
"x": "min(ceilDiv((dim(shapes.indicesT, 0) * ceilDiv(dim(shapes.outputT, 1), 4)), (workgroupSize)), 65535)",
"y": "ceilDiv(ceilDiv((dim(shapes.indicesT, 0) * ceilDiv(dim(shapes.outputT, 1), 4)), (workgroupSize)), 65535)",
"z": 1
}
}
]
}
]
}
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