{
  "domain": "ai.onnx",
  "name": "LayerNormalization",
  "sinceVersion": 17,
  "inputs": {
    "x": { "onnx": "X", "dtype": "T" },
    "scale": { "onnx": "Scale", "dtype": "T" },
    "b": { "onnx": "B", "dtype": "T", "optional": true }
  },
  "outputs": {
    "y": { "onnx": "Y", "dtype": "T", "rank": "ranks.x", "shape": "shapes.x" },
    "mean": { "onnx": "Mean", "dtype": "float32", "rank": "ranks.x", "optional": true },
    "invStdDev": { "onnx": "InvStdDev", "dtype": "float32", "rank": "ranks.x", "optional": true }
  },
  "attributes": { "axis": { "default": -1 }, "epsilon": { "default": 0.00001 }, "stash_type": { "default": 1 } },
  "attributeConstraints": { "stash_type": { "values": [1] } },
  "typeConstraints": { "T": ["float32", "float16"] },
  "tunables": { "MAX_WORKGROUP_SIZE": { "default": 256 }, "SCALAR_FAST_MAX_HIDDEN": { "default": 1024 } },
  "derive": {
    "deviceWorkgroupCap": "min(device.limits.maxComputeInvocationsPerWorkgroup, device.limits.maxComputeWorkgroupSizeX)",
    "normWorkgroupCap": "min(tunables.MAX_WORKGROUP_SIZE, deviceWorkgroupCap)",
    "hasSubgroupId": "device.features.has(\"subgroups\") and device.wgslLanguageFeatures.has(\"subgroup_id\")",
    "lastAxisWg": "min(normWorkgroupCap, pow2ceil(dim(shapes.x, -1)))",
    "lastAxisWgVec4": "min(normWorkgroupCap, pow2ceil(dim(shapes.x, -1) / 4))",
    "lastAxisContractOk": "ranks.x >= 1 and ranks.y == ranks.x and numel(shapes.x) == numel(shapes.y) and (attrs.axis == -1 or attrs.axis == ranks.x - 1)",
    "suffixAxisContractOk": "ranks.x >= 2 and ranks.y == ranks.x and numel(shapes.x) == numel(shapes.y) and attrs.axis + ranks.x >= 0 and attrs.axis < ranks.x and not (attrs.axis == -1 or attrs.axis == ranks.x - 1)",
    "axisNorm": "attrs.axis if attrs.axis >= 0 else attrs.axis + ranks.x",
    "normRows": "numel(shapes.x) / max(1, dim(shapes.x, -1)) if lastAxisContractOk else outer(shapes.x, axisNorm)",
    "normRowStride": "max(1, min(normRows, min(device.limits.maxComputeWorkgroupsPerDimension, 65535)))",
    "suffixAxisSize": "numel(shapes.x) / max(1, outer(shapes.x, axisNorm))",
    "suffixAxisWg": "min(normWorkgroupCap, pow2ceil(suffixAxisSize))",
    "suffixAxisWgVec4": "min(normWorkgroupCap, pow2ceil(suffixAxisSize / 4))",
    "genericHiddenSize": "dim(shapes.x, -1) if lastAxisContractOk else suffixAxisSize",
    "genericWorkgroupSize": "lastAxisWg if lastAxisContractOk else suffixAxisWg",
    "scaleExactOk": "ranks.x >= 1 and ranks.scale >= 1 and numel(shapes.scale) == dim(shapes.x, -1) and dim(shapes.scale, -1) == dim(shapes.x, -1)",
    "scaleBroadcastOk": "ranks.scale >= 0 and ranks.scale <= ranks.x and broadcastable(shapes.scale, shapes.x)",
    "biasExactOk": "present.b and ranks.x >= 1 and ranks.b >= 1 and numel(shapes.b) == dim(shapes.x, -1) and dim(shapes.b, -1) == dim(shapes.x, -1)",
    "biasBroadcastOk": "present.b and ranks.b >= 0 and ranks.b <= ranks.x and broadcastable(shapes.b, shapes.x)",
    "suffixScaleExactOk": "suffixAxisContractOk and scaleBroadcastOk and numel(shapes.scale) == suffixAxisSize",
    "suffixBiasExactOk": "present.b and suffixAxisContractOk and biasBroadcastOk and numel(shapes.b) == suffixAxisSize",
    "lastAxisExactScaleOk": "lastAxisContractOk and scaleExactOk",
    "lastAxisBroadcastScaleOk": "lastAxisContractOk and scaleBroadcastOk",
    "suffixAxisBroadcastScaleOk": "suffixAxisContractOk and scaleBroadcastOk",
    "suffixAxisExactAffineOk": "suffixAxisContractOk and suffixScaleExactOk and suffixBiasExactOk",
    "lastAxisScalarFastOk": "dtypes.T == \"f16\" or dim(shapes.x, -1) <= tunables.SCALAR_FAST_MAX_HIDDEN",
    "noStatsOutputs": "not present.mean and not present.invStdDev",
    "meanOnlyOutputs": "present.mean and not present.invStdDev",
    "invStdOnlyOutputs": "not present.mean and present.invStdDev",
    "fullStatsOutputs": "present.mean and present.invStdDev",
    "statsRowsOk": "fullStatsOutputs and ranks.x >= 1 and numel(shapes.mean) == normRows and numel(shapes.invStdDev) == normRows",
    "meanRowsOk": "present.mean and ranks.x >= 1 and numel(shapes.mean) == normRows",
    "invStdRowsOk": "present.invStdDev and ranks.x >= 1 and numel(shapes.invStdDev) == normRows",
    "statsOuterOk": "fullStatsOutputs and ranks.x >= 2 and numel(shapes.mean) == normRows and numel(shapes.invStdDev) == normRows"
  },
  "when": ["f16Ok(dtypes.T)"],
  "bindings": {
    "x": { "buffer": "read-only-storage", "elementType": "$vectorScalar" },
    "scale": { "buffer": "read-only-storage", "elementType": "$vectorScalar" },
    "y": { "buffer": "storage", "elementType": "$vectorScalar" },
    "params": {
      "buffer": "uniform",
      "struct": [
        { "name": "rows", "type": "u32", "value": "normRows" },
        { "name": "rowStride", "type": "u32", "value": "normRowStride" }
      ]
    },
    "bias": { "arg": "b", "buffer": "read-only-storage", "elementType": "$vectorScalar" },
    "mean_out": { "arg": "mean", "buffer": "storage", "elementType": "f32" },
    "inv_std_out": { "arg": "invStdDev", "buffer": "storage", "elementType": "f32" },
    "x_2": { "name": "x", "buffer": "read-only-storage", "elementType": "$scalar" },
    "scale_2": { "name": "scale", "buffer": "read-only-storage", "elementType": "$scalar" },
    "y_2": { "name": "y", "buffer": "storage", "elementType": "$scalar" },
    "bias_2": { "arg": "b", "name": "bias", "buffer": "read-only-storage", "elementType": "$scalar" }
  },
  "variants": [
    {
      "id": "last_axis_row_vec4",
      "priority": 110,
      "when": ["not present.b and noStatsOutputs", "lastAxisExactScaleOk", "dim(shapes.x, -1) % 4 == 0"],
      "derive": { "scalar": "dtypes.T", "vectorScalar": "\"vec4<\" ~ dtypes.T ~ \">\"" },
      "passes": [
        {
          "id": "main",
          "name": "LayerNormalization.LastAxisRowVec4",
          "shader": "norm-row-stats.wgsl.jinja",
          "derive": {
            "modeSpec": "\"layer\"",
            "vec4": true,
            "hasBias": false,
            "writeStats": false,
            "scalar": "dtypes.T",
            "usesF16Spec": "dtypes.T == \"f16\"",
            "hidden": "dim(shapes.x, -1)",
            "wg": "lastAxisWgVec4",
            "epsilon": "attrs.epsilon",
            "hiddenVec": "dim(shapes.x, -1) / 4",
            "vecType": "\"vec4<\" ~ dtypes.T ~ \">\"",
            "combineSubgroups": "hasSubgroupId"
          },
          "bindings": ["x", "scale", "y", "params"],
          "dispatch": { "x": "min(normRows, 65535)", "y": "ceilDiv(normRows, 65535)", "z": 1 },
          "subgroupCollectivesWidth": "portable"
        }
      ]
    },
    {
      "id": "last_axis_row",
      "priority": 100,
      "when": ["not present.b and noStatsOutputs", "lastAxisExactScaleOk"],
      "demoteWhen": ["not lastAxisScalarFastOk"],
      "derive": { "scalar": "dtypes.T", "vectorScalar": "dtypes.T" },
      "passes": [
        {
          "id": "main",
          "name": "LayerNormalization.LastAxisRow",
          "shader": "norm-row-stats.wgsl.jinja",
          "derive": {
            "modeSpec": "\"layer\"",
            "vec4": false,
            "hasBias": false,
            "writeStats": false,
            "scalar": "dtypes.T",
            "usesF16Spec": "dtypes.T == \"f16\"",
            "hidden": "dim(shapes.x, -1)",
            "wg": "lastAxisWg",
            "epsilon": "attrs.epsilon",
            "combineSubgroups": "hasSubgroupId"
          },
          "bindings": ["x", "scale", "y", "params"],
          "dispatch": { "x": "min(normRows, 65535)", "y": "ceilDiv(normRows, 65535)", "z": 1 },
          "subgroupCollectivesWidth": "portable"
        }
      ]
    },
    {
      "id": "last_axis_bias_row_vec4",
      "priority": 111,
      "when": ["present.b and noStatsOutputs and biasExactOk", "lastAxisExactScaleOk", "dim(shapes.x, -1) % 4 == 0"],
      "derive": { "scalar": "dtypes.T", "vectorScalar": "\"vec4<\" ~ dtypes.T ~ \">\"" },
      "passes": [
        {
          "id": "main",
          "name": "LayerNormalization.LastAxisRowVec4",
          "shader": "norm-row-stats.wgsl.jinja",
          "derive": {
            "modeSpec": "\"layer\"",
            "vec4": true,
            "hasBias": true,
            "writeStats": false,
            "scalar": "dtypes.T",
            "usesF16Spec": "dtypes.T == \"f16\"",
            "hidden": "dim(shapes.x, -1)",
            "wg": "lastAxisWgVec4",
            "epsilon": "attrs.epsilon",
            "hiddenVec": "dim(shapes.x, -1) / 4",
            "vecType": "\"vec4<\" ~ dtypes.T ~ \">\"",
            "combineSubgroups": "hasSubgroupId"
          },
          "bindings": ["x", "scale", "bias", "y", "params"],
          "dispatch": { "x": "min(normRows, 65535)", "y": "ceilDiv(normRows, 65535)", "z": 1 },
          "subgroupCollectivesWidth": "portable"
        }
      ]
    },
    {
      "id": "last_axis_bias_row",
      "priority": 101,
      "when": ["present.b and noStatsOutputs and biasExactOk", "lastAxisExactScaleOk"],
      "demoteWhen": ["not lastAxisScalarFastOk"],
      "derive": { "scalar": "dtypes.T", "vectorScalar": "dtypes.T" },
      "passes": [
        {
          "id": "main",
          "name": "LayerNormalization.LastAxisRow",
          "shader": "norm-row-stats.wgsl.jinja",
          "derive": {
            "modeSpec": "\"layer\"",
            "vec4": false,
            "hasBias": true,
            "writeStats": false,
            "scalar": "dtypes.T",
            "usesF16Spec": "dtypes.T == \"f16\"",
            "hidden": "dim(shapes.x, -1)",
            "wg": "lastAxisWg",
            "epsilon": "attrs.epsilon",
            "combineSubgroups": "hasSubgroupId"
          },
          "bindings": ["x", "scale", "bias", "y", "params"],
          "dispatch": { "x": "min(normRows, 65535)", "y": "ceilDiv(normRows, 65535)", "z": 1 },
          "subgroupCollectivesWidth": "portable"
        }
      ]
    },
    {
      "id": "last_axis_stats_row_vec4",
      "priority": 112,
      "when": ["not present.b and fullStatsOutputs and statsRowsOk", "lastAxisExactScaleOk", "dim(shapes.x, -1) % 4 == 0"],
      "derive": { "scalar": "dtypes.T", "vectorScalar": "\"vec4<\" ~ dtypes.T ~ \">\"" },
      "passes": [
        {
          "id": "main",
          "name": "LayerNormalization.LastAxisRowVec4",
          "shader": "norm-row-stats.wgsl.jinja",
          "derive": {
            "modeSpec": "\"layer\"",
            "vec4": true,
            "hasBias": false,
            "writeStats": true,
            "scalar": "dtypes.T",
            "usesF16Spec": "dtypes.T == \"f16\"",
            "hidden": "dim(shapes.x, -1)",
            "wg": "lastAxisWgVec4",
            "epsilon": "attrs.epsilon",
            "hiddenVec": "dim(shapes.x, -1) / 4",
            "vecType": "\"vec4<\" ~ dtypes.T ~ \">\"",
            "combineSubgroups": "hasSubgroupId"
          },
          "bindings": ["x", "scale", "y", "mean_out", "inv_std_out", "params"],
          "dispatch": { "x": "min(normRows, 65535)", "y": "ceilDiv(normRows, 65535)", "z": 1 },
          "subgroupCollectivesWidth": "portable"
        }
      ]
    },
    {
      "id": "last_axis_stats_row",
      "priority": 102,
      "when": ["not present.b and fullStatsOutputs and statsRowsOk", "lastAxisExactScaleOk"],
      "demoteWhen": ["not lastAxisScalarFastOk"],
      "derive": { "scalar": "dtypes.T", "vectorScalar": "dtypes.T" },
      "passes": [
        {
          "id": "main",
          "name": "LayerNormalization.LastAxisRow",
          "shader": "norm-row-stats.wgsl.jinja",
          "derive": {
            "modeSpec": "\"layer\"",
            "vec4": false,
            "hasBias": false,
            "writeStats": true,
            "scalar": "dtypes.T",
            "usesF16Spec": "dtypes.T == \"f16\"",
            "hidden": "dim(shapes.x, -1)",
            "wg": "lastAxisWg",
            "epsilon": "attrs.epsilon",
            "combineSubgroups": "hasSubgroupId"
          },
          "bindings": ["x", "scale", "y", "mean_out", "inv_std_out", "params"],
          "dispatch": { "x": "min(normRows, 65535)", "y": "ceilDiv(normRows, 65535)", "z": 1 },
          "subgroupCollectivesWidth": "portable"
        }
      ]
    },
    {
      "id": "last_axis_bias_stats_row_vec4",
      "priority": 113,
      "when": ["present.b and fullStatsOutputs and biasExactOk and statsRowsOk", "lastAxisExactScaleOk", "dim(shapes.x, -1) % 4 == 0"],
      "derive": { "scalar": "dtypes.T", "vectorScalar": "\"vec4<\" ~ dtypes.T ~ \">\"" },
      "passes": [
        {
          "id": "main",
          "name": "LayerNormalization.LastAxisRowVec4",
          "shader": "norm-row-stats.wgsl.jinja",
          "derive": {
            "modeSpec": "\"layer\"",
            "vec4": true,
            "hasBias": true,
            "writeStats": true,
            "scalar": "dtypes.T",
            "usesF16Spec": "dtypes.T == \"f16\"",
            "hidden": "dim(shapes.x, -1)",
            "wg": "lastAxisWgVec4",
            "epsilon": "attrs.epsilon",
            "hiddenVec": "dim(shapes.x, -1) / 4",
            "vecType": "\"vec4<\" ~ dtypes.T ~ \">\"",
            "combineSubgroups": "hasSubgroupId"
          },
          "bindings": ["x", "scale", "bias", "y", "mean_out", "inv_std_out", "params"],
          "dispatch": { "x": "min(normRows, 65535)", "y": "ceilDiv(normRows, 65535)", "z": 1 },
          "subgroupCollectivesWidth": "portable"
        }
      ]
    },
    {
      "id": "last_axis_bias_stats_row",
      "priority": 103,
      "when": ["present.b and fullStatsOutputs and biasExactOk and statsRowsOk", "lastAxisExactScaleOk"],
      "demoteWhen": ["not lastAxisScalarFastOk"],
      "derive": { "scalar": "dtypes.T", "vectorScalar": "dtypes.T" },
      "passes": [
        {
          "id": "main",
          "name": "LayerNormalization.LastAxisRow",
          "shader": "norm-row-stats.wgsl.jinja",
          "derive": {
            "modeSpec": "\"layer\"",
            "vec4": false,
            "hasBias": true,
            "writeStats": true,
            "scalar": "dtypes.T",
            "usesF16Spec": "dtypes.T == \"f16\"",
            "hidden": "dim(shapes.x, -1)",
            "wg": "lastAxisWg",
            "epsilon": "attrs.epsilon",
            "combineSubgroups": "hasSubgroupId"
          },
          "bindings": ["x", "scale", "bias", "y", "mean_out", "inv_std_out", "params"],
          "dispatch": { "x": "min(normRows, 65535)", "y": "ceilDiv(normRows, 65535)", "z": 1 },
          "subgroupCollectivesWidth": "portable"
        }
      ]
    },
    {
      "id": "suffix_axis_bias_exact_row_vec4",
      "priority": 121,
      "when": ["present.b", "noStatsOutputs", "suffixAxisExactAffineOk", "suffixAxisSize % 4 == 0"],
      "derive": { "scalar": "dtypes.T", "vectorScalar": "\"vec4<\" ~ dtypes.T ~ \">\"" },
      "passes": [
        {
          "id": "main",
          "name": "LayerNormalization.SuffixAxisRowVec4",
          "shader": "norm-row-stats.wgsl.jinja",
          "derive": {
            "modeSpec": "\"layer\"",
            "vec4": true,
            "hasBias": true,
            "writeStats": false,
            "scalar": "dtypes.T",
            "usesF16Spec": "dtypes.T == \"f16\"",
            "hidden": "suffixAxisSize",
            "wg": "suffixAxisWgVec4",
            "epsilon": "attrs.epsilon",
            "hiddenVec": "suffixAxisSize / 4",
            "vecType": "\"vec4<\" ~ dtypes.T ~ \">\"",
            "combineSubgroups": "hasSubgroupId"
          },
          "bindings": ["x", "scale", "bias", "y", "params"],
          "dispatch": { "x": "min(normRows, 65535)", "y": "ceilDiv(normRows, 65535)", "z": 1 },
          "subgroupCollectivesWidth": "portable"
        }
      ]
    },
    {
      "id": "last_axis",
      "priority": 0,
      "when": ["not present.b", "noStatsOutputs", "lastAxisBroadcastScaleOk"],
      "derive": {
        "hasBias": false,
        "writeMean": false,
        "writeInvStdDev": false,
        "scalar": "dtypes.T",
        "vectorScalar": "dtypes.T",
        "hiddenSize": "dim(shapes.x, -1)",
        "workgroupSize": "lastAxisWg",
        "epsilon": "attrs.epsilon"
      },
      "passes": [
        {
          "id": "main",
          "name": "LayerNormalization",
          "shader": "layer-normalization.wgsl.jinja",
          "derive": { "xShape": "shapes.x", "scaleShape": "shapes.scale" },
          "bindings": ["x", "scale", "y", "params"],
          "dispatch": { "x": "min(normRows, 65535)", "y": "ceilDiv(normRows, 65535)", "z": 1 }
        }
      ]
    },
    {
      "id": "last_axis_bias",
      "priority": 10,
      "when": ["present.b", "noStatsOutputs", "lastAxisBroadcastScaleOk", "biasBroadcastOk"],
      "derive": {
        "hasBias": true,
        "writeMean": false,
        "writeInvStdDev": false,
        "scalar": "dtypes.T",
        "vectorScalar": "dtypes.T",
        "hiddenSize": "dim(shapes.x, -1)",
        "workgroupSize": "lastAxisWg",
        "epsilon": "attrs.epsilon"
      },
      "passes": [
        {
          "id": "main",
          "name": "LayerNormalization",
          "shader": "layer-normalization.wgsl.jinja",
          "derive": { "xShape": "shapes.x", "scaleShape": "shapes.scale", "biasShape": "shapes.b" },
          "bindings": ["x", "scale", "bias", "y", "params"],
          "dispatch": { "x": "min(normRows, 65535)", "y": "ceilDiv(normRows, 65535)", "z": 1 }
        }
      ]
    },
    {
      "id": "last_axis_stats",
      "priority": 20,
      "when": ["not present.b", "fullStatsOutputs", "lastAxisBroadcastScaleOk", "statsRowsOk"],
      "derive": {
        "hasBias": false,
        "writeMean": true,
        "writeInvStdDev": true,
        "scalar": "dtypes.T",
        "vectorScalar": "dtypes.T",
        "hiddenSize": "dim(shapes.x, -1)",
        "workgroupSize": "lastAxisWg",
        "epsilon": "attrs.epsilon"
      },
      "passes": [
        {
          "id": "main",
          "name": "LayerNormalization",
          "shader": "layer-normalization.wgsl.jinja",
          "derive": { "xShape": "shapes.x", "scaleShape": "shapes.scale" },
          "bindings": ["x", "scale", "y", "mean_out", "inv_std_out", "params"],
          "dispatch": { "x": "min(normRows, 65535)", "y": "ceilDiv(normRows, 65535)", "z": 1 }
        }
      ]
    },
    {
      "id": "last_axis_bias_stats",
      "priority": 30,
      "when": ["present.b", "fullStatsOutputs", "lastAxisBroadcastScaleOk", "biasBroadcastOk", "statsRowsOk"],
      "derive": {
        "hasBias": true,
        "writeMean": true,
        "writeInvStdDev": true,
        "scalar": "dtypes.T",
        "vectorScalar": "dtypes.T",
        "hiddenSize": "dim(shapes.x, -1)",
        "workgroupSize": "lastAxisWg",
        "epsilon": "attrs.epsilon"
      },
      "passes": [
        {
          "id": "main",
          "name": "LayerNormalization",
          "shader": "layer-normalization.wgsl.jinja",
          "derive": { "xShape": "shapes.x", "scaleShape": "shapes.scale", "biasShape": "shapes.b" },
          "bindings": ["x", "scale", "bias", "y", "mean_out", "inv_std_out", "params"],
          "dispatch": { "x": "min(normRows, 65535)", "y": "ceilDiv(normRows, 65535)", "z": 1 }
        }
      ]
    },
    {
      "id": "suffix_axis",
      "priority": 40,
      "when": ["not present.b", "noStatsOutputs", "suffixAxisBroadcastScaleOk"],
      "derive": {
        "hasBias": false,
        "writeMean": false,
        "writeInvStdDev": false,
        "scalar": "dtypes.T",
        "vectorScalar": "dtypes.T",
        "hiddenSize": "suffixAxisSize",
        "workgroupSize": "suffixAxisWg",
        "epsilon": "attrs.epsilon"
      },
      "passes": [
        {
          "id": "main",
          "name": "LayerNormalization.SuffixAxis",
          "shader": "layer-normalization.wgsl.jinja",
          "derive": { "xShape": "shapes.x", "scaleShape": "shapes.scale" },
          "bindings": ["x", "scale", "y", "params"],
          "dispatch": { "x": "min(normRows, 65535)", "y": "ceilDiv(normRows, 65535)", "z": 1 }
        }
      ]
    },
    {
      "id": "suffix_axis_bias",
      "priority": 50,
      "when": ["present.b", "noStatsOutputs", "suffixAxisBroadcastScaleOk", "biasBroadcastOk"],
      "derive": {
        "hasBias": true,
        "writeMean": false,
        "writeInvStdDev": false,
        "scalar": "dtypes.T",
        "vectorScalar": "dtypes.T",
        "hiddenSize": "suffixAxisSize",
        "workgroupSize": "suffixAxisWg",
        "epsilon": "attrs.epsilon"
      },
      "passes": [
        {
          "id": "main",
          "name": "LayerNormalization.SuffixAxisBias",
          "shader": "layer-normalization.wgsl.jinja",
          "derive": { "xShape": "shapes.x", "scaleShape": "shapes.scale", "biasShape": "shapes.b" },
          "bindings": ["x", "scale", "bias", "y", "params"],
          "dispatch": { "x": "min(normRows, 65535)", "y": "ceilDiv(normRows, 65535)", "z": 1 }
        }
      ]
    },
    {
      "id": "suffix_axis_stats",
      "priority": 45,
      "when": ["not present.b", "fullStatsOutputs", "suffixAxisBroadcastScaleOk", "statsOuterOk"],
      "derive": {
        "hasBias": false,
        "writeMean": true,
        "writeInvStdDev": true,
        "scalar": "dtypes.T",
        "vectorScalar": "dtypes.T",
        "hiddenSize": "suffixAxisSize",
        "workgroupSize": "suffixAxisWg",
        "epsilon": "attrs.epsilon"
      },
      "passes": [
        {
          "id": "main",
          "name": "LayerNormalization.SuffixAxisStats",
          "shader": "layer-normalization.wgsl.jinja",
          "derive": { "xShape": "shapes.x", "scaleShape": "shapes.scale" },
          "bindings": ["x", "scale", "y", "mean_out", "inv_std_out", "params"],
          "dispatch": { "x": "min(normRows, 65535)", "y": "ceilDiv(normRows, 65535)", "z": 1 }
        }
      ]
    },
    {
      "id": "suffix_axis_bias_stats",
      "priority": 55,
      "when": ["present.b", "fullStatsOutputs", "suffixAxisBroadcastScaleOk", "biasBroadcastOk", "statsOuterOk"],
      "derive": {
        "hasBias": true,
        "writeMean": true,
        "writeInvStdDev": true,
        "scalar": "dtypes.T",
        "vectorScalar": "dtypes.T",
        "hiddenSize": "suffixAxisSize",
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}