{
  "domain": "com.microsoft",
  "name": "MatMulNBitsMlp",
  "sinceVersion": 1,
  "description": "Fuses a gated MLP over two block-quantized projections that share one activation: `Y = silu(A_norm @ gate + gate_bias) * (A_norm @ up + up_bias)`, using the `MatMulNBits` weight packing with no zero-point input. `A_norm` is `A`, `SimplifiedLayerNormalization(A, norm_scale)`, or `SkipSimplifiedLayerNormalization(A, skip, norm_scale)`, whose residual sum may be returned as a second output. Only `silu` and the default `accuracy_level = 0` are implemented; bfloat16 is not implemented.",
  "inputs": [
    {
      "role": "A",
      "dtype": "T1",
      "description": "Shared activation of rank 2 `(M, K)` or rank 3 `(batch, sequence, K)`; only the last axis is the reduction axis."
    },
    {
      "role": "skip",
      "dtype": "T1",
      "optional": true,
      "description": "Residual added to `A` before normalization, with `A`'s shape. Requires `norm_scale`."
    },
    {
      "role": "norm_scale",
      "dtype": "T1",
      "rank": 1,
      "optional": true,
      "description": "Simplified-layer-normalization (RMS) gain of shape `[K]`. Absent means the projections read `A` unnormalized."
    },
    {
      "role": "gate_B",
      "dtype": "uint8",
      "rank": 3,
      "description": "Bit-packed uint8 gate weights of shape `(N, k_blocks, blob_size)`."
    },
    {
      "role": "gate_scales",
      "dtype": "T1",
      "rank": 2,
      "description": "Per-block gate scales of shape `(N, k_blocks)`, with the same dtype as `A`. Quantization is symmetric: this operator has no zero-point input, so codes are offset by the midpoint `2^(bits - 1)`."
    },
    {
      "role": "gate_bias",
      "dtype": "T1",
      "rank": 1,
      "optional": true,
      "description": "Optional gate bias of shape `[N]`, added before the activation."
    },
    {
      "role": "up_B",
      "dtype": "uint8",
      "rank": 3,
      "description": "Bit-packed up weights, same shape and packing as gate_B."
    },
    { "role": "up_scales", "dtype": "T1", "rank": 2, "description": "Per-block up scales of shape `(N, k_blocks)`." },
    {
      "role": "up_bias",
      "dtype": "T1",
      "rank": 1,
      "optional": true,
      "description": "Optional up bias of shape `[N]`, added before the product."
    }
  ],
  "outputs": [
    {
      "role": "Y",
      "dtype": "T1",
      "rank": "ranks.aT",
      "shape": "shapes.aT[:-1] + [attrs.N]",
      "description": "Gated MLP output: A's leading axes with a trailing N."
    },
    {
      "role": "input_skip_bias_sum",
      "dtype": "T1",
      "rank": "ranks.aT",
      "optional": true,
      "shape": "shapes.aT",
      "description": "The residual sum A + skip, with A's shape. Requires the skip input."
    }
  ],
  "attributes": { "accuracy_level": 0, "bits": 4, "epsilon": 0.00001 },
  "attributeDescriptions": {
    "K": "Input feature dimension shared by both quantized weight matrices.",
    "N": "Output feature dimension shared by both quantized weight matrices.",
    "accuracy_level": "Minimum internal accuracy level: 0 (unset), 1 (float32), 2 (float16), 3 (bfloat16), or 4 (int8).",
    "activation": "Activation applied to the gate projection; this implementation supports `silu`.",
    "bits": "Bit width used to quantize both weight matrices; this implementation supports 2, 4, and 8.",
    "block_size": "Size of each quantization block along K.",
    "epsilon": "Epsilon used by the optional fused RMS normalization."
  },
  "attributeConstraints": {
    "K": { "required": true },
    "N": { "required": true },
    "accuracy_level": { "values": [0] },
    "activation": { "required": true, "values": ["silu"] },
    "bits": { "values": [2, 4, 8] },
    "block_size": { "required": true }
  },
  "typeConstraints": { "T1": ["float32", "float16"] },
  "args": {
    "aT": { "kind": "tensor", "semantic": "A", "role": "input" },
    "skipT": { "kind": "tensor", "semantic": "skip", "role": "input", "required": false },
    "normScaleT": { "kind": "tensor", "semantic": "norm_scale", "role": "weights", "required": false },
    "gateBT": { "kind": "tensor", "semantic": "gate_B", "role": "weights" },
    "gateScalesT": { "kind": "tensor", "semantic": "gate_scales", "role": "weights" },
    "gateBiasT": { "kind": "tensor", "semantic": "gate_bias", "role": "weights", "required": false },
    "upBT": { "kind": "tensor", "semantic": "up_B", "role": "weights" },
    "upScalesT": { "kind": "tensor", "semantic": "up_scales", "role": "weights" },
    "upBiasT": { "kind": "tensor", "semantic": "up_bias", "role": "weights", "required": false },
    "yT": { "kind": "tensor", "semantic": "Y", "role": "output" },
    "residualT": { "kind": "tensor", "semantic": "input_skip_bias_sum", "role": "output", "required": false }
  },
  "tunables": { "TILE_N": 8, "LANES": 8, "NORM_WORKGROUP_SIZE": 128, "ROW_TILE": 8 },
  "derive": {
    "aRows": "numel(shapes.aT) / max(1, attrs.K)",
    "rowTile": "1 if aRows <= 1 else min(aRows, tunables.ROW_TILE)",
    "rowGroups": "ceilDiv(aRows, rowTile)",
    "kBlocks": "dim(shapes.gateBT, 1)",
    "blobSize": "dim(shapes.gateBT, 2)",
    "codesPerByte": "8 / attrs.bits",
    "codeMask": "3 if attrs.bits == 2 else (15 if attrs.bits == 4 else 255)",
    "epsilonValue": "attrs.epsilon",
    "bitsSupported": "attrs.bits == 2 or attrs.bits == 4 or attrs.bits == 8",
    "weightShapeOk": "ranks.gateBT == 3 and ranks.upBT == 3 and dim(shapes.gateBT, 0) == attrs.N and dim(shapes.upBT, 0) == attrs.N and dim(shapes.upBT, 1) == kBlocks and dim(shapes.upBT, 2) == blobSize and kBlocks == ceilDiv(attrs.K, attrs.block_size) and blobSize * 8 == attrs.block_size * attrs.bits",
    "scaleShapeOk": "ranks.gateScalesT == 2 and ranks.upScalesT == 2 and dim(shapes.gateScalesT, 0) == attrs.N and dim(shapes.gateScalesT, 1) == kBlocks and dim(shapes.upScalesT, 0) == attrs.N and dim(shapes.upScalesT, 1) == kBlocks",
    "ioShapeOk": "(ranks.aT == 2 or ranks.aT == 3) and dim(shapes.aT, ranks.aT - 1) == attrs.K and ranks.yT == ranks.aT and dim(shapes.yT, ranks.yT - 1) == attrs.N and sameShape(prefix(shapes.yT, ranks.yT - 1), prefix(shapes.aT, ranks.aT - 1))",
    "biasShapeOk": "(ranks.gateBiasT == 1 and dim(shapes.gateBiasT, 0) == attrs.N if present.gateBiasT else true) and (ranks.upBiasT == 1 and dim(shapes.upBiasT, 0) == attrs.N if present.upBiasT else true)",
    "dtypeOk": "tensorDtypes.gateScalesT == tensorDtypes.aT and tensorDtypes.upScalesT == tensorDtypes.aT and tensorDtypes.yT == tensorDtypes.aT and f16Ok(tensorDtypes.aT)",
    "lanesPow2": "tunables.LANES == pow2ceil(tunables.LANES)",
    "mlpShapeOk": "bitsSupported and weightShapeOk and scaleShapeOk and ioShapeOk and biasShapeOk and dtypeOk and lanesPow2 and attrs.K > 0 and attrs.N > 0 and attrs.block_size > 0",
    "normContractOk": "present.normScaleT and ranks.normScaleT == 1 and dim(shapes.normScaleT, 0) == attrs.K and tensorDtypes.normScaleT == tensorDtypes.aT and (sameShape(shapes.skipT, shapes.aT) and tensorDtypes.skipT == tensorDtypes.aT if present.skipT else true) and (sameShape(shapes.residualT, shapes.aT) and tensorDtypes.residualT == tensorDtypes.aT and present.skipT if present.residualT else true)",
    "gateUpDispatchFits": "ceilDiv(attrs.N, tunables.TILE_N) <= device.limits.maxComputeWorkgroupsPerDimension and aRows <= device.limits.maxComputeWorkgroupsPerDimension and tunables.TILE_N * tunables.LANES <= device.limits.maxComputeInvocationsPerWorkgroup and tunables.TILE_N * tunables.LANES <= device.limits.maxComputeWorkgroupSizeX",
    "normDispatchFits": "tunables.NORM_WORKGROUP_SIZE <= device.limits.maxComputeInvocationsPerWorkgroup and tunables.NORM_WORKGROUP_SIZE <= device.limits.maxComputeWorkgroupSizeX",
    "biasPresence_nogb_noub": "not present.gateBiasT and not present.upBiasT",
    "biasPresence_nogb_ub": "not present.gateBiasT and present.upBiasT",
    "biasPresence_gb_noub": "present.gateBiasT and not present.upBiasT",
    "biasPresence_gb_ub": "present.gateBiasT and present.upBiasT"
  },
  "constants": {
    "aScalar": "\"f16\" if tensorDtypes.aT == \"float16\" else \"f32\"",
    "scalar": "\"f16\" if tensorDtypes.aT == \"float16\" else \"f32\"",
    "usesF16": "tensorDtypes.aT == \"float16\"",
    "K": "attrs.K",
    "N": "attrs.N",
    "blockSize": "attrs.block_size",
    "kBlocks": "kBlocks",
    "blobSize": "blobSize",
    "bits": "attrs.bits",
    "codesPerByte": "codesPerByte",
    "codeMask": "codeMask",
    "defaultZero": "\"2.0\" if attrs.bits == 2 else (\"8.0\" if attrs.bits == 4 else \"128.0\")",
    "tileN": "tunables.TILE_N",
    "lanes": "tunables.LANES",
    "rowTile": "rowTile",
    "rows": "aRows",
    "hidden": "attrs.K",
    "workgroupSize": "tunables.NORM_WORKGROUP_SIZE",
    "epsilon": "epsilonValue",
    "hasGateBias": "present.gateBiasT",
    "hasUpBias": "present.upBiasT",
    "hasSkip": "present.skipT",
    "writeResidual": "present.residualT",
    "K_LEN": "attrs.K",
    "N_LEN": "attrs.N"
  },
  "bindingSets": {
    "normFull": [
      {
        "name": "a",
        "arg": "aT",
        "semantic": "A",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      {
        "name": "skip",
        "arg": "skipT",
        "semantic": "skip",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      {
        "name": "norm_scale",
        "arg": "normScaleT",
        "semantic": "norm_scale",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar",
        "length": "$K_LEN"
      },
      { "name": "normed", "semantic": "normedA", "buffer": { "type": "storage" }, "elementType": "f32" },
      {
        "name": "residual",
        "arg": "residualT",
        "semantic": "input_skip_bias_sum",
        "buffer": { "type": "storage" },
        "elementType": "$aScalar"
      },
      {
        "name": "params",
        "semantic": "kernel.params",
        "buffer": { "type": "uniform" },
        "struct": { "name": "Params", "fields": [{ "name": "rows", "type": "u32", "value": "aRows" }] }
      }
    ],
    "normSkip": [
      {
        "name": "a",
        "arg": "aT",
        "semantic": "A",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      {
        "name": "skip",
        "arg": "skipT",
        "semantic": "skip",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      {
        "name": "norm_scale",
        "arg": "normScaleT",
        "semantic": "norm_scale",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar",
        "length": "$K_LEN"
      },
      { "name": "normed", "semantic": "normedA", "buffer": { "type": "storage" }, "elementType": "f32" },
      {
        "name": "params",
        "semantic": "kernel.params",
        "buffer": { "type": "uniform" },
        "struct": { "name": "Params", "fields": [{ "name": "rows", "type": "u32", "value": "aRows" }] }
      }
    ],
    "normOnly": [
      {
        "name": "a",
        "arg": "aT",
        "semantic": "A",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      {
        "name": "norm_scale",
        "arg": "normScaleT",
        "semantic": "norm_scale",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar",
        "length": "$K_LEN"
      },
      { "name": "normed", "semantic": "normedA", "buffer": { "type": "storage" }, "elementType": "f32" },
      {
        "name": "params",
        "semantic": "kernel.params",
        "buffer": { "type": "uniform" },
        "struct": { "name": "Params", "fields": [{ "name": "rows", "type": "u32", "value": "aRows" }] }
      }
    ],
    "gateUpAFull": [
      {
        "name": "a",
        "arg": "aT",
        "semantic": "A",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      {
        "name": "gate_b",
        "arg": "gateBT",
        "semantic": "gate_B",
        "buffer": { "type": "read-only-storage" },
        "elementType": "u32"
      },
      {
        "name": "gate_scales",
        "arg": "gateScalesT",
        "semantic": "gate_scales",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      {
        "name": "gate_bias",
        "arg": "gateBiasT",
        "semantic": "gate_bias",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar",
        "length": "$N_LEN"
      },
      {
        "name": "up_b",
        "arg": "upBT",
        "semantic": "up_B",
        "buffer": { "type": "read-only-storage" },
        "elementType": "u32"
      },
      {
        "name": "up_scales",
        "arg": "upScalesT",
        "semantic": "up_scales",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      {
        "name": "up_bias",
        "arg": "upBiasT",
        "semantic": "up_bias",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar",
        "length": "$N_LEN"
      },
      { "name": "y", "arg": "yT", "semantic": "Y", "buffer": { "type": "storage" }, "elementType": "$aScalar" }
    ],
    "gateUpNormedFull": [
      { "name": "normed", "semantic": "normedA", "buffer": { "type": "read-only-storage" }, "elementType": "f32" },
      {
        "name": "gate_b",
        "arg": "gateBT",
        "semantic": "gate_B",
        "buffer": { "type": "read-only-storage" },
        "elementType": "u32"
      },
      {
        "name": "gate_scales",
        "arg": "gateScalesT",
        "semantic": "gate_scales",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      {
        "name": "gate_bias",
        "arg": "gateBiasT",
        "semantic": "gate_bias",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar",
        "length": "$N_LEN"
      },
      {
        "name": "up_b",
        "arg": "upBT",
        "semantic": "up_B",
        "buffer": { "type": "read-only-storage" },
        "elementType": "u32"
      },
      {
        "name": "up_scales",
        "arg": "upScalesT",
        "semantic": "up_scales",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      {
        "name": "up_bias",
        "arg": "upBiasT",
        "semantic": "up_bias",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar",
        "length": "$N_LEN"
      },
      { "name": "y", "arg": "yT", "semantic": "Y", "buffer": { "type": "storage" }, "elementType": "$aScalar" }
    ],
    "fusedFull": [
      {
        "name": "a",
        "arg": "aT",
        "semantic": "A",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      {
        "name": "skip",
        "arg": "skipT",
        "semantic": "skip",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      {
        "name": "norm_scale",
        "arg": "normScaleT",
        "semantic": "norm_scale",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar",
        "length": "$K_LEN"
      },
      {
        "name": "gate_b",
        "arg": "gateBT",
        "semantic": "gate_B",
        "buffer": { "type": "read-only-storage" },
        "elementType": "u32"
      },
      {
        "name": "gate_scales",
        "arg": "gateScalesT",
        "semantic": "gate_scales",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      {
        "name": "gate_bias",
        "arg": "gateBiasT",
        "semantic": "gate_bias",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar",
        "length": "$N_LEN"
      },
      {
        "name": "up_b",
        "arg": "upBT",
        "semantic": "up_B",
        "buffer": { "type": "read-only-storage" },
        "elementType": "u32"
      },
      {
        "name": "up_scales",
        "arg": "upScalesT",
        "semantic": "up_scales",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      {
        "name": "up_bias",
        "arg": "upBiasT",
        "semantic": "up_bias",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar",
        "length": "$N_LEN"
      },
      { "name": "y", "arg": "yT", "semantic": "Y", "buffer": { "type": "storage" }, "elementType": "$aScalar" },
      {
        "name": "residual",
        "arg": "residualT",
        "semantic": "input_skip_bias_sum",
        "buffer": { "type": "storage" },
        "elementType": "$aScalar"
      }
    ],
    "gateUpA_nogb_noub": [
      {
        "name": "a",
        "arg": "aT",
        "semantic": "A",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      {
        "name": "gate_b",
        "arg": "gateBT",
        "semantic": "gate_B",
        "buffer": { "type": "read-only-storage" },
        "elementType": "u32"
      },
      {
        "name": "gate_scales",
        "arg": "gateScalesT",
        "semantic": "gate_scales",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      {
        "name": "up_b",
        "arg": "upBT",
        "semantic": "up_B",
        "buffer": { "type": "read-only-storage" },
        "elementType": "u32"
      },
      {
        "name": "up_scales",
        "arg": "upScalesT",
        "semantic": "up_scales",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      { "name": "y", "arg": "yT", "semantic": "Y", "buffer": { "type": "storage" }, "elementType": "$aScalar" }
    ],
    "gateUpNormed_nogb_noub": [
      { "name": "normed", "semantic": "normedA", "buffer": { "type": "read-only-storage" }, "elementType": "f32" },
      {
        "name": "gate_b",
        "arg": "gateBT",
        "semantic": "gate_B",
        "buffer": { "type": "read-only-storage" },
        "elementType": "u32"
      },
      {
        "name": "gate_scales",
        "arg": "gateScalesT",
        "semantic": "gate_scales",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      {
        "name": "up_b",
        "arg": "upBT",
        "semantic": "up_B",
        "buffer": { "type": "read-only-storage" },
        "elementType": "u32"
      },
      {
        "name": "up_scales",
        "arg": "upScalesT",
        "semantic": "up_scales",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      { "name": "y", "arg": "yT", "semantic": "Y", "buffer": { "type": "storage" }, "elementType": "$aScalar" }
    ],
    "fused_norm_nogb_noub": [
      {
        "name": "a",
        "arg": "aT",
        "semantic": "A",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      {
        "name": "norm_scale",
        "arg": "normScaleT",
        "semantic": "norm_scale",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar",
        "length": "$K_LEN"
      },
      {
        "name": "gate_b",
        "arg": "gateBT",
        "semantic": "gate_B",
        "buffer": { "type": "read-only-storage" },
        "elementType": "u32"
      },
      {
        "name": "gate_scales",
        "arg": "gateScalesT",
        "semantic": "gate_scales",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      {
        "name": "up_b",
        "arg": "upBT",
        "semantic": "up_B",
        "buffer": { "type": "read-only-storage" },
        "elementType": "u32"
      },
      {
        "name": "up_scales",
        "arg": "upScalesT",
        "semantic": "up_scales",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      { "name": "y", "arg": "yT", "semantic": "Y", "buffer": { "type": "storage" }, "elementType": "$aScalar" }
    ],
    "fused_skip_nogb_noub": [
      {
        "name": "a",
        "arg": "aT",
        "semantic": "A",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      {
        "name": "skip",
        "arg": "skipT",
        "semantic": "skip",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      {
        "name": "norm_scale",
        "arg": "normScaleT",
        "semantic": "norm_scale",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar",
        "length": "$K_LEN"
      },
      {
        "name": "gate_b",
        "arg": "gateBT",
        "semantic": "gate_B",
        "buffer": { "type": "read-only-storage" },
        "elementType": "u32"
      },
      {
        "name": "gate_scales",
        "arg": "gateScalesT",
        "semantic": "gate_scales",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$aScalar"
      },
      {
        "name": "up_b",
        "arg": "upBT",
        "semantic": "up_B",
        "buffer": { "type": "read-only-storage" },
        "elementType": "u32"
      },
      {
        "name": "up_scales",
        "arg": "upScalesT",
        "semantic": "up_scales",
        "buffer": { "type": "read-only-storage" },
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      "constants": { "inlineNorm": "1", "fromNormed": "0", "rowTile": "1" },
      "passes": [
        {
          "id": "main",
          "name": "MatMulNBitsMlp.FusedDecode",
          "shader": "mlp-gate-up.wgsl.jinja",
          "bindings": "fused_skip_gb_noub",
          "dispatch": { "x": "ceilDiv(attrs.N, tunables.TILE_N)", "y": "aRows" }
        }
      ]
    },
    {
      "id": "fused_skipsum_gb_noub",
      "priority": 30,
      "requires": { "limits": { "maxStorageBuffersPerShaderStage": 10 } },
      "when": ["mlpShapeOk", "normContractOk", "biasPresence_gb_noub", "gateUpDispatchFits", "aRows == 1", "present.skipT", "present.residualT"],
      "constants": { "inlineNorm": "1", "fromNormed": "0", "rowTile": "1" },
      "passes": [
        {
          "id": "main",
          "name": "MatMulNBitsMlp.FusedDecode",
          "shader": "mlp-gate-up.wgsl.jinja",
          "bindings": "fused_skipsum_gb_noub",
          "dispatch": { "x": "ceilDiv(attrs.N, tunables.TILE_N)", "y": "aRows" }
        }
      ]
    },
    {
      "id": "fused_norm_gb_ub",
      "priority": 30,
      "requires": { "limits": { "maxStorageBuffersPerShaderStage": 9 } },
      "when": ["mlpShapeOk", "normContractOk", "biasPresence_gb_ub", "gateUpDispatchFits", "aRows == 1", "not present.skipT", "not present.residualT"],
      "constants": { "inlineNorm": "1", "fromNormed": "0", "rowTile": "1" },
      "passes": [
        {
          "id": "main",
          "name": "MatMulNBitsMlp.FusedDecode",
          "shader": "mlp-gate-up.wgsl.jinja",
          "bindings": "fused_norm_gb_ub",
          "dispatch": { "x": "ceilDiv(attrs.N, tunables.TILE_N)", "y": "aRows" }
        }
      ]
    },
    {
      "id": "fused_skip_gb_ub",
      "priority": 30,
      "requires": { "limits": { "maxStorageBuffersPerShaderStage": 10 } },
      "when": ["mlpShapeOk", "normContractOk", "biasPresence_gb_ub", "gateUpDispatchFits", "aRows == 1", "present.skipT", "not present.residualT"],
      "constants": { "inlineNorm": "1", "fromNormed": "0", "rowTile": "1" },
      "passes": [
        {
          "id": "main",
          "name": "MatMulNBitsMlp.FusedDecode",
          "shader": "mlp-gate-up.wgsl.jinja",
          "bindings": "fused_skip_gb_ub",
          "dispatch": { "x": "ceilDiv(attrs.N, tunables.TILE_N)", "y": "aRows" }
        }
      ]
    }
  ]
}