MUCM_Net / UWaterlooSkinCancer.onnx.provenance.json
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Add ONNX graphs: ACDC.onnx, ACDC.onnx.config.json, ACDC.onnx.provenance.json, BUSI.onnx, BUSI.onnx.config.json, BUSI.onnx.provenance.json, COVIDQUEx.onnx, COVIDQUEx.onnx.config.json, COVIDQUEx.onnx.provenance.json, DRIVE.onnx, DRIVE.onnx.config.json, DRIVE.onnx.provenance.json, KvasirSEG.onnx, KvasirSEG.onnx.config.json, KvasirSEG.onnx.provenance.json, PROMISE12.onnx, PROMISE12.onnx.config.json, PROMISE12.onnx.provenance.json, UWaterlooSkinCancer.onnx, UWaterlooSkinCancer.onnx.config.json, UWaterlooSkinCancer.onnx.provenance.json (tools/hf_onnx_export.py)
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{
"schema": "medotter/graph-provenance/v1",
"source": {
"file": "UWaterlooSkinCancer.pth",
"sha256": "1bd232d6858cd4cd93b7de4fffe93bc4be9351748781f0b33f4f2d44ae4d78b1",
"reference": "UWaterlooSkinCancer.pth",
"model": "MUCM_Net",
"declaration_source": "sidecar",
"declaration": [
{
"file": "UWaterlooSkinCancer.pth.config.json",
"sha256": "0e549a9e05b553b7ed74aae3918d33d3b4586e37d008f8db4313bceafad3303c"
}
],
"float32_vs_float64": {
"shape": [
1,
3,
256,
256
],
"torch": "ok",
"float64": "ok",
"threads": 8,
"max_abs_diff": 0.0008446669509301064,
"scale": 10.65425033074388,
"rel_diff": 7.927981084626268e-05,
"kernel_noise_rel": 0.00011206796546158397
}
},
"graph": {
"kind": "onnx",
"file": "UWaterlooSkinCancer.onnx",
"sha256": "eef8419af916fe0368348a5f2c28c8817a67335c811e2624daa0648d2377da71",
"bytes": 3337352,
"opset": 20,
"dynamic": false,
"reason": "fixed_size",
"input": "image",
"output": "logits",
"input_channel": 3,
"num_classes": 1,
"size": [
256,
256
]
},
"exporter": {
"api": "torch.onnx.export",
"name": "dynamo",
"dynamo": true,
"registered_symbolics": {},
"producer": "pytorch 2.13.0+cpu",
"torch": "2.13.0+cpu",
"onnx": "1.22.0",
"onnxruntime": "1.29.0"
},
"verification_input": {
"kind": "smooth_random_field",
"distribution": "normal",
"coarse_factor": 16,
"min_coarse": 4,
"interpolation": "bilinear",
"align_corners": false,
"seed": 0,
"pixel_domain": "uint8-range smooth field through the declaration's intensity contract",
"pixel_mean": 127.5,
"pixel_std": 45.0,
"through_contract": true
},
"attempts": [
{
"mode": "dynamic",
"exporter": "torchscript",
"outcome": "fell_back",
"reason": "fixed_size",
"error": {
"kind": "export",
"text": "torchscript: SymbolicValueError: Failed to export a node '%387 : Long(device=cpu) = onnx::Gather[axis=0](%384, %386), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.Mamba.MUCM_Net.MUCM_Net.MUCM_Net::inner/model_zoo.Mamba.MUCM_Net.MUCM_Net.OverlapPatchEmbed::patch_embed1 # /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-research/model_zoo/Mamba/MUCM_Net/MUCM_Net.py:781:0 ' (in list node %1387 : int[] = prim::ListConstruct(%387, %392), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.Mamba.MUCM_Net.MUCM_Net.MUCM_Net::inner/model_zoo.Mamba.MUCM_Net.MUCM_Net.UCMBlock::block_0_1.0/model_zoo.Mamba.MUCM_Net.MUCM_Net.DWConv::dwconv ) because it is not constant. Please try to make things (e.g. kernel sizes) static if possible. [Caused by the value '1387 defined in (%1387 : int[] = prim::ListConstruct(%387, %392), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.Mamba.MUCM_Net.MUCM_Net.MUCM_Net::inner/model_zoo.Mamba.MUCM_Net.MUCM_Net.UCMBlock::block_0_1.0/model_zoo.Mamba.MUCM_Net.MUCM_Net.DWConv::dwconv )' (type 'List[int]') in the TorchScript graph. The containing node has kind 'prim::ListConstruct'.] Inputs: #0: 387 defined in (%387 : Long(device=cpu) = onnx::Gather[axis=0](%384, %386), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.Mamba.MUCM_Net.MUCM_Net.MUCM_Net::inner/model_zoo.Mamba.MUCM_Net.MUCM_Net.OverlapPatchEmbed::patch_embed1 # /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-research/model_zoo/Mamba/MUCM_Net/MUCM_Net.py:781:0 ) (type 'Tensor') #1: 392 defined in (%392 : Long(device=cpu) = onnx::Gather[axis=0](%389, %391), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.Mamba.MUCM_Net.MUCM_Net.MUCM_Net::inner/model_zoo.Mamba.MUCM_Net.MUCM_Net.OverlapPatchEmbed::patch_embed1 # /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-research/model_zoo/Mamba/MUCM_Net/MUCM_Net.py:781:0 ) (type 'Tensor') Outputs: #0: 1387 defined in (%1387 : int[] = prim::ListConstruct(%387, %392), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.Mamba.MUCM_Net.MUCM_Net.MUCM_Net::inner/model_zoo.Mamba.MUCM_Net.MUCM_Net.UCMBlock::block_0_1.0/model_zoo.Mamba.MUCM_Net.MUCM_Net.DWConv::dwconv ) (type 'List[int]')"
},
"verification": null
},
{
"mode": "static",
"exporter": "dynamo",
"outcome": "kept",
"reason": "fixed_size",
"error": null,
"verification": [
{
"shape": [
1,
3,
256,
256
],
"torch": "ok",
"graph": "ok",
"max_abs_diff": 0.002537250518798828,
"scale": 10.654251098632812,
"rel_diff": 0.00023814442660586592
}
]
}
],
"verification": [
{
"shape": [
1,
3,
256,
256
],
"torch": "ok",
"graph": "ok",
"max_abs_diff": 0.002537250518798828,
"scale": 10.654251098632812,
"rel_diff": 0.00023814442660586592
}
],
"exported_at": "2026-09-10T02:32:33+00:00",
"release": {
"repo": "MedOtter/MUCM_Net",
"revision": "097c6945bab2c6261eb6b560da6a9d13f6239a5e",
"pth_file": "UWaterlooSkinCancer.pth",
"pth_sha256": "1bd232d6858cd4cd93b7de4fffe93bc4be9351748781f0b33f4f2d44ae4d78b1",
"sidecar_sha256": "402e4863796b2530120ab02b07d1cb1732e28237a9d98398dec1bbc4a73d5594",
"sidecar_source": "hub",
"group": "checkout_only",
"reason": "fixed_size",
"dynamic_attempt": null,
"reference_check": {
"dataset": "UWaterlooSkinCancer",
"split": "val",
"samples": 4,
"reproducible": true,
"status": "pass",
"sizes": [
{
"size": [
256,
256
],
"predict_masks_equal": 4,
"pixels": 262144,
"disagreeing_pixels": 1,
"unexplained_pixels": 0,
"max_abs_diff": 0.0034743547439575195,
"scale": 10.639901161193848,
"rel_diff": 0.000326540133345344,
"float32_vs_float64": {
"max_abs_diff": 0.0015327125308051137,
"scale": 10.639901807602508,
"rel_diff": 0.00014405325899811855,
"samples": 4,
"of": 4,
"complete": true
}
}
]
},
"tool": "tools/hf_onnx_export.py",
"stamped_at": "2026-09-10T02:33:14+00:00"
}
}