ai.onnx.Col2Im / build /webgpu /bench.json
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{
"op": "ai.onnx.Col2Im",
"tunableSpace": { "WORKGROUP_SIZE": [64, 128, 256] },
"cases": [
{
"name": "nchw_1x16_32x32_k3",
"attrs": {},
"inputs": {
"input": { "dtype": "float32", "shape": [1, 144, 900] },
"image_shape": { "dtype": "uint32", "shape": [2], "data": { "kind": "values", "values": [32, 32] } },
"block_shape": { "dtype": "uint32", "shape": [2], "data": { "kind": "values", "values": [3, 3] } }
},
"outputs": { "output": { "dtype": "float32", "shape": [1, 16, 32, 32] } }
},
{
"name": "nchw_4m_k3_overlap_healthy",
"preset": "smoke",
"attrs": {},
"inputs": {
"input": { "dtype": "float32", "shape": [1, 144, 260100], "dist": "normal", "seed": 411, "scale": 0.2 },
"image_shape": { "dtype": "uint32", "shape": [2], "data": { "kind": "values", "values": [512, 512] } },
"block_shape": { "dtype": "uint32", "shape": [2], "data": { "kind": "values", "values": [3, 3] } }
},
"outputs": { "output": { "dtype": "float32", "shape": [1, 16, 512, 512] } },
"bench": {
"primary": true,
"metrics": [{ "type": "bandwidth", "value": "(numel(shapes.input) + numel(shapes.output)) * 4" }]
}
},
{
"name": "nchw_dispatch_cliff_8m_gidy_fold",
"preset": "smoke",
"attrs": {},
"inputs": {
"input": { "dtype": "float32", "shape": [1, 32, 262144], "dist": "normal", "seed": 412, "scale": 0.2 },
"image_shape": { "dtype": "uint32", "shape": [2], "data": { "kind": "values", "values": [512, 512] } },
"block_shape": { "dtype": "uint32", "shape": [2], "data": { "kind": "values", "values": [1, 1] } }
},
"outputs": { "output": { "dtype": "float32", "shape": [1, 32, 512, 512] } },
"bench": { "metrics": [{ "type": "bandwidth", "value": "(numel(shapes.input) + numel(shapes.output)) * 4" }] }
},
{
"name": "nchw_k1x1_copy_baseline",
"preset": "smoke",
"attrs": {},
"inputs": {
"input": { "dtype": "float32", "shape": [1, 16, 262144], "dist": "normal", "seed": 413, "scale": 0.2 },
"image_shape": { "dtype": "uint32", "shape": [2], "data": { "kind": "values", "values": [512, 512] } },
"block_shape": { "dtype": "uint32", "shape": [2], "data": { "kind": "values", "values": [1, 1] } }
},
"outputs": { "output": { "dtype": "float32", "shape": [1, 16, 512, 512] } },
"bench": { "metrics": [{ "type": "bandwidth", "value": "(numel(shapes.input) + numel(shapes.output)) * 4" }] }
},
{
"name": "nchw-k1-fold-f32-b1c320-128x128-diffusion-feature",
"preset": "stress",
"attrs": {},
"inputs": {
"input": { "dtype": "float32", "shape": [1, 320, 16384], "dist": "normal", "seed": 416, "scale": 0.2 },
"image_shape": { "dtype": "uint32", "shape": [2], "data": { "kind": "values", "values": [128, 128] } },
"block_shape": { "dtype": "uint32", "shape": [2], "data": { "kind": "values", "values": [1, 1] } }
},
"outputs": { "output": { "dtype": "float32", "shape": [1, 320, 128, 128] } },
"bench": {
"primary": true,
"metrics": [{ "type": "bandwidth", "value": "(numel(shapes.input) + numel(shapes.output)) * 4" }]
}
},
{
"name": "nchw_k5x5_overlap_heavy_gather",
"preset": "stress",
"provenance": {
"notes": "Stress-only capacity case: the overlap-heavy gather declares 409 MiB of GPU-resident tensors."
},
"attrs": {},
"inputs": {
"input": { "dtype": "float32", "shape": [1, 400, 258064], "dist": "normal", "seed": 414, "scale": 0.1 },
"image_shape": { "dtype": "uint32", "shape": [2], "data": { "kind": "values", "values": [512, 512] } },
"block_shape": { "dtype": "uint32", "shape": [2], "data": { "kind": "values", "values": [5, 5] } }
},
"outputs": { "output": { "dtype": "float32", "shape": [1, 16, 512, 512] } },
"bench": { "metrics": [{ "type": "bandwidth", "value": "(numel(shapes.input) + numel(shapes.output)) * 4" }] }
},
{
"name": "ncdhw_3d_2m_copy_variant",
"preset": "smoke",
"attrs": {},
"inputs": {
"input": { "dtype": "float32", "shape": [1, 16, 131072], "dist": "normal", "seed": 415, "scale": 0.2 },
"image_shape": { "dtype": "uint32", "shape": [3], "data": { "kind": "values", "values": [32, 64, 64] } },
"block_shape": { "dtype": "uint32", "shape": [3], "data": { "kind": "values", "values": [1, 1, 1] } }
},
"outputs": { "output": { "dtype": "float32", "shape": [1, 16, 32, 64, 64] } },
"bench": { "metrics": [{ "type": "bandwidth", "value": "(numel(shapes.input) + numel(shapes.output)) * 4" }] }
}
]
}