com.microsoft.MoE / build /webgpu /manifest.json
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{
"domain": "com.microsoft",
"name": "MoE",
"sinceVersion": 1,
"inputs": {
"inputT": { "onnx": "input", "dtype": "T" },
"routerT": { "onnx": "router_probs", "dtype": "T", "rank": 2 },
"fc1T": { "onnx": "fc1_experts_weights", "dtype": "T", "rank": 3 },
"fc1BiasT": { "onnx": "fc1_experts_bias", "dtype": "T", "rank": 2, "optional": true },
"fc2T": { "onnx": "fc2_experts_weights", "dtype": "T", "rank": 3 },
"fc2BiasT": { "onnx": "fc2_experts_bias", "dtype": "T", "rank": 2, "optional": true },
"fc3T": { "onnx": "fc3_experts_weights", "dtype": "T", "rank": 3, "optional": true },
"fc3BiasT": { "onnx": "fc3_experts_bias", "dtype": "T", "rank": 2, "optional": true }
},
"outputs": { "outputT": { "onnx": "output", "dtype": "T", "rank": "ranks.inputT", "shape": "shapes.inputT" } },
"attributes": {
"activation_alpha": { "default": 1 },
"activation_beta": { "default": 0 },
"activation_type": { "default": "relu" },
"k": { "default": 1 },
"normalize_routing_weights": { "default": 0 },
"swiglu_fusion": { "default": 0 },
"use_sparse_mixer": { "default": 0 },
"swiglu_limit": {}
},
"attributeConstraints": {
"activation_type": { "values": ["relu", "gelu", "silu", "swiglu", "identity"] },
"normalize_routing_weights": { "values": [0, 1] },
"swiglu_fusion": { "values": [0, 1, 2] },
"use_sparse_mixer": { "values": [0] }
},
"typeConstraints": { "T": ["float32"] },
"tunables": {
"workgroupSize": { "default": 64 },
"decodeLanes": { "default": 32 },
"decodeBlockTarget": { "default": 1024 },
"decodeMinLaneTrips": { "default": 4 },
"groupThreads": { "default": 8 },
"groupRegM": { "default": 4 },
"groupRegN": { "default": 4 },
"groupTileK": { "default": 16 },
"groupRouteWorkgroup": { "default": 256 },
"matrixMinWorkgroups": { "default": 16 }
},
"derive": {
"deviceWorkgroupCap": "min(device.limits.maxComputeInvocationsPerWorkgroup, device.limits.maxComputeWorkgroupSizeX)",
"wave32Adapter": "has(device.adapterInfo, \"subgroupMinSize\") and has(device.adapterInfo, \"subgroupMaxSize\") and device.adapterInfo.subgroupMinSize == 32 and device.adapterInfo.subgroupMaxSize == 32",
"canPinSubgroupSize32": "device.features.has(\"subgroups\") and device.features.has(\"subgroup-size-control\") and has(device.adapterInfo, \"subgroupMinSize\") and has(device.adapterInfo, \"subgroupMaxSize\") and device.adapterInfo.subgroupMinSize <= 32 and device.adapterInfo.subgroupMaxSize >= 32",
"pinSubgroupSize32": "canPinSubgroupSize32 and not wave32Adapter",
"wave32Effective": "wave32Adapter or pinSubgroupSize32",
"topK": "attrs.k",
"hiddenDim": "dim(shapes.inputT, ranks.inputT - 1)",
"tokenCount": "numel(shapes.inputT) / max(1, hiddenDim)",
"expertCount": "dim(shapes.routerT, 1)",
"activationType": "attrs.activation_type",
"isSwiglu": "activationType == \"swiglu\"",
"fusionMode": "attrs.swiglu_fusion",
"fusionSize": "2 if isSwiglu and fusionMode != 0 else 1",
"interSize": "dim(shapes.fc1T, 1) / max(1, fusionSize)",
"fusionOk": "(fusionMode == 0 or fusionMode == 1 or fusionMode == 2) if isSwiglu else fusionMode == 0",
"fc3ShapeOk": "not present.fc3T or (ranks.fc3T == 3 and dim(shapes.fc3T, 0) == expertCount and dim(shapes.fc3T, 1) == interSize and dim(shapes.fc3T, 2) == hiddenDim)",
"fc3PresenceOk": "(present.fc3T if fusionMode == 0 else not present.fc3T) if isSwiglu else (not present.fc3T or activationType == \"silu\")",
"fc1BiasOk": "not present.fc1BiasT or (ranks.fc1BiasT == 2 and dim(shapes.fc1BiasT, 0) == expertCount and dim(shapes.fc1BiasT, 1) == dim(shapes.fc1T, 1))",
"fc2BiasOk": "not present.fc2BiasT or (ranks.fc2BiasT == 2 and dim(shapes.fc2BiasT, 0) == expertCount and dim(shapes.fc2BiasT, 1) == hiddenDim)",
"fc3BiasOk": "not present.fc3BiasT or (present.fc3T and ranks.fc3BiasT == 2 and dim(shapes.fc3BiasT, 0) == expertCount and dim(shapes.fc3BiasT, 1) == interSize)",
"shapeOk": "(ranks.inputT == 2 or ranks.inputT == 3) and ranks.outputT == ranks.inputT and sameShape(shapes.inputT, shapes.outputT) and ranks.routerT == 2 and ranks.fc1T == 3 and ranks.fc2T == 3 and hiddenDim > 0 and interSize > 0 and dim(shapes.routerT, 0) == tokenCount and dim(shapes.fc1T, 0) == expertCount and dim(shapes.fc2T, 0) == expertCount and dim(shapes.fc1T, 2) == hiddenDim and dim(shapes.fc1T, 1) % max(1, fusionSize) == 0 and dim(shapes.fc2T, 1) == hiddenDim and dim(shapes.fc2T, 2) == interSize and topK >= 1 and topK <= expertCount",
"contractOk": "shapeOk and fusionOk and fc3ShapeOk and fc3PresenceOk and fc1BiasOk and fc2BiasOk and fc3BiasOk",
"workgroupSizeOk": "tunables.workgroupSize >= 1 and tunables.workgroupSize <= deviceWorkgroupCap",
"hiddenChunkBytes": "topK * interSize * 4",
"hiddenChunkFits": "hiddenChunkBytes <= device.limits.maxStorageBufferBindingSize and hiddenChunkBytes <= device.limits.maxBufferSize",
"hiddenChunkTokens": "min(tokenCount, max(1, floor(min(device.limits.maxStorageBufferBindingSize, device.limits.maxBufferSize) / max(1, hiddenChunkBytes))))",
"hiddenChunkCount": "max(1, ceilDiv(tokenCount, max(1, hiddenChunkTokens)))",
"routeScratchBytes": "tokenCount * topK * 4",
"routeScratchFits": "routeScratchBytes <= device.limits.maxStorageBufferBindingSize and routeScratchBytes <= device.limits.maxBufferSize",
"splitContract": "contractOk and workgroupSizeOk and hiddenChunkFits and routeScratchFits",
"groupTileM": "tunables.groupThreads * tunables.groupRegM",
"groupTileN": "tunables.groupThreads * tunables.groupRegN",
"groupTileKVec": "ceilDiv(tunables.groupTileK, 4)",
"groupThreadCount": "tunables.groupThreads * tunables.groupThreads",
"groupSlots": "hiddenChunkTokens * topK",
"groupMaxTiles": "ceilDiv(groupSlots, max(1, groupTileM)) + expertCount",
"groupSharedBytes": "(groupTileM * tunables.groupTileK + 2 * groupTileN * tunables.groupTileK + groupTileM) * 4",
"groupedDeviceOk": "groupThreadCount <= device.limits.maxComputeInvocationsPerWorkgroup and tunables.groupThreads <= device.limits.maxComputeWorkgroupSizeX and tunables.groupThreads <= device.limits.maxComputeWorkgroupSizeY and tunables.groupRouteWorkgroup <= deviceWorkgroupCap and groupSharedBytes <= device.limits.maxComputeWorkgroupStorageSize and expertCount * 8 <= device.limits.maxComputeWorkgroupStorageSize and tunables.groupTileK % 4 == 0",
"groupedDispatchOk": "groupMaxTiles <= min(device.limits.maxComputeWorkgroupsPerDimension, 65535) and ceilDiv(interSize, max(1, groupTileN)) <= min(device.limits.maxComputeWorkgroupsPerDimension, 65535) and ceilDiv(hiddenDim, max(1, groupTileN)) <= min(device.limits.maxComputeWorkgroupsPerDimension, 65535)",
"groupedShapeOk": "tokenCount * topK * 4 >= groupTileM * expertCount",
"groupSlotOutBytes": "hiddenChunkTokens * topK * hiddenDim * 4",
"groupSlotOutFits": "groupSlotOutBytes <= device.limits.maxStorageBufferBindingSize and groupSlotOutBytes <= device.limits.maxBufferSize",
"groupedContract": "splitContract and groupedDeviceOk and groupedDispatchOk and groupSlotOutFits and groupedShapeOk",
"decodeLanesOk": "tunables.decodeLanes >= 1 and tunables.decodeLanes <= tunables.workgroupSize and tunables.workgroupSize % tunables.decodeLanes == 0",
"decodeRows": "max(1, tunables.workgroupSize / max(1, tunables.decodeLanes))",
"decodeDeviceOk": "workgroupSizeOk and decodeLanesOk and tunables.decodeLanes <= device.limits.maxComputeWorkgroupSizeX and decodeRows <= device.limits.maxComputeWorkgroupSizeY and tunables.workgroupSize * 8 <= device.limits.maxComputeWorkgroupStorageSize",
"decodeDispatchOk": "ceilDiv(interSize, decodeRows) <= min(device.limits.maxComputeWorkgroupsPerDimension, 65535) and ceilDiv(hiddenDim, decodeRows) <= min(device.limits.maxComputeWorkgroupsPerDimension, 65535) and hiddenChunkTokens * topK <= min(device.limits.maxComputeWorkgroupsPerDimension, 65535)",
"decodeLaneDepth": "min(hiddenDim, interSize) / max(1, tunables.decodeLanes)",
"decodeDepthOk": "decodeLaneDepth >= tunables.decodeMinLaneTrips",
"splitFfnBlocks": "ceilDiv(tokenCount * topK * interSize, max(1, tunables.workgroupSize))",
"decodeOccupancyOk": "splitFfnBlocks <= tunables.decodeBlockTarget",
"decodeContract": "splitContract and decodeDeviceOk and decodeDispatchOk and decodeDepthOk and (decodeOccupancyOk or not groupedContract)",
"groupedVec4Ok": "hiddenDim % 4 == 0 and interSize % 4 == 0",
"hidden": "hiddenDim",
"inter": "interSize",
"fc1Rows": "dim(shapes.fc1T, 1)",
"experts": "expertCount",
"tokens": "tokenCount",
"activation": "activationType",
"swigluFusion": "fusionMode",
"hasSwigluLimit": "has(attrs, \"swiglu_limit\")",
"swigluLimit": "attrs.swiglu_limit if has(attrs, \"swiglu_limit\") else 0",
"hasFc1Bias": "present.fc1BiasT",
"hasFc2Bias": "present.fc2BiasT",
"hasFc3": "present.fc3T",
"hasFc3Bias": "present.fc3BiasT",
"workgroupSize": "tunables.workgroupSize",
"groupedSgmatSharedBytes": "max(groupTileM * 32, 2 * 4 * 4 * 64) * 4",
"groupedSgmatOk": "splitContract and groupSlotOutFits and groupedShapeOk and groupTileM == 32 and groupMaxTiles <= min(device.limits.maxComputeWorkgroupsPerDimension, 65535) and ceilDiv(interSize * (2 if present.fc3T or isSwiglu else 1), 64) <= min(device.limits.maxComputeWorkgroupsPerDimension, 65535) and ceilDiv(hiddenDim, 64) <= min(device.limits.maxComputeWorkgroupsPerDimension, 65535) and deviceWorkgroupCap >= 128 and tunables.groupRouteWorkgroup >= 1 and tunables.groupRouteWorkgroup <= deviceWorkgroupCap and expertCount * 8 <= device.limits.maxComputeWorkgroupStorageSize and groupedSgmatSharedBytes <= device.limits.maxComputeWorkgroupStorageSize and hiddenDim % 64 == 0 and interSize % (32 if present.fc3T or isSwiglu else 64) == 0"
},
"bindings": {
"router_probs": { "arg": "routerT", "buffer": "read-only-storage", "elementType": "f32" },
"route_expert": { "scratch": "routeExpert", "buffer": "storage", "elementType": "u32" },
"route_mix": { "scratch": "routeMix", "buffer": "storage", "elementType": "f32" },
"params": {
"buffer": "uniform",
"struct": [{ "name": "normalizeRoutingWeights", "type": "u32", "value": "attrs.normalize_routing_weights" }]
},
"input": { "arg": "inputT", "buffer": "read-only-storage", "elementType": "f32" },
"route_expert_2": {
"scratch": "routeExpert",
"name": "route_expert",
"buffer": "read-only-storage",
"elementType": "u32"
},
"fc1_experts_weights": { "arg": "fc1T", "buffer": "read-only-storage", "elementType": "f32" },
"hidden_act": { "scratch": "hiddenAct", "buffer": "storage", "elementType": "f32" },
"params_2": {
"name": "params",
"buffer": "uniform",
"struct": [
{ "name": "activationAlpha", "type": "f32", "value": "attrs.activation_alpha" },
{ "name": "activationBeta", "type": "f32", "value": "attrs.activation_beta" },
{ "name": "tokenOffset", "type": "u32", "value": "repeat.chunk * hiddenChunkTokens" },
{
"name": "tokenCount",
"type": "u32",
"value": "min(hiddenChunkTokens, tokenCount - repeat.chunk * hiddenChunkTokens)"
}
]
},
"params_3": {
"name": "params",
"buffer": "uniform",
"struct": [
{ "name": "activationAlpha", "type": "f32", "value": "attrs.activation_alpha" },
{ "name": "activationBeta", "type": "f32", "value": "attrs.activation_beta" },
{ "name": "tokenOffset", "type": "u32", "value": "repeat.chunk * hiddenChunkTokens" }
]
},
"fc3_experts_weights": { "arg": "fc3T", "buffer": "read-only-storage", "elementType": "f32" },
"fc3_experts_bias": { "arg": "fc3BiasT", "buffer": "read-only-storage", "elementType": "f32" },
"fc1_experts_bias": { "arg": "fc1BiasT", "buffer": "read-only-storage", "elementType": "f32" },
"hidden_act_2": {
"scratch": "hiddenAct",
"name": "hidden_act",
"buffer": "read-only-storage",
"elementType": "f32"
},
"route_mix_2": { "scratch": "routeMix", "name": "route_mix", "buffer": "read-only-storage", "elementType": "f32" },
"fc2_experts_weights": { "arg": "fc2T", "buffer": "read-only-storage", "elementType": "f32" },
"output": { "arg": "outputT", "buffer": "storage", "elementType": "f32" },
"params_4": {
"name": "params",
"buffer": "uniform",
"struct": [
{ "name": "tokenOffset", "type": "u32", "value": "repeat.chunk * hiddenChunkTokens" },
{
"name": "tokenCount",
"type": "u32",
"value": "min(hiddenChunkTokens, tokenCount - repeat.chunk * hiddenChunkTokens)"
}
]
},
"params_5": {
"name": "params",
"buffer": "uniform",
"struct": [{ "name": "tokenOffset", "type": "u32", "value": "repeat.chunk * hiddenChunkTokens" }]
},
"fc2_experts_bias": { "arg": "fc2BiasT", "buffer": "read-only-storage", "elementType": "f32" },
"input_2": { "arg": "inputT", "name": "input", "buffer": "read-only-storage", "elementType": "$groupElem" },
"slot_list_2": { "scratch": "slotList", "name": "slot_list", "buffer": "read-only-storage", "elementType": "u32" },
"tile_meta_2": { "scratch": "tileMeta", "name": "tile_meta", "buffer": "read-only-storage", "elementType": "u32" },
"fc1_experts_weights_2": {
"arg": "fc1T",
"name": "fc1_experts_weights",
"buffer": "read-only-storage",
"elementType": "$groupElem"
},
"fc3_experts_weights_2": {
"arg": "fc3T",
"name": "fc3_experts_weights",
"buffer": "read-only-storage",
"elementType": "$groupElem"
},
"hidden_act_3": {
"scratch": "hiddenAct",
"name": "hidden_act",
"buffer": "read-only-storage",
"elementType": "$groupElem"
},
"fc2_experts_weights_2": {
"arg": "fc2T",
"name": "fc2_experts_weights",
"buffer": "read-only-storage",
"elementType": "$groupElem"
},
"slot_out": { "scratch": "slotOut", "buffer": "storage", "elementType": "f32" },
"matrix_params": {
"name": "params",
"buffer": "uniform",
"struct": [{ "name": "tokenOffset", "type": "u32", "value": "repeat.chunk * hiddenChunkTokens" }]
}
},
"variants": [
{
"id": "split_routed_fc1plain_fc3none_fc2plain",
"priority": 10,
"when": ["splitContract", "not present.fc1BiasT", "not present.fc3T", "not present.fc2BiasT"],
"derive": {},
"intermediates": [
{ "id": "routeExpert", "dtype": "uint32", "shape": "[max(1, tokenCount * topK)]" },
{ "id": "routeMix", "dtype": "float32", "shape": "[max(1, tokenCount * topK)]" },
{ "id": "hiddenAct", "dtype": "float32", "shape": "[max(1, hiddenChunkTokens * topK * interSize)]" }
],
"passes": [
{
"id": "route_stage",
"name": "MoE.RouteStage",
"shader": "moe-route-stage.wgsl.jinja",
"bindings": ["router_probs", "route_expert", "route_mix", "params"],
"dispatch": {
"x": "min(ceilDiv((tokenCount), (workgroupSize)), 65535)",
"y": "ceilDiv(ceilDiv((tokenCount), (workgroupSize)), 65535)",
"z": 1
}
},
{
"id": "token_chunks",
"repeat": { "count": "hiddenChunkCount", "index": "chunk" },
"passes": [
{
"id": "ffn_stage",
"name": "MoE.FfnStage",
"shader": "moe-ffn-stage.wgsl.jinja",
"bindings": ["input", "route_expert_2", "fc1_experts_weights", "hidden_act", "params_2"],
"dispatch": {
"x": "min(ceilDiv((min(hiddenChunkTokens, tokenCount - repeat.chunk * hiddenChunkTokens) * topK * interSize), (workgroupSize)), 65535)",
"y": "ceilDiv(ceilDiv((min(hiddenChunkTokens, tokenCount - repeat.chunk * hiddenChunkTokens) * topK * interSize), (workgroupSize)), 65535)",
"z": 1
}
},
{
"id": "output_stage",
"name": "MoE.OutputStage",
"shader": "moe-output-stage.wgsl.jinja",
"bindings": ["hidden_act_2", "route_expert_2", "route_mix_2", "fc2_experts_weights", "output", "params_4"],
"dispatch": {
"x": "min(ceilDiv((min(hiddenChunkTokens, tokenCount - repeat.chunk * hiddenChunkTokens) * hiddenDim), (workgroupSize)), 65535)",
"y": "ceilDiv(ceilDiv((min(hiddenChunkTokens, tokenCount - repeat.chunk * hiddenChunkTokens) * hiddenDim), (workgroupSize)), 65535)",
"z": 1
}
}
]
}
]
},
{
"id": "gemv_routed_fc1plain_fc3none_fc2plain",
"priority": 20,
"when": ["decodeContract", "not present.fc1BiasT", "not present.fc3T", "not present.fc2BiasT"],
"derive": { "decodeLanes": "tunables.decodeLanes" },
"intermediates": [
{ "id": "routeExpert", "dtype": "uint32", "shape": "[max(1, tokenCount * topK)]" },
{ "id": "routeMix", "dtype": "float32", "shape": "[max(1, tokenCount * topK)]" },
{ "id": "hiddenAct", "dtype": "float32", "shape": "[max(1, hiddenChunkTokens * topK * interSize)]" }
],
"passes": [
{
"id": "route_stage",
"name": "MoE.RouteStage",
"shader": "moe-route-stage.wgsl.jinja",
"bindings": ["router_probs", "route_expert", "route_mix", "params"],
"dispatch": {
"x": "min(ceilDiv((tokenCount), (workgroupSize)), 65535)",
"y": "ceilDiv(ceilDiv((tokenCount), (workgroupSize)), 65535)",
"z": 1
}
},
{
"id": "token_chunks",
"repeat": { "count": "hiddenChunkCount", "index": "chunk" },
"passes": [
{
"id": "ffn_stage",
"name": "MoE.FfnStage",
"shader": "moe-ffn-gemv.wgsl.jinja",
"bindings": ["input", "route_expert_2", "fc1_experts_weights", "hidden_act", "params_3"],
"dispatch": {
"x": "ceilDiv(interSize, decodeRows)",
"y": "min(hiddenChunkTokens, tokenCount - repeat.chunk * hiddenChunkTokens) * topK"
}
},
{
"id": "output_stage",
"name": "MoE.OutputStage",
"shader": "moe-output-gemv.wgsl.jinja",
"bindings": ["hidden_act_2", "route_expert_2", "route_mix_2", "fc2_experts_weights", "output", "params_5"],
"dispatch": {
"x": "ceilDiv(hiddenDim, decodeRows)",
"y": "min(hiddenChunkTokens, tokenCount - repeat.chunk * hiddenChunkTokens)"
}
}
]
}
]
},
{
"id": "split_routed_fc1plain_fc3none_fc2bias",
"priority": 10,
"when": ["splitContract", "not present.fc1BiasT", "not present.fc3T", "present.fc2BiasT"],
"derive": {},
"intermediates": [
{ "id": "routeExpert", "dtype": "uint32", "shape": "[max(1, tokenCount * topK)]" },
{ "id": "routeMix", "dtype": "float32", "shape": "[max(1, tokenCount * topK)]" },
{ "id": "hiddenAct", "dtype": "float32", "shape": "[max(1, hiddenChunkTokens * topK * interSize)]" }
],
"passes": [
{
"id": "route_stage",
"name": "MoE.RouteStage",
"shader": "moe-route-stage.wgsl.jinja",
"bindings": ["router_probs", "route_expert", "route_mix", "params"],
"dispatch": {
"x": "min(ceilDiv((tokenCount), (workgroupSize)), 65535)",
"y": "ceilDiv(ceilDiv((tokenCount), (workgroupSize)), 65535)",
"z": 1
}
},
{
"id": "token_chunks",
"repeat": { "count": "hiddenChunkCount", "index": "chunk" },
"passes": [
{
"id": "ffn_stage",
"name": "MoE.FfnStage",
"shader": "moe-ffn-stage.wgsl.jinja",
"bindings": ["input", "route_expert_2", "fc1_experts_weights", "hidden_act", "params_2"],
"dispatch": {
"x": "min(ceilDiv((min(hiddenChunkTokens, tokenCount - repeat.chunk * hiddenChunkTokens) * topK * interSize), (workgroupSize)), 65535)",
"y": "ceilDiv(ceilDiv((min(hiddenChunkTokens, tokenCount - repeat.chunk * hiddenChunkTokens) * topK * interSize), (workgroupSize)), 65535)",
"z": 1
}
},
{
"id": "output_stage",
"name": "MoE.OutputStage",
"shader": "moe-output-stage.wgsl.jinja",
"bindings": ["hidden_act_2", "route_expert_2", "route_mix_2", "fc2_experts_weights", "fc2_experts_bias", "output", "params_4"],
"dispatch": {
"x": "min(ceilDiv((min(hiddenChunkTokens, tokenCount - repeat.chunk * hiddenChunkTokens) * hiddenDim), (workgroupSize)), 65535)",
"y": "ceilDiv(ceilDiv((min(hiddenChunkTokens, tokenCount - repeat.chunk * hiddenChunkTokens) * hiddenDim), (workgroupSize)), 65535)",
"z": 1
}
}
]
}
]
},
{
"id": "gemv_routed_fc1plain_fc3none_fc2bias",
"priority": 20,
"when": ["decodeContract", "not present.fc1BiasT", "not present.fc3T", "present.fc2BiasT"],
"derive": { "decodeLanes": "tunables.decodeLanes" },
"intermediates": [
{ "id": "routeExpert", "dtype": "uint32", "shape": "[max(1, tokenCount * topK)]" },
{ "id": "routeMix", "dtype": "float32", "shape": "[max(1, tokenCount * topK)]" },
{ "id": "hiddenAct", "dtype": "float32", "shape": "[max(1, hiddenChunkTokens * topK * interSize)]" }
],
"passes": [
{
"id": "route_stage",
"name": "MoE.RouteStage",
"shader": "moe-route-stage.wgsl.jinja",
"bindings": ["router_probs", "route_expert", "route_mix", "params"],
"dispatch": {
"x": "min(ceilDiv((tokenCount), (workgroupSize)), 65535)",
"y": "ceilDiv(ceilDiv((tokenCount), (workgroupSize)), 65535)",
"z": 1
}
},
{
"id": "token_chunks",
"repeat": { "count": "hiddenChunkCount", "index": "chunk" },
"passes": [
{
"id": "ffn_stage",
"name": "MoE.FfnStage",
"shader": "moe-ffn-gemv.wgsl.jinja",
"bindings": ["input", "route_expert_2", "fc1_experts_weights", "hidden_act", "params_3"],
"dispatch": {
"x": "ceilDiv(interSize, decodeRows)",
"y": "min(hiddenChunkTokens, tokenCount - repeat.chunk * hiddenChunkTokens) * topK"
}
},
{
"id": "output_stage",
"name": "MoE.OutputStage",
"shader": "moe-output-gemv.wgsl.jinja",
"bindings": ["hidden_act_2", "route_expert_2", "route_mix_2", "fc2_experts_weights", "fc2_experts_bias", "output", "params_5"],
"dispatch": {
"x": "ceilDiv(hiddenDim, decodeRows)",
"y": "min(hiddenChunkTokens, tokenCount - repeat.chunk * hiddenChunkTokens)"
}
}
]
}
]
},
{
"id": "split_routed_fc1plain_fc3plain_fc2plain",
"priority": 10,
"when": ["splitContract", "not present.fc1BiasT", "present.fc3T and not present.fc3BiasT", "not present.fc2BiasT"],
"derive": {},
"intermediates": [
{ "id": "routeExpert", "dtype": "uint32", "shape": "[max(1, tokenCount * topK)]" },
{ "id": "routeMix", "dtype": "float32", "shape": "[max(1, tokenCount * topK)]" },
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},
{
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},
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}
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{
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},
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},
{
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{ "scratch": "slotOut", "name": "slot_out", "buffer": "read-only-storage", "elementType": "f32" },
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],
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}
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]
}
]
}
]
}