{
  "domain": "com.microsoft",
  "name": "FastGelu",
  "sinceVersion": 1,
  "description": "Applies the GELU (Gaussian Error Linear Unit) activation using a tanh approximation: `Y = 0.5 * X * (1 + tanh(0.797885 * X + 0.035677 * X^3))`. An optional `bias` is added to `X` before the activation is computed. This WebGPU package implements float16 and float32; the schema-allowed double and bfloat16 types are not supported.",
  "inputs": [
    { "role": "X", "dtype": "T", "description": "Values transformed by FastGelu after adding the optional `bias`." },
    {
      "role": "bias",
      "dtype": "T",
      "rank": 1,
      "optional": true,
      "description": "Optional 1-D bias added to `X` along the last dimension before the GELU activation."
    }
  ],
  "outputs": [
    {
      "role": "Y",
      "dtype": "T",
      "rank": "ranks.X",
      "shape": "shapes.X",
      "description": "Output tensor after applying the GELU activation; same shape as `X`."
    }
  ],
  "typeConstraints": { "T": ["float32", "float16"] },
  "args": {
    "X": { "kind": "tensor", "semantic": "X", "role": "input" },
    "bias": { "kind": "tensor", "semantic": "bias", "role": "input", "required": false },
    "Y": { "kind": "tensor", "semantic": "Y", "role": "output" }
  },
  "tunables": { "WORKGROUP_SIZE": 256 },
  "derive": {
    "deviceWorkgroupCap": "min(device.limits.maxComputeInvocationsPerWorkgroup, device.limits.maxComputeWorkgroupSizeX)",
    "storageBufferLimit": "min(device.limits.maxStorageBufferBindingSize, device.limits.maxBufferSize)",
    "workgroupSize": "min(tunables.WORKGROUP_SIZE, deviceWorkgroupCap)",
    "buffersFit": "numel(shapes.X) * dtypeBytes(dtypes.T) <= storageBufferLimit and numel(shapes.Y) * dtypeBytes(dtypes.T) <= storageBufferLimit and (not present.bias or numel(shapes.bias) * dtypeBytes(dtypes.T) <= storageBufferLimit)",
    "dispatchFits": "numel(shapes.X) <= device.limits.maxComputeWorkgroupsPerDimension * device.limits.maxComputeWorkgroupsPerDimension * workgroupSize * 4",
    "baseOk": "workgroupSize > 0 and ranks.X >= 1 and numel(shapes.X) == numel(shapes.Y) and f16Ok(dtypes.T) and buffersFit and dispatchFits",
    "biasOk": "present.bias and ranks.bias == 1 and dim(shapes.bias, 0) == dim(shapes.X, ranks.X - 1)",
    "noBiasOk": "not present.bias",
    "vec4Ok": "numel(shapes.X) > 0 and numel(shapes.X) % 4 == 0 and dim(shapes.X, ranks.X - 1) % 4 == 0"
  },
  "constants": { "scalar": "dtypes.T", "usesF16": "dtypes.T == \"f16\"", "approximate": "\"tanh\"" },
  "bindingSets": {
    "vec4Bias": [
      {
        "name": "x",
        "arg": "X",
        "semantic": "X",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$vectorScalar"
      },
      {
        "name": "bias",
        "arg": "bias",
        "semantic": "bias",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$scalar",
        "length": "$hidden"
      },
      { "name": "y", "arg": "Y", "semantic": "Y", "buffer": { "type": "storage" }, "elementType": "$vectorScalar" },
      {
        "name": "params",
        "semantic": "kernel.params",
        "buffer": { "type": "uniform" },
        "struct": { "name": "Params", "fields": [{ "name": "count", "type": "u32", "value": "numel(shapes.X) / 4" }] }
      }
    ],
    "vec4": [
      {
        "name": "x",
        "arg": "X",
        "semantic": "X",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$vectorScalar"
      },
      { "name": "y", "arg": "Y", "semantic": "Y", "buffer": { "type": "storage" }, "elementType": "$vectorScalar" },
      {
        "name": "params",
        "semantic": "kernel.params",
        "buffer": { "type": "uniform" },
        "struct": { "name": "Params", "fields": [{ "name": "count", "type": "u32", "value": "numel(shapes.X) / 4" }] }
      }
    ],
    "scalarBias": [
      { "name": "x", "arg": "X", "semantic": "X", "buffer": { "type": "read-only-storage" }, "elementType": "$scalar" },
      {
        "name": "bias",
        "arg": "bias",
        "semantic": "bias",
        "buffer": { "type": "read-only-storage" },
        "elementType": "$scalar"
      },
      { "name": "y", "arg": "Y", "semantic": "Y", "buffer": { "type": "storage" }, "elementType": "$scalar" },
      {
        "name": "params",
        "semantic": "kernel.params",
        "buffer": { "type": "uniform" },
        "struct": { "name": "Params", "fields": [{ "name": "count", "type": "u32", "value": "numel(shapes.X)" }] }
      }
    ],
    "scalar": [
      { "name": "x", "arg": "X", "semantic": "X", "buffer": { "type": "read-only-storage" }, "elementType": "$scalar" },
      { "name": "y", "arg": "Y", "semantic": "Y", "buffer": { "type": "storage" }, "elementType": "$scalar" },
      {
        "name": "params",
        "semantic": "kernel.params",
        "buffer": { "type": "uniform" },
        "struct": { "name": "Params", "fields": [{ "name": "count", "type": "u32", "value": "numel(shapes.X)" }] }
      }
    ]
  },
  "variants": [
    {
      "id": "vec4_bias",
      "priority": 30,
      "when": ["baseOk", "biasOk", "vec4Ok"],
      "constants": {
        "vec4": true,
        "vec4Tail": false,
        "hasBias": true,
        "vectorScalar": "\"vec4<\" ~ dtypes.T ~ \">\"",
        "hidden": "dim(shapes.X, ranks.X - 1) if dim(shapes.X, ranks.X - 1) > 0 else 1"
      },
      "passes": [
        {
          "id": "main",
          "name": "FastGelu.vec4Bias",
          "shader": "elementwise-bias-gelu.wgsl.jinja",
          "bindings": "vec4Bias",
          "dispatch": { "threads": "numel(shapes.X) / 4", "workgroupSize": "workgroupSize" }
        }
      ]
    },
    {
      "id": "vec4_no_bias",
      "priority": 25,
      "when": ["baseOk", "noBiasOk", "vec4Ok"],
      "constants": { "vec4": true, "vec4Tail": false, "hasBias": false, "vectorScalar": "\"vec4<\" ~ dtypes.T ~ \">\"" },
      "passes": [
        {
          "id": "main",
          "name": "FastGelu.vec4",
          "shader": "elementwise-bias-gelu.wgsl.jinja",
          "bindings": "vec4",
          "dispatch": { "threads": "numel(shapes.X) / 4", "workgroupSize": "workgroupSize" }
        }
      ]
    },
    {
      "id": "vec4_tail_bias",
      "priority": 20,
      "when": ["baseOk", "biasOk", "numel(shapes.X) > 0"],
      "constants": {
        "vec4": false,
        "vec4Tail": true,
        "hasBias": true,
        "hidden": "dim(shapes.X, ranks.X - 1) if dim(shapes.X, ranks.X - 1) > 0 else 1"
      },
      "passes": [
        {
          "id": "main",
          "name": "FastGelu.vec4TailBias",
          "shader": "elementwise-bias-gelu.wgsl.jinja",
          "bindings": "scalarBias",
          "dispatch": { "threads": "ceilDiv(numel(shapes.X), 4)", "workgroupSize": "workgroupSize" }
        }
      ]
    },
    {
      "id": "vec4_tail_no_bias",
      "priority": 15,
      "when": ["baseOk", "noBiasOk", "numel(shapes.X) > 0"],
      "constants": { "vec4": false, "vec4Tail": true, "hasBias": false },
      "passes": [
        {
          "id": "main",
          "name": "FastGelu.vec4Tail",
          "shader": "elementwise-bias-gelu.wgsl.jinja",
          "bindings": "scalar",
          "dispatch": { "threads": "ceilDiv(numel(shapes.X), 4)", "workgroupSize": "workgroupSize" }
        }
      ]
    },
    {
      "id": "scalar_bias",
      "priority": 10,
      "when": ["baseOk", "biasOk", "true"],
      "constants": {
        "vec4": false,
        "vec4Tail": false,
        "hasBias": true,
        "hidden": "dim(shapes.X, ranks.X - 1) if dim(shapes.X, ranks.X - 1) > 0 else 1"
      },
      "passes": [
        {
          "id": "main",
          "name": "FastGelu.scalarBias",
          "shader": "elementwise-bias-gelu.wgsl.jinja",
          "bindings": "scalarBias",
          "dispatch": { "threads": "numel(shapes.X)", "workgroupSize": "workgroupSize" }
        }
      ]
    },
    {
      "id": "scalar_no_bias",
      "priority": 0,
      "when": ["baseOk", "noBiasOk", "true"],
      "constants": { "vec4": false, "vec4Tail": false, "hasBias": false },
      "passes": [
        {
          "id": "main",
          "name": "FastGelu.scalar",
          "shader": "elementwise-bias-gelu.wgsl.jinja",
          "bindings": "scalar",
          "dispatch": { "threads": "numel(shapes.X)", "workgroupSize": "workgroupSize" }
        }
      ]
    }
  ]
}