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