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            "values": { "$ref": "#/fixtureArrays/varlenconv-unit-capture-b64-c4096-k4-cap4_input_captureCountT" }
          }
        }
      },
      "outputs": {
        "outputT": { "shape": [64, 4097], "dtype": "float32" },
        "finalStateT": { "shape": [64, 4097, 7], "dtype": "float32" },
        "stateUpdateT": { "dtype": "float32", "shape": [64, 8, 4097] }
      },
      "bench": {
        "metrics": [
          {
            "type": "bandwidth",
            "name": "Logical tensor traffic",
            "provenance": "logical",
            "value": "(numel(shapes.inputT) + numel(shapes.weightT) + numel(shapes.initialStateT) + numel(shapes.outputT) + numel(shapes.finalStateT) + (numel(shapes.biasT) if has(shapes, \"biasT\") else 0) + (numel(shapes.stateUpdateT) if has(shapes, \"stateUpdateT\") else 0)) * dtypeBytes(args.dtype) + 4 * (numel(shapes.cumulativeSequenceLengthT) + (numel(shapes.captureCountT) if has(shapes, \"captureCountT\") else 0))"
          }
        ]
      },
      "attrs": { "activation": "silu", "state_update_capacity": 8 }
    },
    {
      "name": "varlenconv-capture-b64-t128-c4096-k4-d1",
      "preset": "smoke",
      "vars": { "dtype": "float32" },
      "inputs": {
        "inputT": { "shape": [128, 4096], "dtype": "float32", "dist": "normal", "seed": 4100, "scale": 1 },
        "weightT": { "shape": [4096, 1, 4], "dtype": "float32", "dist": "normal", "seed": 4101, "scale": 1 },
        "cumulativeSequenceLengthT": {
          "dtype": "int32",
          "shape": [65],
          "dist": "linearMod",
          "mod": 130,
          "step": 2,
          "offset": 0
        },
        "biasT": { "shape": [4096], "dtype": "float32", "dist": "normal", "seed": 4102, "scale": 1 },
        "initialStateT": { "shape": [64, 4096, 3], "dtype": "float32", "dist": "normal", "seed": 4103, "scale": 1 },
        "captureCountT": {
          "dtype": "int32",
          "shape": [64],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/varlenconv-unit-capture-b64-c4096-k4-cap4_input_captureCountT" }
          }
        }
      },
      "outputs": {
        "outputT": { "shape": [128, 4096], "dtype": "float32" },
        "finalStateT": { "shape": [64, 4096, 3], "dtype": "float32" },
        "stateUpdateT": { "dtype": "float32", "shape": [64, 4, 4096] }
      },
      "bench": {
        "metrics": [
          {
            "type": "bandwidth",
            "name": "Logical tensor traffic",
            "provenance": "logical",
            "value": "(numel(shapes.inputT) + numel(shapes.weightT) + numel(shapes.initialStateT) + numel(shapes.outputT) + numel(shapes.finalStateT) + (numel(shapes.biasT) if has(shapes, \"biasT\") else 0) + (numel(shapes.stateUpdateT) if has(shapes, \"stateUpdateT\") else 0)) * dtypeBytes(args.dtype) + 4 * (numel(shapes.cumulativeSequenceLengthT) + (numel(shapes.captureCountT) if has(shapes, \"captureCountT\") else 0))"
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        ]
      },
      "attrs": { "activation": "silu", "state_update_capacity": 4, "dilation": 1 }
    },
    {
      "name": "varlenconv-capture-b64-t128-c4096-k4-d2",
      "preset": "smoke",
      "vars": { "dtype": "float32" },
      "inputs": {
        "inputT": { "shape": [128, 4096], "dtype": "float32", "dist": "normal", "seed": 4100, "scale": 1 },
        "weightT": { "shape": [4096, 1, 4], "dtype": "float32", "dist": "normal", "seed": 4101, "scale": 1 },
        "cumulativeSequenceLengthT": {
          "dtype": "int32",
          "shape": [65],
          "dist": "linearMod",
          "mod": 130,
          "step": 2,
          "offset": 0
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        "biasT": { "shape": [4096], "dtype": "float32", "dist": "normal", "seed": 4102, "scale": 1 },
        "initialStateT": { "shape": [64, 4096, 6], "dtype": "float32", "dist": "normal", "seed": 4103, "scale": 1 },
        "captureCountT": {
          "dtype": "int32",
          "shape": [64],
          "data": {
            "kind": "values",
            "values": { "$ref": "#/fixtureArrays/varlenconv-unit-capture-b64-c4096-k4-cap4_input_captureCountT" }
          }
        }
      },
      "outputs": {
        "outputT": { "shape": [128, 4096], "dtype": "float32" },
        "finalStateT": { "shape": [64, 4096, 6], "dtype": "float32" },
        "stateUpdateT": { "dtype": "float32", "shape": [64, 4, 4096] }
      },
      "bench": {
        "metrics": [
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            "type": "bandwidth",
            "name": "Logical tensor traffic",
            "provenance": "logical",
            "value": "(numel(shapes.inputT) + numel(shapes.weightT) + numel(shapes.initialStateT) + numel(shapes.outputT) + numel(shapes.finalStateT) + (numel(shapes.biasT) if has(shapes, \"biasT\") else 0) + (numel(shapes.stateUpdateT) if has(shapes, \"stateUpdateT\") else 0)) * dtypeBytes(args.dtype) + 4 * (numel(shapes.cumulativeSequenceLengthT) + (numel(shapes.captureCountT) if has(shapes, \"captureCountT\") else 0))"
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      },
      "attrs": { "activation": "silu", "state_update_capacity": 4, "dilation": 2 }
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  ]
}