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, ISIC2018.onnx, ISIC2018.onnx.config.json, ISIC2018.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)
Browse files- ACDC.onnx +3 -0
- ACDC.onnx.config.json +16 -0
- ACDC.onnx.provenance.json +158 -0
- BUSI.onnx +3 -0
- BUSI.onnx.config.json +30 -0
- BUSI.onnx.provenance.json +158 -0
- COVIDQUEx.onnx +3 -0
- COVIDQUEx.onnx.config.json +30 -0
- COVIDQUEx.onnx.provenance.json +158 -0
- DRIVE.onnx +3 -0
- DRIVE.onnx.config.json +30 -0
- DRIVE.onnx.provenance.json +158 -0
- ISIC2018.onnx +3 -0
- ISIC2018.onnx.config.json +30 -0
- ISIC2018.onnx.provenance.json +158 -0
- PROMISE12.onnx +3 -0
- PROMISE12.onnx.config.json +30 -0
- PROMISE12.onnx.provenance.json +158 -0
- UWaterlooSkinCancer.onnx +3 -0
- UWaterlooSkinCancer.onnx.config.json +30 -0
- UWaterlooSkinCancer.onnx.provenance.json +158 -0
ACDC.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0fa5430510c208c720f5d999cd83159b233a3e3a8463cee2ede49235da956512
|
| 3 |
+
size 347258266
|
ACDC.onnx.config.json
ADDED
|
@@ -0,0 +1,16 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"schema": "medotter/model-sidecar/v1",
|
| 3 |
+
"model": {
|
| 4 |
+
"graph": "onnx",
|
| 5 |
+
"args": {
|
| 6 |
+
"input_channel": 3,
|
| 7 |
+
"num_classes": 4
|
| 8 |
+
}
|
| 9 |
+
},
|
| 10 |
+
"inference": {
|
| 11 |
+
"size": [
|
| 12 |
+
256,
|
| 13 |
+
256
|
| 14 |
+
]
|
| 15 |
+
}
|
| 16 |
+
}
|
ACDC.onnx.provenance.json
ADDED
|
@@ -0,0 +1,158 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"schema": "medotter/graph-provenance/v1",
|
| 3 |
+
"source": {
|
| 4 |
+
"file": "ACDC.pth",
|
| 5 |
+
"sha256": "d07c4bce8b4fe6f8868c31fa82620de7cdd6d5f2de04b13d1f44a0427c2a603b",
|
| 6 |
+
"reference": "ACDC.pth",
|
| 7 |
+
"model": "MFMSNet",
|
| 8 |
+
"declaration_source": "sidecar",
|
| 9 |
+
"declaration": [
|
| 10 |
+
{
|
| 11 |
+
"file": "ACDC.pth.config.json",
|
| 12 |
+
"sha256": "c8ff5addcce9ddec8226fafab5fd866c9b29df1543039376259990fc4bf706c9"
|
| 13 |
+
}
|
| 14 |
+
],
|
| 15 |
+
"float32_vs_float64": {
|
| 16 |
+
"shape": [
|
| 17 |
+
1,
|
| 18 |
+
3,
|
| 19 |
+
256,
|
| 20 |
+
256
|
| 21 |
+
],
|
| 22 |
+
"torch": "ok",
|
| 23 |
+
"float64": "ok",
|
| 24 |
+
"threads": 6,
|
| 25 |
+
"max_abs_diff": 1.222852213711434e-05,
|
| 26 |
+
"scale": 14.029687815299587,
|
| 27 |
+
"rel_diff": 8.716175511602582e-07
|
| 28 |
+
}
|
| 29 |
+
},
|
| 30 |
+
"graph": {
|
| 31 |
+
"kind": "onnx",
|
| 32 |
+
"file": "ACDC.onnx",
|
| 33 |
+
"sha256": "0fa5430510c208c720f5d999cd83159b233a3e3a8463cee2ede49235da956512",
|
| 34 |
+
"bytes": 347258266,
|
| 35 |
+
"opset": 20,
|
| 36 |
+
"dynamic": false,
|
| 37 |
+
"reason": "dynamic_export_error",
|
| 38 |
+
"input": "image",
|
| 39 |
+
"output": "logits",
|
| 40 |
+
"input_channel": 3,
|
| 41 |
+
"num_classes": 4,
|
| 42 |
+
"size": [
|
| 43 |
+
256,
|
| 44 |
+
256
|
| 45 |
+
]
|
| 46 |
+
},
|
| 47 |
+
"exporter": {
|
| 48 |
+
"api": "torch.onnx.export",
|
| 49 |
+
"name": "dynamo",
|
| 50 |
+
"dynamo": true,
|
| 51 |
+
"registered_symbolics": {},
|
| 52 |
+
"producer": "pytorch 2.13.0+cpu",
|
| 53 |
+
"torch": "2.13.0+cpu",
|
| 54 |
+
"onnx": "1.22.0",
|
| 55 |
+
"onnxruntime": "1.29.0"
|
| 56 |
+
},
|
| 57 |
+
"verification_input": {
|
| 58 |
+
"kind": "smooth_random_field",
|
| 59 |
+
"distribution": "normal",
|
| 60 |
+
"coarse_factor": 16,
|
| 61 |
+
"min_coarse": 4,
|
| 62 |
+
"interpolation": "bilinear",
|
| 63 |
+
"align_corners": false,
|
| 64 |
+
"seed": 0
|
| 65 |
+
},
|
| 66 |
+
"attempts": [
|
| 67 |
+
{
|
| 68 |
+
"mode": "dynamic",
|
| 69 |
+
"exporter": "torchscript",
|
| 70 |
+
"outcome": "fell_back",
|
| 71 |
+
"reason": "dynamic_export_error",
|
| 72 |
+
"error": {
|
| 73 |
+
"kind": "export",
|
| 74 |
+
"text": "torchscript: SymbolicValueError: Unsupported: ONNX export of operator adaptive_avg_pool2d, input size not accessible. Please feel free to request support or submit a pull request on PyTorch GitHub: https://github.com/pytorch/pytorch/issues [Caused by the value '1101 defined in (%1101 : Float(*, 256, *, *, strides=[65536, 256, 16, 1], requires_grad=1, device=cpu) = onnx::Relu(%input.444), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.CNN.IS2D_models.mfmsnet.MFMSNet::inner/model_zoo.CNN.IS2D_models.mfmsnet.UpsampleBlock::decoder_stage1/model_zoo.CNN.IS2D_models.mfmsnet.MFMSAttentionBlock::attention_layer/torch.nn.modules.container.Sequential::multi_scale_branches.0/torch.nn.modules.activation.ReLU::multi_scale_branches.0.5 # /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py:1769:0 )' (type 'Tensor') in the TorchScript graph. The containing node has kind 'onnx::Relu'.] (node defined in /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py(1769): relu /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/activation.py(143): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/container.py(253): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/model_zoo/CNN/IS2D_models/mfmsnet.py(171): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/model_zoo/CNN/IS2D_models/mfmsnet.py(211): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/model_zoo/CNN/IS2D_models/mfmsnet.py(305): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(726): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/jit/_trace.py(131): wrapper /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/jit/_trace.py(140): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/jit/_trace.py(1439): _get_trace_graph /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(898): _trace_and_get_graph_from_model /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(992): _create_jit_graph /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(1108): _model_to_graph /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(1510): _export /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(547): export /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/__init__.py(334): export /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(774): _export_onnx /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1123): attempt /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1160): cmd_export /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1271): main /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1275): <module> <frozen runpy>(88): _run_code <frozen runpy>(198): _run_module_as_main ) Inputs: #0: input.444 defined in (%input.444 : Float(*, 256, *, *, strides=[65536, 256, 16, 1], requires_grad=1, device=cpu) = onnx::BatchNormalization[epsilon=1.0000000000000001e-05, momentum=0.90000000000000002, training_mode=0](%input.440, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.weight, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.bias, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.running_mean, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.running_var), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.CNN.IS2D_models.mfmsnet.MFMSNet::inner/model_zoo.CNN.IS2D_models.mfmsnet.UpsampleBlock::decoder_stage1/model_zoo.CNN.IS2D_models.mfmsnet.MFMSAttentionBlock::attention_layer/torch.nn.modules.container.Sequential::multi_scale_branches.0/torch.nn.modules.batchnorm.BatchNorm2d::multi_scale_branches.0.4 # /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py:2898:0 ) (type 'Tensor') Outputs: #0: 1101 defined in (%1101 : Float(*, 256, *, *, strides=[65536, 256, 16, 1], requires_grad=1, device=cpu) = onnx::Relu(%input.444), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.CNN.IS2D_models.mfmsnet.MFMSNet::inner/model_zoo.CNN.IS2D_models.mfmsnet.UpsampleBlock::decoder_stage1/model_zoo.CNN.IS2D_models.mfmsnet.MFMSAttentionBlock::attention_layer/torch.nn.modules.container.Sequential::multi_scale_branches.0/torch.nn.modules.activation.ReLU::multi_scale_branches.0.5 # /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py:1769:0 ) (type 'Tensor')"
|
| 75 |
+
},
|
| 76 |
+
"verification": null
|
| 77 |
+
},
|
| 78 |
+
{
|
| 79 |
+
"mode": "static",
|
| 80 |
+
"exporter": "dynamo",
|
| 81 |
+
"outcome": "kept",
|
| 82 |
+
"reason": "dynamic_export_error",
|
| 83 |
+
"error": null,
|
| 84 |
+
"verification": [
|
| 85 |
+
{
|
| 86 |
+
"shape": [
|
| 87 |
+
1,
|
| 88 |
+
3,
|
| 89 |
+
256,
|
| 90 |
+
256
|
| 91 |
+
],
|
| 92 |
+
"torch": "ok",
|
| 93 |
+
"graph": "ok",
|
| 94 |
+
"max_abs_diff": 8.58306884765625e-06,
|
| 95 |
+
"scale": 14.029688835144043,
|
| 96 |
+
"rel_diff": 6.117789887225341e-07
|
| 97 |
+
}
|
| 98 |
+
]
|
| 99 |
+
}
|
| 100 |
+
],
|
| 101 |
+
"verification": [
|
| 102 |
+
{
|
| 103 |
+
"shape": [
|
| 104 |
+
1,
|
| 105 |
+
3,
|
| 106 |
+
256,
|
| 107 |
+
256
|
| 108 |
+
],
|
| 109 |
+
"torch": "ok",
|
| 110 |
+
"graph": "ok",
|
| 111 |
+
"max_abs_diff": 8.58306884765625e-06,
|
| 112 |
+
"scale": 14.029688835144043,
|
| 113 |
+
"rel_diff": 6.117789887225341e-07
|
| 114 |
+
}
|
| 115 |
+
],
|
| 116 |
+
"exported_at": "2026-09-07T16:01:41+00:00",
|
| 117 |
+
"release": {
|
| 118 |
+
"repo": "MedOtter/MFMSNet",
|
| 119 |
+
"revision": "0f4ed1a62fb8c0c88fc30a511a7ca0a2bf6124ea",
|
| 120 |
+
"pth_file": "ACDC.pth",
|
| 121 |
+
"pth_sha256": "d07c4bce8b4fe6f8868c31fa82620de7cdd6d5f2de04b13d1f44a0427c2a603b",
|
| 122 |
+
"sidecar_sha256": "9867fc324419b3f483f4f5b56708a3271f503d4c68bf7fdb4c768189884baefb",
|
| 123 |
+
"sidecar_source": "existing",
|
| 124 |
+
"group": "checkout_only",
|
| 125 |
+
"reference_check": {
|
| 126 |
+
"dataset": "ACDC",
|
| 127 |
+
"split": "test",
|
| 128 |
+
"samples": 4,
|
| 129 |
+
"reproducible": true,
|
| 130 |
+
"status": "pass",
|
| 131 |
+
"sizes": [
|
| 132 |
+
{
|
| 133 |
+
"size": [
|
| 134 |
+
256,
|
| 135 |
+
256
|
| 136 |
+
],
|
| 137 |
+
"predict_masks_equal": 4,
|
| 138 |
+
"pixels": 262144,
|
| 139 |
+
"disagreeing_pixels": 0,
|
| 140 |
+
"unexplained_pixels": 0,
|
| 141 |
+
"max_abs_diff": 0.000293731689453125,
|
| 142 |
+
"scale": 231.98648071289062,
|
| 143 |
+
"rel_diff": 1.2661586509286763e-06,
|
| 144 |
+
"float32_vs_float64": {
|
| 145 |
+
"max_abs_diff": 0.0007090725917748841,
|
| 146 |
+
"scale": 231.9865492799054,
|
| 147 |
+
"rel_diff": 3.056524587205038e-06,
|
| 148 |
+
"samples": 4,
|
| 149 |
+
"of": 4,
|
| 150 |
+
"complete": true
|
| 151 |
+
}
|
| 152 |
+
}
|
| 153 |
+
]
|
| 154 |
+
},
|
| 155 |
+
"tool": "tools/hf_onnx_export.py",
|
| 156 |
+
"stamped_at": "2026-09-07T16:02:09+00:00"
|
| 157 |
+
}
|
| 158 |
+
}
|
BUSI.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:215f51d7f50c215180adcdd1a39d3c08bdcf90465801c3ee046d8f3fa7e5133c
|
| 3 |
+
size 347257078
|
BUSI.onnx.config.json
ADDED
|
@@ -0,0 +1,30 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"schema": "medotter/model-sidecar/v1",
|
| 3 |
+
"model": {
|
| 4 |
+
"graph": "onnx",
|
| 5 |
+
"args": {
|
| 6 |
+
"input_channel": 3,
|
| 7 |
+
"num_classes": 1
|
| 8 |
+
}
|
| 9 |
+
},
|
| 10 |
+
"inference": {
|
| 11 |
+
"normalize": {
|
| 12 |
+
"mean": [
|
| 13 |
+
0.485,
|
| 14 |
+
0.456,
|
| 15 |
+
0.406
|
| 16 |
+
],
|
| 17 |
+
"std": [
|
| 18 |
+
58.395,
|
| 19 |
+
57.12,
|
| 20 |
+
57.375
|
| 21 |
+
]
|
| 22 |
+
},
|
| 23 |
+
"scale": 255.0,
|
| 24 |
+
"size": [
|
| 25 |
+
256,
|
| 26 |
+
256
|
| 27 |
+
],
|
| 28 |
+
"threshold": 0.5
|
| 29 |
+
}
|
| 30 |
+
}
|
BUSI.onnx.provenance.json
ADDED
|
@@ -0,0 +1,158 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"schema": "medotter/graph-provenance/v1",
|
| 3 |
+
"source": {
|
| 4 |
+
"file": "BUSI.pth",
|
| 5 |
+
"sha256": "b7740000438844f44eb646f8499d05f8848d056e5d6b3cb22bb6550de450650c",
|
| 6 |
+
"reference": "BUSI.pth",
|
| 7 |
+
"model": "MFMSNet",
|
| 8 |
+
"declaration_source": "sidecar",
|
| 9 |
+
"declaration": [
|
| 10 |
+
{
|
| 11 |
+
"file": "BUSI.pth.config.json",
|
| 12 |
+
"sha256": "6e19b4d8047bc7af8152f87db8170b2824a31ddb20e67430bd36fd5e24d331e9"
|
| 13 |
+
}
|
| 14 |
+
],
|
| 15 |
+
"float32_vs_float64": {
|
| 16 |
+
"shape": [
|
| 17 |
+
1,
|
| 18 |
+
3,
|
| 19 |
+
256,
|
| 20 |
+
256
|
| 21 |
+
],
|
| 22 |
+
"torch": "ok",
|
| 23 |
+
"float64": "ok",
|
| 24 |
+
"threads": 6,
|
| 25 |
+
"max_abs_diff": 0.0015352713321590272,
|
| 26 |
+
"scale": 2397.571431429128,
|
| 27 |
+
"rel_diff": 6.403443551393558e-07
|
| 28 |
+
}
|
| 29 |
+
},
|
| 30 |
+
"graph": {
|
| 31 |
+
"kind": "onnx",
|
| 32 |
+
"file": "BUSI.onnx",
|
| 33 |
+
"sha256": "215f51d7f50c215180adcdd1a39d3c08bdcf90465801c3ee046d8f3fa7e5133c",
|
| 34 |
+
"bytes": 347257078,
|
| 35 |
+
"opset": 20,
|
| 36 |
+
"dynamic": false,
|
| 37 |
+
"reason": "dynamic_export_error",
|
| 38 |
+
"input": "image",
|
| 39 |
+
"output": "logits",
|
| 40 |
+
"input_channel": 3,
|
| 41 |
+
"num_classes": 1,
|
| 42 |
+
"size": [
|
| 43 |
+
256,
|
| 44 |
+
256
|
| 45 |
+
]
|
| 46 |
+
},
|
| 47 |
+
"exporter": {
|
| 48 |
+
"api": "torch.onnx.export",
|
| 49 |
+
"name": "dynamo",
|
| 50 |
+
"dynamo": true,
|
| 51 |
+
"registered_symbolics": {},
|
| 52 |
+
"producer": "pytorch 2.13.0+cpu",
|
| 53 |
+
"torch": "2.13.0+cpu",
|
| 54 |
+
"onnx": "1.22.0",
|
| 55 |
+
"onnxruntime": "1.29.0"
|
| 56 |
+
},
|
| 57 |
+
"verification_input": {
|
| 58 |
+
"kind": "smooth_random_field",
|
| 59 |
+
"distribution": "normal",
|
| 60 |
+
"coarse_factor": 16,
|
| 61 |
+
"min_coarse": 4,
|
| 62 |
+
"interpolation": "bilinear",
|
| 63 |
+
"align_corners": false,
|
| 64 |
+
"seed": 0
|
| 65 |
+
},
|
| 66 |
+
"attempts": [
|
| 67 |
+
{
|
| 68 |
+
"mode": "dynamic",
|
| 69 |
+
"exporter": "torchscript",
|
| 70 |
+
"outcome": "fell_back",
|
| 71 |
+
"reason": "dynamic_export_error",
|
| 72 |
+
"error": {
|
| 73 |
+
"kind": "export",
|
| 74 |
+
"text": "torchscript: SymbolicValueError: Unsupported: ONNX export of operator adaptive_avg_pool2d, input size not accessible. Please feel free to request support or submit a pull request on PyTorch GitHub: https://github.com/pytorch/pytorch/issues [Caused by the value '1101 defined in (%1101 : Float(*, 256, *, *, strides=[65536, 256, 16, 1], requires_grad=1, device=cpu) = onnx::Relu(%input.444), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.CNN.IS2D_models.mfmsnet.MFMSNet::inner/model_zoo.CNN.IS2D_models.mfmsnet.UpsampleBlock::decoder_stage1/model_zoo.CNN.IS2D_models.mfmsnet.MFMSAttentionBlock::attention_layer/torch.nn.modules.container.Sequential::multi_scale_branches.0/torch.nn.modules.activation.ReLU::multi_scale_branches.0.5 # /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py:1769:0 )' (type 'Tensor') in the TorchScript graph. The containing node has kind 'onnx::Relu'.] (node defined in /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py(1769): relu /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/activation.py(143): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/container.py(253): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/model_zoo/CNN/IS2D_models/mfmsnet.py(171): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/model_zoo/CNN/IS2D_models/mfmsnet.py(211): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/model_zoo/CNN/IS2D_models/mfmsnet.py(305): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(726): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/jit/_trace.py(131): wrapper /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/jit/_trace.py(140): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/jit/_trace.py(1439): _get_trace_graph /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(898): _trace_and_get_graph_from_model /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(992): _create_jit_graph /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(1108): _model_to_graph /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(1510): _export /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(547): export /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/__init__.py(334): export /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(774): _export_onnx /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1123): attempt /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1160): cmd_export /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1271): main /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1275): <module> <frozen runpy>(88): _run_code <frozen runpy>(198): _run_module_as_main ) Inputs: #0: input.444 defined in (%input.444 : Float(*, 256, *, *, strides=[65536, 256, 16, 1], requires_grad=1, device=cpu) = onnx::BatchNormalization[epsilon=1.0000000000000001e-05, momentum=0.90000000000000002, training_mode=0](%input.440, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.weight, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.bias, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.running_mean, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.running_var), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.CNN.IS2D_models.mfmsnet.MFMSNet::inner/model_zoo.CNN.IS2D_models.mfmsnet.UpsampleBlock::decoder_stage1/model_zoo.CNN.IS2D_models.mfmsnet.MFMSAttentionBlock::attention_layer/torch.nn.modules.container.Sequential::multi_scale_branches.0/torch.nn.modules.batchnorm.BatchNorm2d::multi_scale_branches.0.4 # /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py:2898:0 ) (type 'Tensor') Outputs: #0: 1101 defined in (%1101 : Float(*, 256, *, *, strides=[65536, 256, 16, 1], requires_grad=1, device=cpu) = onnx::Relu(%input.444), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.CNN.IS2D_models.mfmsnet.MFMSNet::inner/model_zoo.CNN.IS2D_models.mfmsnet.UpsampleBlock::decoder_stage1/model_zoo.CNN.IS2D_models.mfmsnet.MFMSAttentionBlock::attention_layer/torch.nn.modules.container.Sequential::multi_scale_branches.0/torch.nn.modules.activation.ReLU::multi_scale_branches.0.5 # /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py:1769:0 ) (type 'Tensor')"
|
| 75 |
+
},
|
| 76 |
+
"verification": null
|
| 77 |
+
},
|
| 78 |
+
{
|
| 79 |
+
"mode": "static",
|
| 80 |
+
"exporter": "dynamo",
|
| 81 |
+
"outcome": "kept",
|
| 82 |
+
"reason": "dynamic_export_error",
|
| 83 |
+
"error": null,
|
| 84 |
+
"verification": [
|
| 85 |
+
{
|
| 86 |
+
"shape": [
|
| 87 |
+
1,
|
| 88 |
+
3,
|
| 89 |
+
256,
|
| 90 |
+
256
|
| 91 |
+
],
|
| 92 |
+
"torch": "ok",
|
| 93 |
+
"graph": "ok",
|
| 94 |
+
"max_abs_diff": 0.0010986328125,
|
| 95 |
+
"scale": 2397.5712890625,
|
| 96 |
+
"rel_diff": 4.5822738098002005e-07
|
| 97 |
+
}
|
| 98 |
+
]
|
| 99 |
+
}
|
| 100 |
+
],
|
| 101 |
+
"verification": [
|
| 102 |
+
{
|
| 103 |
+
"shape": [
|
| 104 |
+
1,
|
| 105 |
+
3,
|
| 106 |
+
256,
|
| 107 |
+
256
|
| 108 |
+
],
|
| 109 |
+
"torch": "ok",
|
| 110 |
+
"graph": "ok",
|
| 111 |
+
"max_abs_diff": 0.0010986328125,
|
| 112 |
+
"scale": 2397.5712890625,
|
| 113 |
+
"rel_diff": 4.5822738098002005e-07
|
| 114 |
+
}
|
| 115 |
+
],
|
| 116 |
+
"exported_at": "2026-09-07T16:01:38+00:00",
|
| 117 |
+
"release": {
|
| 118 |
+
"repo": "MedOtter/MFMSNet",
|
| 119 |
+
"revision": "0f4ed1a62fb8c0c88fc30a511a7ca0a2bf6124ea",
|
| 120 |
+
"pth_file": "BUSI.pth",
|
| 121 |
+
"pth_sha256": "b7740000438844f44eb646f8499d05f8848d056e5d6b3cb22bb6550de450650c",
|
| 122 |
+
"sidecar_sha256": "402e4863796b2530120ab02b07d1cb1732e28237a9d98398dec1bbc4a73d5594",
|
| 123 |
+
"sidecar_source": "existing",
|
| 124 |
+
"group": "checkout_only",
|
| 125 |
+
"reference_check": {
|
| 126 |
+
"dataset": "BUSI",
|
| 127 |
+
"split": "train",
|
| 128 |
+
"samples": 4,
|
| 129 |
+
"reproducible": true,
|
| 130 |
+
"status": "pass",
|
| 131 |
+
"sizes": [
|
| 132 |
+
{
|
| 133 |
+
"size": [
|
| 134 |
+
256,
|
| 135 |
+
256
|
| 136 |
+
],
|
| 137 |
+
"predict_masks_equal": 4,
|
| 138 |
+
"pixels": 262144,
|
| 139 |
+
"disagreeing_pixels": 0,
|
| 140 |
+
"unexplained_pixels": 0,
|
| 141 |
+
"max_abs_diff": 1.1444091796875e-05,
|
| 142 |
+
"scale": 15.125402450561523,
|
| 143 |
+
"rel_diff": 7.566140361739693e-07,
|
| 144 |
+
"float32_vs_float64": {
|
| 145 |
+
"max_abs_diff": 4.2203342240476616e-05,
|
| 146 |
+
"scale": 15.125402587997666,
|
| 147 |
+
"rel_diff": 2.7902293505870632e-06,
|
| 148 |
+
"samples": 4,
|
| 149 |
+
"of": 4,
|
| 150 |
+
"complete": true
|
| 151 |
+
}
|
| 152 |
+
}
|
| 153 |
+
]
|
| 154 |
+
},
|
| 155 |
+
"tool": "tools/hf_onnx_export.py",
|
| 156 |
+
"stamped_at": "2026-09-07T16:01:59+00:00"
|
| 157 |
+
}
|
| 158 |
+
}
|
COVIDQUEx.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:6e362343d036354405b48f1a6f144033739503f595fdc35a56fdd3de630fcb08
|
| 3 |
+
size 347257078
|
COVIDQUEx.onnx.config.json
ADDED
|
@@ -0,0 +1,30 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"schema": "medotter/model-sidecar/v1",
|
| 3 |
+
"model": {
|
| 4 |
+
"graph": "onnx",
|
| 5 |
+
"args": {
|
| 6 |
+
"input_channel": 3,
|
| 7 |
+
"num_classes": 1
|
| 8 |
+
}
|
| 9 |
+
},
|
| 10 |
+
"inference": {
|
| 11 |
+
"normalize": {
|
| 12 |
+
"mean": [
|
| 13 |
+
0.485,
|
| 14 |
+
0.456,
|
| 15 |
+
0.406
|
| 16 |
+
],
|
| 17 |
+
"std": [
|
| 18 |
+
58.395,
|
| 19 |
+
57.12,
|
| 20 |
+
57.375
|
| 21 |
+
]
|
| 22 |
+
},
|
| 23 |
+
"scale": 255.0,
|
| 24 |
+
"size": [
|
| 25 |
+
256,
|
| 26 |
+
256
|
| 27 |
+
],
|
| 28 |
+
"threshold": 0.5
|
| 29 |
+
}
|
| 30 |
+
}
|
COVIDQUEx.onnx.provenance.json
ADDED
|
@@ -0,0 +1,158 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"schema": "medotter/graph-provenance/v1",
|
| 3 |
+
"source": {
|
| 4 |
+
"file": "COVIDQUEx.pth",
|
| 5 |
+
"sha256": "97ebc9a48e2b12b8da90feeddc3e07e66292a1650d857b5b681385283207fab5",
|
| 6 |
+
"reference": "COVIDQUEx.pth",
|
| 7 |
+
"model": "MFMSNet",
|
| 8 |
+
"declaration_source": "sidecar",
|
| 9 |
+
"declaration": [
|
| 10 |
+
{
|
| 11 |
+
"file": "COVIDQUEx.pth.config.json",
|
| 12 |
+
"sha256": "6e19b4d8047bc7af8152f87db8170b2824a31ddb20e67430bd36fd5e24d331e9"
|
| 13 |
+
}
|
| 14 |
+
],
|
| 15 |
+
"float32_vs_float64": {
|
| 16 |
+
"shape": [
|
| 17 |
+
1,
|
| 18 |
+
3,
|
| 19 |
+
256,
|
| 20 |
+
256
|
| 21 |
+
],
|
| 22 |
+
"torch": "ok",
|
| 23 |
+
"float64": "ok",
|
| 24 |
+
"threads": 6,
|
| 25 |
+
"max_abs_diff": 0.0015574603983168345,
|
| 26 |
+
"scale": 724.9438961383603,
|
| 27 |
+
"rel_diff": 2.148387491243299e-06
|
| 28 |
+
}
|
| 29 |
+
},
|
| 30 |
+
"graph": {
|
| 31 |
+
"kind": "onnx",
|
| 32 |
+
"file": "COVIDQUEx.onnx",
|
| 33 |
+
"sha256": "6e362343d036354405b48f1a6f144033739503f595fdc35a56fdd3de630fcb08",
|
| 34 |
+
"bytes": 347257078,
|
| 35 |
+
"opset": 20,
|
| 36 |
+
"dynamic": false,
|
| 37 |
+
"reason": "dynamic_export_error",
|
| 38 |
+
"input": "image",
|
| 39 |
+
"output": "logits",
|
| 40 |
+
"input_channel": 3,
|
| 41 |
+
"num_classes": 1,
|
| 42 |
+
"size": [
|
| 43 |
+
256,
|
| 44 |
+
256
|
| 45 |
+
]
|
| 46 |
+
},
|
| 47 |
+
"exporter": {
|
| 48 |
+
"api": "torch.onnx.export",
|
| 49 |
+
"name": "dynamo",
|
| 50 |
+
"dynamo": true,
|
| 51 |
+
"registered_symbolics": {},
|
| 52 |
+
"producer": "pytorch 2.13.0+cpu",
|
| 53 |
+
"torch": "2.13.0+cpu",
|
| 54 |
+
"onnx": "1.22.0",
|
| 55 |
+
"onnxruntime": "1.29.0"
|
| 56 |
+
},
|
| 57 |
+
"verification_input": {
|
| 58 |
+
"kind": "smooth_random_field",
|
| 59 |
+
"distribution": "normal",
|
| 60 |
+
"coarse_factor": 16,
|
| 61 |
+
"min_coarse": 4,
|
| 62 |
+
"interpolation": "bilinear",
|
| 63 |
+
"align_corners": false,
|
| 64 |
+
"seed": 0
|
| 65 |
+
},
|
| 66 |
+
"attempts": [
|
| 67 |
+
{
|
| 68 |
+
"mode": "dynamic",
|
| 69 |
+
"exporter": "torchscript",
|
| 70 |
+
"outcome": "fell_back",
|
| 71 |
+
"reason": "dynamic_export_error",
|
| 72 |
+
"error": {
|
| 73 |
+
"kind": "export",
|
| 74 |
+
"text": "torchscript: SymbolicValueError: Unsupported: ONNX export of operator adaptive_avg_pool2d, input size not accessible. Please feel free to request support or submit a pull request on PyTorch GitHub: https://github.com/pytorch/pytorch/issues [Caused by the value '1101 defined in (%1101 : Float(*, 256, *, *, strides=[65536, 256, 16, 1], requires_grad=1, device=cpu) = onnx::Relu(%input.444), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.CNN.IS2D_models.mfmsnet.MFMSNet::inner/model_zoo.CNN.IS2D_models.mfmsnet.UpsampleBlock::decoder_stage1/model_zoo.CNN.IS2D_models.mfmsnet.MFMSAttentionBlock::attention_layer/torch.nn.modules.container.Sequential::multi_scale_branches.0/torch.nn.modules.activation.ReLU::multi_scale_branches.0.5 # /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py:1769:0 )' (type 'Tensor') in the TorchScript graph. The containing node has kind 'onnx::Relu'.] (node defined in /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py(1769): relu /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/activation.py(143): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/container.py(253): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/model_zoo/CNN/IS2D_models/mfmsnet.py(171): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/model_zoo/CNN/IS2D_models/mfmsnet.py(211): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/model_zoo/CNN/IS2D_models/mfmsnet.py(305): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(726): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/jit/_trace.py(131): wrapper /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/jit/_trace.py(140): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/jit/_trace.py(1439): _get_trace_graph /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(898): _trace_and_get_graph_from_model /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(992): _create_jit_graph /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(1108): _model_to_graph /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(1510): _export /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(547): export /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/__init__.py(334): export /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(774): _export_onnx /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1123): attempt /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1160): cmd_export /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1271): main /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1275): <module> <frozen runpy>(88): _run_code <frozen runpy>(198): _run_module_as_main ) Inputs: #0: input.444 defined in (%input.444 : Float(*, 256, *, *, strides=[65536, 256, 16, 1], requires_grad=1, device=cpu) = onnx::BatchNormalization[epsilon=1.0000000000000001e-05, momentum=0.90000000000000002, training_mode=0](%input.440, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.weight, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.bias, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.running_mean, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.running_var), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.CNN.IS2D_models.mfmsnet.MFMSNet::inner/model_zoo.CNN.IS2D_models.mfmsnet.UpsampleBlock::decoder_stage1/model_zoo.CNN.IS2D_models.mfmsnet.MFMSAttentionBlock::attention_layer/torch.nn.modules.container.Sequential::multi_scale_branches.0/torch.nn.modules.batchnorm.BatchNorm2d::multi_scale_branches.0.4 # /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py:2898:0 ) (type 'Tensor') Outputs: #0: 1101 defined in (%1101 : Float(*, 256, *, *, strides=[65536, 256, 16, 1], requires_grad=1, device=cpu) = onnx::Relu(%input.444), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.CNN.IS2D_models.mfmsnet.MFMSNet::inner/model_zoo.CNN.IS2D_models.mfmsnet.UpsampleBlock::decoder_stage1/model_zoo.CNN.IS2D_models.mfmsnet.MFMSAttentionBlock::attention_layer/torch.nn.modules.container.Sequential::multi_scale_branches.0/torch.nn.modules.activation.ReLU::multi_scale_branches.0.5 # /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py:1769:0 ) (type 'Tensor')"
|
| 75 |
+
},
|
| 76 |
+
"verification": null
|
| 77 |
+
},
|
| 78 |
+
{
|
| 79 |
+
"mode": "static",
|
| 80 |
+
"exporter": "dynamo",
|
| 81 |
+
"outcome": "kept",
|
| 82 |
+
"reason": "dynamic_export_error",
|
| 83 |
+
"error": null,
|
| 84 |
+
"verification": [
|
| 85 |
+
{
|
| 86 |
+
"shape": [
|
| 87 |
+
1,
|
| 88 |
+
3,
|
| 89 |
+
256,
|
| 90 |
+
256
|
| 91 |
+
],
|
| 92 |
+
"torch": "ok",
|
| 93 |
+
"graph": "ok",
|
| 94 |
+
"max_abs_diff": 0.0013427734375,
|
| 95 |
+
"scale": 724.94384765625,
|
| 96 |
+
"rel_diff": 1.8522447522538451e-06
|
| 97 |
+
}
|
| 98 |
+
]
|
| 99 |
+
}
|
| 100 |
+
],
|
| 101 |
+
"verification": [
|
| 102 |
+
{
|
| 103 |
+
"shape": [
|
| 104 |
+
1,
|
| 105 |
+
3,
|
| 106 |
+
256,
|
| 107 |
+
256
|
| 108 |
+
],
|
| 109 |
+
"torch": "ok",
|
| 110 |
+
"graph": "ok",
|
| 111 |
+
"max_abs_diff": 0.0013427734375,
|
| 112 |
+
"scale": 724.94384765625,
|
| 113 |
+
"rel_diff": 1.8522447522538451e-06
|
| 114 |
+
}
|
| 115 |
+
],
|
| 116 |
+
"exported_at": "2026-09-07T16:01:43+00:00",
|
| 117 |
+
"release": {
|
| 118 |
+
"repo": "MedOtter/MFMSNet",
|
| 119 |
+
"revision": "0f4ed1a62fb8c0c88fc30a511a7ca0a2bf6124ea",
|
| 120 |
+
"pth_file": "COVIDQUEx.pth",
|
| 121 |
+
"pth_sha256": "97ebc9a48e2b12b8da90feeddc3e07e66292a1650d857b5b681385283207fab5",
|
| 122 |
+
"sidecar_sha256": "402e4863796b2530120ab02b07d1cb1732e28237a9d98398dec1bbc4a73d5594",
|
| 123 |
+
"sidecar_source": "existing",
|
| 124 |
+
"group": "checkout_only",
|
| 125 |
+
"reference_check": {
|
| 126 |
+
"dataset": "COVIDQUEx",
|
| 127 |
+
"split": "val",
|
| 128 |
+
"samples": 4,
|
| 129 |
+
"reproducible": true,
|
| 130 |
+
"status": "pass",
|
| 131 |
+
"sizes": [
|
| 132 |
+
{
|
| 133 |
+
"size": [
|
| 134 |
+
256,
|
| 135 |
+
256
|
| 136 |
+
],
|
| 137 |
+
"predict_masks_equal": 4,
|
| 138 |
+
"pixels": 262144,
|
| 139 |
+
"disagreeing_pixels": 0,
|
| 140 |
+
"unexplained_pixels": 0,
|
| 141 |
+
"max_abs_diff": 7.390975952148438e-05,
|
| 142 |
+
"scale": 14.588199615478516,
|
| 143 |
+
"rel_diff": 5.066407196886991e-06,
|
| 144 |
+
"float32_vs_float64": {
|
| 145 |
+
"max_abs_diff": 5.6213520393200156e-05,
|
| 146 |
+
"scale": 14.588200211235419,
|
| 147 |
+
"rel_diff": 3.853355422823584e-06,
|
| 148 |
+
"samples": 4,
|
| 149 |
+
"of": 4,
|
| 150 |
+
"complete": true
|
| 151 |
+
}
|
| 152 |
+
}
|
| 153 |
+
]
|
| 154 |
+
},
|
| 155 |
+
"tool": "tools/hf_onnx_export.py",
|
| 156 |
+
"stamped_at": "2026-09-07T16:02:15+00:00"
|
| 157 |
+
}
|
| 158 |
+
}
|
DRIVE.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:348a0fd78283e5126d7a836184ca7318fc6d0880cc64625c0c2ba7d2e4acce25
|
| 3 |
+
size 347257078
|
DRIVE.onnx.config.json
ADDED
|
@@ -0,0 +1,30 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"schema": "medotter/model-sidecar/v1",
|
| 3 |
+
"model": {
|
| 4 |
+
"graph": "onnx",
|
| 5 |
+
"args": {
|
| 6 |
+
"input_channel": 3,
|
| 7 |
+
"num_classes": 1
|
| 8 |
+
}
|
| 9 |
+
},
|
| 10 |
+
"inference": {
|
| 11 |
+
"normalize": {
|
| 12 |
+
"mean": [
|
| 13 |
+
0.485,
|
| 14 |
+
0.456,
|
| 15 |
+
0.406
|
| 16 |
+
],
|
| 17 |
+
"std": [
|
| 18 |
+
58.395,
|
| 19 |
+
57.12,
|
| 20 |
+
57.375
|
| 21 |
+
]
|
| 22 |
+
},
|
| 23 |
+
"scale": 255.0,
|
| 24 |
+
"size": [
|
| 25 |
+
256,
|
| 26 |
+
256
|
| 27 |
+
],
|
| 28 |
+
"threshold": 0.5
|
| 29 |
+
}
|
| 30 |
+
}
|
DRIVE.onnx.provenance.json
ADDED
|
@@ -0,0 +1,158 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"schema": "medotter/graph-provenance/v1",
|
| 3 |
+
"source": {
|
| 4 |
+
"file": "DRIVE.pth",
|
| 5 |
+
"sha256": "b090aaa128ff53d10c1bf3938cd6ecac704c35f6fa0db66524daee17ae554a8d",
|
| 6 |
+
"reference": "DRIVE.pth",
|
| 7 |
+
"model": "MFMSNet",
|
| 8 |
+
"declaration_source": "sidecar",
|
| 9 |
+
"declaration": [
|
| 10 |
+
{
|
| 11 |
+
"file": "DRIVE.pth.config.json",
|
| 12 |
+
"sha256": "6e19b4d8047bc7af8152f87db8170b2824a31ddb20e67430bd36fd5e24d331e9"
|
| 13 |
+
}
|
| 14 |
+
],
|
| 15 |
+
"float32_vs_float64": {
|
| 16 |
+
"shape": [
|
| 17 |
+
1,
|
| 18 |
+
3,
|
| 19 |
+
256,
|
| 20 |
+
256
|
| 21 |
+
],
|
| 22 |
+
"torch": "ok",
|
| 23 |
+
"float64": "ok",
|
| 24 |
+
"threads": 6,
|
| 25 |
+
"max_abs_diff": 0.0016424685604192746,
|
| 26 |
+
"scale": 1993.6710321925345,
|
| 27 |
+
"rel_diff": 8.238413127831697e-07
|
| 28 |
+
}
|
| 29 |
+
},
|
| 30 |
+
"graph": {
|
| 31 |
+
"kind": "onnx",
|
| 32 |
+
"file": "DRIVE.onnx",
|
| 33 |
+
"sha256": "348a0fd78283e5126d7a836184ca7318fc6d0880cc64625c0c2ba7d2e4acce25",
|
| 34 |
+
"bytes": 347257078,
|
| 35 |
+
"opset": 20,
|
| 36 |
+
"dynamic": false,
|
| 37 |
+
"reason": "dynamic_export_error",
|
| 38 |
+
"input": "image",
|
| 39 |
+
"output": "logits",
|
| 40 |
+
"input_channel": 3,
|
| 41 |
+
"num_classes": 1,
|
| 42 |
+
"size": [
|
| 43 |
+
256,
|
| 44 |
+
256
|
| 45 |
+
]
|
| 46 |
+
},
|
| 47 |
+
"exporter": {
|
| 48 |
+
"api": "torch.onnx.export",
|
| 49 |
+
"name": "dynamo",
|
| 50 |
+
"dynamo": true,
|
| 51 |
+
"registered_symbolics": {},
|
| 52 |
+
"producer": "pytorch 2.13.0+cpu",
|
| 53 |
+
"torch": "2.13.0+cpu",
|
| 54 |
+
"onnx": "1.22.0",
|
| 55 |
+
"onnxruntime": "1.29.0"
|
| 56 |
+
},
|
| 57 |
+
"verification_input": {
|
| 58 |
+
"kind": "smooth_random_field",
|
| 59 |
+
"distribution": "normal",
|
| 60 |
+
"coarse_factor": 16,
|
| 61 |
+
"min_coarse": 4,
|
| 62 |
+
"interpolation": "bilinear",
|
| 63 |
+
"align_corners": false,
|
| 64 |
+
"seed": 0
|
| 65 |
+
},
|
| 66 |
+
"attempts": [
|
| 67 |
+
{
|
| 68 |
+
"mode": "dynamic",
|
| 69 |
+
"exporter": "torchscript",
|
| 70 |
+
"outcome": "fell_back",
|
| 71 |
+
"reason": "dynamic_export_error",
|
| 72 |
+
"error": {
|
| 73 |
+
"kind": "export",
|
| 74 |
+
"text": "torchscript: SymbolicValueError: Unsupported: ONNX export of operator adaptive_avg_pool2d, input size not accessible. Please feel free to request support or submit a pull request on PyTorch GitHub: https://github.com/pytorch/pytorch/issues [Caused by the value '1101 defined in (%1101 : Float(*, 256, *, *, strides=[65536, 256, 16, 1], requires_grad=1, device=cpu) = onnx::Relu(%input.444), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.CNN.IS2D_models.mfmsnet.MFMSNet::inner/model_zoo.CNN.IS2D_models.mfmsnet.UpsampleBlock::decoder_stage1/model_zoo.CNN.IS2D_models.mfmsnet.MFMSAttentionBlock::attention_layer/torch.nn.modules.container.Sequential::multi_scale_branches.0/torch.nn.modules.activation.ReLU::multi_scale_branches.0.5 # /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py:1769:0 )' (type 'Tensor') in the TorchScript graph. The containing node has kind 'onnx::Relu'.] (node defined in /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py(1769): relu /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/activation.py(143): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/container.py(253): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/model_zoo/CNN/IS2D_models/mfmsnet.py(171): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/model_zoo/CNN/IS2D_models/mfmsnet.py(211): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/model_zoo/CNN/IS2D_models/mfmsnet.py(305): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(726): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/jit/_trace.py(131): wrapper /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/jit/_trace.py(140): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/jit/_trace.py(1439): _get_trace_graph /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(898): _trace_and_get_graph_from_model /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(992): _create_jit_graph /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(1108): _model_to_graph /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(1510): _export /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(547): export /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/__init__.py(334): export /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(774): _export_onnx /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1123): attempt /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1160): cmd_export /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1271): main /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1275): <module> <frozen runpy>(88): _run_code <frozen runpy>(198): _run_module_as_main ) Inputs: #0: input.444 defined in (%input.444 : Float(*, 256, *, *, strides=[65536, 256, 16, 1], requires_grad=1, device=cpu) = onnx::BatchNormalization[epsilon=1.0000000000000001e-05, momentum=0.90000000000000002, training_mode=0](%input.440, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.weight, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.bias, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.running_mean, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.running_var), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.CNN.IS2D_models.mfmsnet.MFMSNet::inner/model_zoo.CNN.IS2D_models.mfmsnet.UpsampleBlock::decoder_stage1/model_zoo.CNN.IS2D_models.mfmsnet.MFMSAttentionBlock::attention_layer/torch.nn.modules.container.Sequential::multi_scale_branches.0/torch.nn.modules.batchnorm.BatchNorm2d::multi_scale_branches.0.4 # /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py:2898:0 ) (type 'Tensor') Outputs: #0: 1101 defined in (%1101 : Float(*, 256, *, *, strides=[65536, 256, 16, 1], requires_grad=1, device=cpu) = onnx::Relu(%input.444), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.CNN.IS2D_models.mfmsnet.MFMSNet::inner/model_zoo.CNN.IS2D_models.mfmsnet.UpsampleBlock::decoder_stage1/model_zoo.CNN.IS2D_models.mfmsnet.MFMSAttentionBlock::attention_layer/torch.nn.modules.container.Sequential::multi_scale_branches.0/torch.nn.modules.activation.ReLU::multi_scale_branches.0.5 # /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py:1769:0 ) (type 'Tensor')"
|
| 75 |
+
},
|
| 76 |
+
"verification": null
|
| 77 |
+
},
|
| 78 |
+
{
|
| 79 |
+
"mode": "static",
|
| 80 |
+
"exporter": "dynamo",
|
| 81 |
+
"outcome": "kept",
|
| 82 |
+
"reason": "dynamic_export_error",
|
| 83 |
+
"error": null,
|
| 84 |
+
"verification": [
|
| 85 |
+
{
|
| 86 |
+
"shape": [
|
| 87 |
+
1,
|
| 88 |
+
3,
|
| 89 |
+
256,
|
| 90 |
+
256
|
| 91 |
+
],
|
| 92 |
+
"torch": "ok",
|
| 93 |
+
"graph": "ok",
|
| 94 |
+
"max_abs_diff": 0.00146484375,
|
| 95 |
+
"scale": 1993.6708984375,
|
| 96 |
+
"rel_diff": 7.347470192538007e-07
|
| 97 |
+
}
|
| 98 |
+
]
|
| 99 |
+
}
|
| 100 |
+
],
|
| 101 |
+
"verification": [
|
| 102 |
+
{
|
| 103 |
+
"shape": [
|
| 104 |
+
1,
|
| 105 |
+
3,
|
| 106 |
+
256,
|
| 107 |
+
256
|
| 108 |
+
],
|
| 109 |
+
"torch": "ok",
|
| 110 |
+
"graph": "ok",
|
| 111 |
+
"max_abs_diff": 0.00146484375,
|
| 112 |
+
"scale": 1993.6708984375,
|
| 113 |
+
"rel_diff": 7.347470192538007e-07
|
| 114 |
+
}
|
| 115 |
+
],
|
| 116 |
+
"exported_at": "2026-09-07T16:01:50+00:00",
|
| 117 |
+
"release": {
|
| 118 |
+
"repo": "MedOtter/MFMSNet",
|
| 119 |
+
"revision": "0f4ed1a62fb8c0c88fc30a511a7ca0a2bf6124ea",
|
| 120 |
+
"pth_file": "DRIVE.pth",
|
| 121 |
+
"pth_sha256": "b090aaa128ff53d10c1bf3938cd6ecac704c35f6fa0db66524daee17ae554a8d",
|
| 122 |
+
"sidecar_sha256": "402e4863796b2530120ab02b07d1cb1732e28237a9d98398dec1bbc4a73d5594",
|
| 123 |
+
"sidecar_source": "existing",
|
| 124 |
+
"group": "checkout_only",
|
| 125 |
+
"reference_check": {
|
| 126 |
+
"dataset": "DRIVE",
|
| 127 |
+
"split": "val",
|
| 128 |
+
"samples": 4,
|
| 129 |
+
"reproducible": true,
|
| 130 |
+
"status": "pass",
|
| 131 |
+
"sizes": [
|
| 132 |
+
{
|
| 133 |
+
"size": [
|
| 134 |
+
256,
|
| 135 |
+
256
|
| 136 |
+
],
|
| 137 |
+
"predict_masks_equal": 4,
|
| 138 |
+
"pixels": 262144,
|
| 139 |
+
"disagreeing_pixels": 0,
|
| 140 |
+
"unexplained_pixels": 0,
|
| 141 |
+
"max_abs_diff": 4.673004150390625e-05,
|
| 142 |
+
"scale": 12.872654914855957,
|
| 143 |
+
"rel_diff": 3.6301789967177995e-06,
|
| 144 |
+
"float32_vs_float64": {
|
| 145 |
+
"max_abs_diff": 8.81781432342521e-05,
|
| 146 |
+
"scale": 12.872640306448938,
|
| 147 |
+
"rel_diff": 6.850043280559669e-06,
|
| 148 |
+
"samples": 4,
|
| 149 |
+
"of": 4,
|
| 150 |
+
"complete": true
|
| 151 |
+
}
|
| 152 |
+
}
|
| 153 |
+
]
|
| 154 |
+
},
|
| 155 |
+
"tool": "tools/hf_onnx_export.py",
|
| 156 |
+
"stamped_at": "2026-09-07T16:02:19+00:00"
|
| 157 |
+
}
|
| 158 |
+
}
|
ISIC2018.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:031d1628a16c15be45a4270fbd7346ced5bb6d5f8d92ee74a68fa70909547953
|
| 3 |
+
size 347257078
|
ISIC2018.onnx.config.json
ADDED
|
@@ -0,0 +1,30 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"schema": "medotter/model-sidecar/v1",
|
| 3 |
+
"model": {
|
| 4 |
+
"graph": "onnx",
|
| 5 |
+
"args": {
|
| 6 |
+
"input_channel": 3,
|
| 7 |
+
"num_classes": 1
|
| 8 |
+
}
|
| 9 |
+
},
|
| 10 |
+
"inference": {
|
| 11 |
+
"normalize": {
|
| 12 |
+
"mean": [
|
| 13 |
+
0.485,
|
| 14 |
+
0.456,
|
| 15 |
+
0.406
|
| 16 |
+
],
|
| 17 |
+
"std": [
|
| 18 |
+
58.395,
|
| 19 |
+
57.12,
|
| 20 |
+
57.375
|
| 21 |
+
]
|
| 22 |
+
},
|
| 23 |
+
"scale": 255.0,
|
| 24 |
+
"size": [
|
| 25 |
+
256,
|
| 26 |
+
256
|
| 27 |
+
],
|
| 28 |
+
"threshold": 0.5
|
| 29 |
+
}
|
| 30 |
+
}
|
ISIC2018.onnx.provenance.json
ADDED
|
@@ -0,0 +1,158 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"schema": "medotter/graph-provenance/v1",
|
| 3 |
+
"source": {
|
| 4 |
+
"file": "ISIC2018.pth",
|
| 5 |
+
"sha256": "bedb0187692a53509275d220eeb7b16afbb2c8e4c61f3e7a8931616cbb89ad88",
|
| 6 |
+
"reference": "ISIC2018.pth",
|
| 7 |
+
"model": "MFMSNet",
|
| 8 |
+
"declaration_source": "sidecar",
|
| 9 |
+
"declaration": [
|
| 10 |
+
{
|
| 11 |
+
"file": "ISIC2018.pth.config.json",
|
| 12 |
+
"sha256": "6e19b4d8047bc7af8152f87db8170b2824a31ddb20e67430bd36fd5e24d331e9"
|
| 13 |
+
}
|
| 14 |
+
],
|
| 15 |
+
"float32_vs_float64": {
|
| 16 |
+
"shape": [
|
| 17 |
+
1,
|
| 18 |
+
3,
|
| 19 |
+
256,
|
| 20 |
+
256
|
| 21 |
+
],
|
| 22 |
+
"torch": "ok",
|
| 23 |
+
"float64": "ok",
|
| 24 |
+
"threads": 6,
|
| 25 |
+
"max_abs_diff": 0.0014899577294613664,
|
| 26 |
+
"scale": 1257.5916587601507,
|
| 27 |
+
"rel_diff": 1.1847706837768816e-06
|
| 28 |
+
}
|
| 29 |
+
},
|
| 30 |
+
"graph": {
|
| 31 |
+
"kind": "onnx",
|
| 32 |
+
"file": "ISIC2018.onnx",
|
| 33 |
+
"sha256": "031d1628a16c15be45a4270fbd7346ced5bb6d5f8d92ee74a68fa70909547953",
|
| 34 |
+
"bytes": 347257078,
|
| 35 |
+
"opset": 20,
|
| 36 |
+
"dynamic": false,
|
| 37 |
+
"reason": "dynamic_export_error",
|
| 38 |
+
"input": "image",
|
| 39 |
+
"output": "logits",
|
| 40 |
+
"input_channel": 3,
|
| 41 |
+
"num_classes": 1,
|
| 42 |
+
"size": [
|
| 43 |
+
256,
|
| 44 |
+
256
|
| 45 |
+
]
|
| 46 |
+
},
|
| 47 |
+
"exporter": {
|
| 48 |
+
"api": "torch.onnx.export",
|
| 49 |
+
"name": "dynamo",
|
| 50 |
+
"dynamo": true,
|
| 51 |
+
"registered_symbolics": {},
|
| 52 |
+
"producer": "pytorch 2.13.0+cpu",
|
| 53 |
+
"torch": "2.13.0+cpu",
|
| 54 |
+
"onnx": "1.22.0",
|
| 55 |
+
"onnxruntime": "1.29.0"
|
| 56 |
+
},
|
| 57 |
+
"verification_input": {
|
| 58 |
+
"kind": "smooth_random_field",
|
| 59 |
+
"distribution": "normal",
|
| 60 |
+
"coarse_factor": 16,
|
| 61 |
+
"min_coarse": 4,
|
| 62 |
+
"interpolation": "bilinear",
|
| 63 |
+
"align_corners": false,
|
| 64 |
+
"seed": 0
|
| 65 |
+
},
|
| 66 |
+
"attempts": [
|
| 67 |
+
{
|
| 68 |
+
"mode": "dynamic",
|
| 69 |
+
"exporter": "torchscript",
|
| 70 |
+
"outcome": "fell_back",
|
| 71 |
+
"reason": "dynamic_export_error",
|
| 72 |
+
"error": {
|
| 73 |
+
"kind": "export",
|
| 74 |
+
"text": "torchscript: SymbolicValueError: Unsupported: ONNX export of operator adaptive_avg_pool2d, input size not accessible. Please feel free to request support or submit a pull request on PyTorch GitHub: https://github.com/pytorch/pytorch/issues [Caused by the value '1101 defined in (%1101 : Float(*, 256, *, *, strides=[65536, 256, 16, 1], requires_grad=1, device=cpu) = onnx::Relu(%input.444), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.CNN.IS2D_models.mfmsnet.MFMSNet::inner/model_zoo.CNN.IS2D_models.mfmsnet.UpsampleBlock::decoder_stage1/model_zoo.CNN.IS2D_models.mfmsnet.MFMSAttentionBlock::attention_layer/torch.nn.modules.container.Sequential::multi_scale_branches.0/torch.nn.modules.activation.ReLU::multi_scale_branches.0.5 # /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py:1769:0 )' (type 'Tensor') in the TorchScript graph. The containing node has kind 'onnx::Relu'.] (node defined in /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py(1769): relu /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/activation.py(143): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/container.py(253): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/model_zoo/CNN/IS2D_models/mfmsnet.py(171): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/model_zoo/CNN/IS2D_models/mfmsnet.py(211): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/model_zoo/CNN/IS2D_models/mfmsnet.py(305): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(726): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/jit/_trace.py(131): wrapper /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/jit/_trace.py(140): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/jit/_trace.py(1439): _get_trace_graph /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(898): _trace_and_get_graph_from_model /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(992): _create_jit_graph /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(1108): _model_to_graph /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(1510): _export /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(547): export /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/__init__.py(334): export /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(774): _export_onnx /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1123): attempt /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1160): cmd_export /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1271): main /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1275): <module> <frozen runpy>(88): _run_code <frozen runpy>(198): _run_module_as_main ) Inputs: #0: input.444 defined in (%input.444 : Float(*, 256, *, *, strides=[65536, 256, 16, 1], requires_grad=1, device=cpu) = onnx::BatchNormalization[epsilon=1.0000000000000001e-05, momentum=0.90000000000000002, training_mode=0](%input.440, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.weight, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.bias, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.running_mean, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.running_var), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.CNN.IS2D_models.mfmsnet.MFMSNet::inner/model_zoo.CNN.IS2D_models.mfmsnet.UpsampleBlock::decoder_stage1/model_zoo.CNN.IS2D_models.mfmsnet.MFMSAttentionBlock::attention_layer/torch.nn.modules.container.Sequential::multi_scale_branches.0/torch.nn.modules.batchnorm.BatchNorm2d::multi_scale_branches.0.4 # /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py:2898:0 ) (type 'Tensor') Outputs: #0: 1101 defined in (%1101 : Float(*, 256, *, *, strides=[65536, 256, 16, 1], requires_grad=1, device=cpu) = onnx::Relu(%input.444), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.CNN.IS2D_models.mfmsnet.MFMSNet::inner/model_zoo.CNN.IS2D_models.mfmsnet.UpsampleBlock::decoder_stage1/model_zoo.CNN.IS2D_models.mfmsnet.MFMSAttentionBlock::attention_layer/torch.nn.modules.container.Sequential::multi_scale_branches.0/torch.nn.modules.activation.ReLU::multi_scale_branches.0.5 # /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py:1769:0 ) (type 'Tensor')"
|
| 75 |
+
},
|
| 76 |
+
"verification": null
|
| 77 |
+
},
|
| 78 |
+
{
|
| 79 |
+
"mode": "static",
|
| 80 |
+
"exporter": "dynamo",
|
| 81 |
+
"outcome": "kept",
|
| 82 |
+
"reason": "dynamic_export_error",
|
| 83 |
+
"error": null,
|
| 84 |
+
"verification": [
|
| 85 |
+
{
|
| 86 |
+
"shape": [
|
| 87 |
+
1,
|
| 88 |
+
3,
|
| 89 |
+
256,
|
| 90 |
+
256
|
| 91 |
+
],
|
| 92 |
+
"torch": "ok",
|
| 93 |
+
"graph": "ok",
|
| 94 |
+
"max_abs_diff": 0.0013580322265625,
|
| 95 |
+
"scale": 1257.5914306640625,
|
| 96 |
+
"rel_diff": 1.079867589305535e-06
|
| 97 |
+
}
|
| 98 |
+
]
|
| 99 |
+
}
|
| 100 |
+
],
|
| 101 |
+
"verification": [
|
| 102 |
+
{
|
| 103 |
+
"shape": [
|
| 104 |
+
1,
|
| 105 |
+
3,
|
| 106 |
+
256,
|
| 107 |
+
256
|
| 108 |
+
],
|
| 109 |
+
"torch": "ok",
|
| 110 |
+
"graph": "ok",
|
| 111 |
+
"max_abs_diff": 0.0013580322265625,
|
| 112 |
+
"scale": 1257.5914306640625,
|
| 113 |
+
"rel_diff": 1.079867589305535e-06
|
| 114 |
+
}
|
| 115 |
+
],
|
| 116 |
+
"exported_at": "2026-09-07T16:01:53+00:00",
|
| 117 |
+
"release": {
|
| 118 |
+
"repo": "MedOtter/MFMSNet",
|
| 119 |
+
"revision": "0f4ed1a62fb8c0c88fc30a511a7ca0a2bf6124ea",
|
| 120 |
+
"pth_file": "ISIC2018.pth",
|
| 121 |
+
"pth_sha256": "bedb0187692a53509275d220eeb7b16afbb2c8e4c61f3e7a8931616cbb89ad88",
|
| 122 |
+
"sidecar_sha256": "402e4863796b2530120ab02b07d1cb1732e28237a9d98398dec1bbc4a73d5594",
|
| 123 |
+
"sidecar_source": "existing",
|
| 124 |
+
"group": "checkout_only",
|
| 125 |
+
"reference_check": {
|
| 126 |
+
"dataset": "ISIC2018",
|
| 127 |
+
"split": "val",
|
| 128 |
+
"samples": 4,
|
| 129 |
+
"reproducible": true,
|
| 130 |
+
"status": "pass",
|
| 131 |
+
"sizes": [
|
| 132 |
+
{
|
| 133 |
+
"size": [
|
| 134 |
+
256,
|
| 135 |
+
256
|
| 136 |
+
],
|
| 137 |
+
"predict_masks_equal": 3,
|
| 138 |
+
"pixels": 262144,
|
| 139 |
+
"disagreeing_pixels": 0,
|
| 140 |
+
"unexplained_pixels": 0,
|
| 141 |
+
"max_abs_diff": 7.390975952148438e-05,
|
| 142 |
+
"scale": 15.030379295349121,
|
| 143 |
+
"rel_diff": 4.917358242872448e-06,
|
| 144 |
+
"float32_vs_float64": {
|
| 145 |
+
"max_abs_diff": 8.759302497995947e-05,
|
| 146 |
+
"scale": 15.030386907134137,
|
| 147 |
+
"rel_diff": 5.827729220888096e-06,
|
| 148 |
+
"samples": 4,
|
| 149 |
+
"of": 4,
|
| 150 |
+
"complete": true
|
| 151 |
+
}
|
| 152 |
+
}
|
| 153 |
+
]
|
| 154 |
+
},
|
| 155 |
+
"tool": "tools/hf_onnx_export.py",
|
| 156 |
+
"stamped_at": "2026-09-07T16:02:22+00:00"
|
| 157 |
+
}
|
| 158 |
+
}
|
PROMISE12.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c7a36e5f25d3ee700789d1c3ff88454aa7cf1b63dfad3eb15e4cef600ee26b37
|
| 3 |
+
size 347257078
|
PROMISE12.onnx.config.json
ADDED
|
@@ -0,0 +1,30 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"schema": "medotter/model-sidecar/v1",
|
| 3 |
+
"model": {
|
| 4 |
+
"graph": "onnx",
|
| 5 |
+
"args": {
|
| 6 |
+
"input_channel": 3,
|
| 7 |
+
"num_classes": 1
|
| 8 |
+
}
|
| 9 |
+
},
|
| 10 |
+
"inference": {
|
| 11 |
+
"normalize": {
|
| 12 |
+
"mean": [
|
| 13 |
+
0.485,
|
| 14 |
+
0.456,
|
| 15 |
+
0.406
|
| 16 |
+
],
|
| 17 |
+
"std": [
|
| 18 |
+
58.395,
|
| 19 |
+
57.12,
|
| 20 |
+
57.375
|
| 21 |
+
]
|
| 22 |
+
},
|
| 23 |
+
"scale": 255.0,
|
| 24 |
+
"size": [
|
| 25 |
+
256,
|
| 26 |
+
256
|
| 27 |
+
],
|
| 28 |
+
"threshold": 0.5
|
| 29 |
+
}
|
| 30 |
+
}
|
PROMISE12.onnx.provenance.json
ADDED
|
@@ -0,0 +1,158 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"schema": "medotter/graph-provenance/v1",
|
| 3 |
+
"source": {
|
| 4 |
+
"file": "PROMISE12.pth",
|
| 5 |
+
"sha256": "d56b0a154ed23424a5b614559d0c35f32b1df02d6185d423d90a61e70a5ffbb1",
|
| 6 |
+
"reference": "PROMISE12.pth",
|
| 7 |
+
"model": "MFMSNet",
|
| 8 |
+
"declaration_source": "sidecar",
|
| 9 |
+
"declaration": [
|
| 10 |
+
{
|
| 11 |
+
"file": "PROMISE12.pth.config.json",
|
| 12 |
+
"sha256": "6e19b4d8047bc7af8152f87db8170b2824a31ddb20e67430bd36fd5e24d331e9"
|
| 13 |
+
}
|
| 14 |
+
],
|
| 15 |
+
"float32_vs_float64": {
|
| 16 |
+
"shape": [
|
| 17 |
+
1,
|
| 18 |
+
3,
|
| 19 |
+
256,
|
| 20 |
+
256
|
| 21 |
+
],
|
| 22 |
+
"torch": "ok",
|
| 23 |
+
"float64": "ok",
|
| 24 |
+
"threads": 6,
|
| 25 |
+
"max_abs_diff": 0.002422711227268337,
|
| 26 |
+
"scale": 2658.450017236831,
|
| 27 |
+
"rel_diff": 9.113247236397098e-07
|
| 28 |
+
}
|
| 29 |
+
},
|
| 30 |
+
"graph": {
|
| 31 |
+
"kind": "onnx",
|
| 32 |
+
"file": "PROMISE12.onnx",
|
| 33 |
+
"sha256": "c7a36e5f25d3ee700789d1c3ff88454aa7cf1b63dfad3eb15e4cef600ee26b37",
|
| 34 |
+
"bytes": 347257078,
|
| 35 |
+
"opset": 20,
|
| 36 |
+
"dynamic": false,
|
| 37 |
+
"reason": "dynamic_export_error",
|
| 38 |
+
"input": "image",
|
| 39 |
+
"output": "logits",
|
| 40 |
+
"input_channel": 3,
|
| 41 |
+
"num_classes": 1,
|
| 42 |
+
"size": [
|
| 43 |
+
256,
|
| 44 |
+
256
|
| 45 |
+
]
|
| 46 |
+
},
|
| 47 |
+
"exporter": {
|
| 48 |
+
"api": "torch.onnx.export",
|
| 49 |
+
"name": "dynamo",
|
| 50 |
+
"dynamo": true,
|
| 51 |
+
"registered_symbolics": {},
|
| 52 |
+
"producer": "pytorch 2.13.0+cpu",
|
| 53 |
+
"torch": "2.13.0+cpu",
|
| 54 |
+
"onnx": "1.22.0",
|
| 55 |
+
"onnxruntime": "1.29.0"
|
| 56 |
+
},
|
| 57 |
+
"verification_input": {
|
| 58 |
+
"kind": "smooth_random_field",
|
| 59 |
+
"distribution": "normal",
|
| 60 |
+
"coarse_factor": 16,
|
| 61 |
+
"min_coarse": 4,
|
| 62 |
+
"interpolation": "bilinear",
|
| 63 |
+
"align_corners": false,
|
| 64 |
+
"seed": 0
|
| 65 |
+
},
|
| 66 |
+
"attempts": [
|
| 67 |
+
{
|
| 68 |
+
"mode": "dynamic",
|
| 69 |
+
"exporter": "torchscript",
|
| 70 |
+
"outcome": "fell_back",
|
| 71 |
+
"reason": "dynamic_export_error",
|
| 72 |
+
"error": {
|
| 73 |
+
"kind": "export",
|
| 74 |
+
"text": "torchscript: SymbolicValueError: Unsupported: ONNX export of operator adaptive_avg_pool2d, input size not accessible. Please feel free to request support or submit a pull request on PyTorch GitHub: https://github.com/pytorch/pytorch/issues [Caused by the value '1101 defined in (%1101 : Float(*, 256, *, *, strides=[65536, 256, 16, 1], requires_grad=1, device=cpu) = onnx::Relu(%input.444), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.CNN.IS2D_models.mfmsnet.MFMSNet::inner/model_zoo.CNN.IS2D_models.mfmsnet.UpsampleBlock::decoder_stage1/model_zoo.CNN.IS2D_models.mfmsnet.MFMSAttentionBlock::attention_layer/torch.nn.modules.container.Sequential::multi_scale_branches.0/torch.nn.modules.activation.ReLU::multi_scale_branches.0.5 # /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py:1769:0 )' (type 'Tensor') in the TorchScript graph. The containing node has kind 'onnx::Relu'.] (node defined in /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py(1769): relu /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/activation.py(143): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/container.py(253): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/model_zoo/CNN/IS2D_models/mfmsnet.py(171): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/model_zoo/CNN/IS2D_models/mfmsnet.py(211): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/model_zoo/CNN/IS2D_models/mfmsnet.py(305): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(726): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/jit/_trace.py(131): wrapper /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/jit/_trace.py(140): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/jit/_trace.py(1439): _get_trace_graph /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(898): _trace_and_get_graph_from_model /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(992): _create_jit_graph /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(1108): _model_to_graph /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(1510): _export /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(547): export /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/__init__.py(334): export /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(774): _export_onnx /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1123): attempt /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1160): cmd_export /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1271): main /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1275): <module> <frozen runpy>(88): _run_code <frozen runpy>(198): _run_module_as_main ) Inputs: #0: input.444 defined in (%input.444 : Float(*, 256, *, *, strides=[65536, 256, 16, 1], requires_grad=1, device=cpu) = onnx::BatchNormalization[epsilon=1.0000000000000001e-05, momentum=0.90000000000000002, training_mode=0](%input.440, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.weight, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.bias, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.running_mean, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.running_var), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.CNN.IS2D_models.mfmsnet.MFMSNet::inner/model_zoo.CNN.IS2D_models.mfmsnet.UpsampleBlock::decoder_stage1/model_zoo.CNN.IS2D_models.mfmsnet.MFMSAttentionBlock::attention_layer/torch.nn.modules.container.Sequential::multi_scale_branches.0/torch.nn.modules.batchnorm.BatchNorm2d::multi_scale_branches.0.4 # /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py:2898:0 ) (type 'Tensor') Outputs: #0: 1101 defined in (%1101 : Float(*, 256, *, *, strides=[65536, 256, 16, 1], requires_grad=1, device=cpu) = onnx::Relu(%input.444), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.CNN.IS2D_models.mfmsnet.MFMSNet::inner/model_zoo.CNN.IS2D_models.mfmsnet.UpsampleBlock::decoder_stage1/model_zoo.CNN.IS2D_models.mfmsnet.MFMSAttentionBlock::attention_layer/torch.nn.modules.container.Sequential::multi_scale_branches.0/torch.nn.modules.activation.ReLU::multi_scale_branches.0.5 # /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py:1769:0 ) (type 'Tensor')"
|
| 75 |
+
},
|
| 76 |
+
"verification": null
|
| 77 |
+
},
|
| 78 |
+
{
|
| 79 |
+
"mode": "static",
|
| 80 |
+
"exporter": "dynamo",
|
| 81 |
+
"outcome": "kept",
|
| 82 |
+
"reason": "dynamic_export_error",
|
| 83 |
+
"error": null,
|
| 84 |
+
"verification": [
|
| 85 |
+
{
|
| 86 |
+
"shape": [
|
| 87 |
+
1,
|
| 88 |
+
3,
|
| 89 |
+
256,
|
| 90 |
+
256
|
| 91 |
+
],
|
| 92 |
+
"torch": "ok",
|
| 93 |
+
"graph": "ok",
|
| 94 |
+
"max_abs_diff": 0.0018310546875,
|
| 95 |
+
"scale": 2658.45166015625,
|
| 96 |
+
"rel_diff": 6.887673433912958e-07
|
| 97 |
+
}
|
| 98 |
+
]
|
| 99 |
+
}
|
| 100 |
+
],
|
| 101 |
+
"verification": [
|
| 102 |
+
{
|
| 103 |
+
"shape": [
|
| 104 |
+
1,
|
| 105 |
+
3,
|
| 106 |
+
256,
|
| 107 |
+
256
|
| 108 |
+
],
|
| 109 |
+
"torch": "ok",
|
| 110 |
+
"graph": "ok",
|
| 111 |
+
"max_abs_diff": 0.0018310546875,
|
| 112 |
+
"scale": 2658.45166015625,
|
| 113 |
+
"rel_diff": 6.887673433912958e-07
|
| 114 |
+
}
|
| 115 |
+
],
|
| 116 |
+
"exported_at": "2026-09-07T16:03:17+00:00",
|
| 117 |
+
"release": {
|
| 118 |
+
"repo": "MedOtter/MFMSNet",
|
| 119 |
+
"revision": "0f4ed1a62fb8c0c88fc30a511a7ca0a2bf6124ea",
|
| 120 |
+
"pth_file": "PROMISE12.pth",
|
| 121 |
+
"pth_sha256": "d56b0a154ed23424a5b614559d0c35f32b1df02d6185d423d90a61e70a5ffbb1",
|
| 122 |
+
"sidecar_sha256": "402e4863796b2530120ab02b07d1cb1732e28237a9d98398dec1bbc4a73d5594",
|
| 123 |
+
"sidecar_source": "existing",
|
| 124 |
+
"group": "checkout_only",
|
| 125 |
+
"reference_check": {
|
| 126 |
+
"dataset": "PROMISE12",
|
| 127 |
+
"split": "val",
|
| 128 |
+
"samples": 4,
|
| 129 |
+
"reproducible": true,
|
| 130 |
+
"status": "pass",
|
| 131 |
+
"sizes": [
|
| 132 |
+
{
|
| 133 |
+
"size": [
|
| 134 |
+
256,
|
| 135 |
+
256
|
| 136 |
+
],
|
| 137 |
+
"predict_masks_equal": 4,
|
| 138 |
+
"pixels": 262144,
|
| 139 |
+
"disagreeing_pixels": 0,
|
| 140 |
+
"unexplained_pixels": 0,
|
| 141 |
+
"max_abs_diff": 8.52346420288086e-05,
|
| 142 |
+
"scale": 15.08598518371582,
|
| 143 |
+
"rel_diff": 5.649922162247179e-06,
|
| 144 |
+
"float32_vs_float64": {
|
| 145 |
+
"max_abs_diff": 7.044717491933028e-05,
|
| 146 |
+
"scale": 15.085988142389814,
|
| 147 |
+
"rel_diff": 4.669709021007526e-06,
|
| 148 |
+
"samples": 4,
|
| 149 |
+
"of": 4,
|
| 150 |
+
"complete": true
|
| 151 |
+
}
|
| 152 |
+
}
|
| 153 |
+
]
|
| 154 |
+
},
|
| 155 |
+
"tool": "tools/hf_onnx_export.py",
|
| 156 |
+
"stamped_at": "2026-09-07T16:03:53+00:00"
|
| 157 |
+
}
|
| 158 |
+
}
|
UWaterlooSkinCancer.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:6d95726f10b1873a1879f827d29f42091263be1cd3eae7b964e6c13d9361a9d1
|
| 3 |
+
size 347257078
|
UWaterlooSkinCancer.onnx.config.json
ADDED
|
@@ -0,0 +1,30 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"schema": "medotter/model-sidecar/v1",
|
| 3 |
+
"model": {
|
| 4 |
+
"graph": "onnx",
|
| 5 |
+
"args": {
|
| 6 |
+
"input_channel": 3,
|
| 7 |
+
"num_classes": 1
|
| 8 |
+
}
|
| 9 |
+
},
|
| 10 |
+
"inference": {
|
| 11 |
+
"normalize": {
|
| 12 |
+
"mean": [
|
| 13 |
+
0.485,
|
| 14 |
+
0.456,
|
| 15 |
+
0.406
|
| 16 |
+
],
|
| 17 |
+
"std": [
|
| 18 |
+
58.395,
|
| 19 |
+
57.12,
|
| 20 |
+
57.375
|
| 21 |
+
]
|
| 22 |
+
},
|
| 23 |
+
"scale": 255.0,
|
| 24 |
+
"size": [
|
| 25 |
+
256,
|
| 26 |
+
256
|
| 27 |
+
],
|
| 28 |
+
"threshold": 0.5
|
| 29 |
+
}
|
| 30 |
+
}
|
UWaterlooSkinCancer.onnx.provenance.json
ADDED
|
@@ -0,0 +1,158 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"schema": "medotter/graph-provenance/v1",
|
| 3 |
+
"source": {
|
| 4 |
+
"file": "UWaterlooSkinCancer.pth",
|
| 5 |
+
"sha256": "54d9539b65159567b29f15e9109949c043934c678134f0d6cb3131f4ca22b1f7",
|
| 6 |
+
"reference": "UWaterlooSkinCancer.pth",
|
| 7 |
+
"model": "MFMSNet",
|
| 8 |
+
"declaration_source": "sidecar",
|
| 9 |
+
"declaration": [
|
| 10 |
+
{
|
| 11 |
+
"file": "UWaterlooSkinCancer.pth.config.json",
|
| 12 |
+
"sha256": "6e19b4d8047bc7af8152f87db8170b2824a31ddb20e67430bd36fd5e24d331e9"
|
| 13 |
+
}
|
| 14 |
+
],
|
| 15 |
+
"float32_vs_float64": {
|
| 16 |
+
"shape": [
|
| 17 |
+
1,
|
| 18 |
+
3,
|
| 19 |
+
256,
|
| 20 |
+
256
|
| 21 |
+
],
|
| 22 |
+
"torch": "ok",
|
| 23 |
+
"float64": "ok",
|
| 24 |
+
"threads": 6,
|
| 25 |
+
"max_abs_diff": 0.0014853474577876113,
|
| 26 |
+
"scale": 1246.714232808468,
|
| 27 |
+
"rel_diff": 1.191409722211621e-06
|
| 28 |
+
}
|
| 29 |
+
},
|
| 30 |
+
"graph": {
|
| 31 |
+
"kind": "onnx",
|
| 32 |
+
"file": "UWaterlooSkinCancer.onnx",
|
| 33 |
+
"sha256": "6d95726f10b1873a1879f827d29f42091263be1cd3eae7b964e6c13d9361a9d1",
|
| 34 |
+
"bytes": 347257078,
|
| 35 |
+
"opset": 20,
|
| 36 |
+
"dynamic": false,
|
| 37 |
+
"reason": "dynamic_export_error",
|
| 38 |
+
"input": "image",
|
| 39 |
+
"output": "logits",
|
| 40 |
+
"input_channel": 3,
|
| 41 |
+
"num_classes": 1,
|
| 42 |
+
"size": [
|
| 43 |
+
256,
|
| 44 |
+
256
|
| 45 |
+
]
|
| 46 |
+
},
|
| 47 |
+
"exporter": {
|
| 48 |
+
"api": "torch.onnx.export",
|
| 49 |
+
"name": "dynamo",
|
| 50 |
+
"dynamo": true,
|
| 51 |
+
"registered_symbolics": {},
|
| 52 |
+
"producer": "pytorch 2.13.0+cpu",
|
| 53 |
+
"torch": "2.13.0+cpu",
|
| 54 |
+
"onnx": "1.22.0",
|
| 55 |
+
"onnxruntime": "1.29.0"
|
| 56 |
+
},
|
| 57 |
+
"verification_input": {
|
| 58 |
+
"kind": "smooth_random_field",
|
| 59 |
+
"distribution": "normal",
|
| 60 |
+
"coarse_factor": 16,
|
| 61 |
+
"min_coarse": 4,
|
| 62 |
+
"interpolation": "bilinear",
|
| 63 |
+
"align_corners": false,
|
| 64 |
+
"seed": 0
|
| 65 |
+
},
|
| 66 |
+
"attempts": [
|
| 67 |
+
{
|
| 68 |
+
"mode": "dynamic",
|
| 69 |
+
"exporter": "torchscript",
|
| 70 |
+
"outcome": "fell_back",
|
| 71 |
+
"reason": "dynamic_export_error",
|
| 72 |
+
"error": {
|
| 73 |
+
"kind": "export",
|
| 74 |
+
"text": "torchscript: SymbolicValueError: Unsupported: ONNX export of operator adaptive_avg_pool2d, input size not accessible. Please feel free to request support or submit a pull request on PyTorch GitHub: https://github.com/pytorch/pytorch/issues [Caused by the value '1101 defined in (%1101 : Float(*, 256, *, *, strides=[65536, 256, 16, 1], requires_grad=1, device=cpu) = onnx::Relu(%input.444), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.CNN.IS2D_models.mfmsnet.MFMSNet::inner/model_zoo.CNN.IS2D_models.mfmsnet.UpsampleBlock::decoder_stage1/model_zoo.CNN.IS2D_models.mfmsnet.MFMSAttentionBlock::attention_layer/torch.nn.modules.container.Sequential::multi_scale_branches.0/torch.nn.modules.activation.ReLU::multi_scale_branches.0.5 # /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py:1769:0 )' (type 'Tensor') in the TorchScript graph. The containing node has kind 'onnx::Relu'.] (node defined in /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py(1769): relu /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/activation.py(143): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/container.py(253): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/model_zoo/CNN/IS2D_models/mfmsnet.py(171): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/model_zoo/CNN/IS2D_models/mfmsnet.py(211): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/model_zoo/CNN/IS2D_models/mfmsnet.py(305): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(726): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1768): _slow_forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/jit/_trace.py(131): wrapper /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/jit/_trace.py(140): forward /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1789): _call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/modules/module.py(1778): _wrapped_call_impl /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/jit/_trace.py(1439): _get_trace_graph /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(898): _trace_and_get_graph_from_model /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(992): _create_jit_graph /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(1108): _model_to_graph /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(1510): _export /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/_internal/torchscript_exporter/utils.py(547): export /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/onnx/__init__.py(334): export /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(774): _export_onnx /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1123): attempt /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1160): cmd_export /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1271): main /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-pilot/medotter/agent/tools/export_graph.py(1275): <module> <frozen runpy>(88): _run_code <frozen runpy>(198): _run_module_as_main ) Inputs: #0: input.444 defined in (%input.444 : Float(*, 256, *, *, strides=[65536, 256, 16, 1], requires_grad=1, device=cpu) = onnx::BatchNormalization[epsilon=1.0000000000000001e-05, momentum=0.90000000000000002, training_mode=0](%input.440, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.weight, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.bias, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.running_mean, %inner.decoder_stage1.attention_layer.multi_scale_branches.0.4.running_var), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.CNN.IS2D_models.mfmsnet.MFMSNet::inner/model_zoo.CNN.IS2D_models.mfmsnet.UpsampleBlock::decoder_stage1/model_zoo.CNN.IS2D_models.mfmsnet.MFMSAttentionBlock::attention_layer/torch.nn.modules.container.Sequential::multi_scale_branches.0/torch.nn.modules.batchnorm.BatchNorm2d::multi_scale_branches.0.4 # /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py:2898:0 ) (type 'Tensor') Outputs: #0: 1101 defined in (%1101 : Float(*, 256, *, *, strides=[65536, 256, 16, 1], requires_grad=1, device=cpu) = onnx::Relu(%input.444), scope: __main__.scored_head.<locals>.ScoredHead::/model_zoo.CNN.IS2D_models.mfmsnet.MFMSNet::inner/model_zoo.CNN.IS2D_models.mfmsnet.UpsampleBlock::decoder_stage1/model_zoo.CNN.IS2D_models.mfmsnet.MFMSAttentionBlock::attention_layer/torch.nn.modules.container.Sequential::multi_scale_branches.0/torch.nn.modules.activation.ReLU::multi_scale_branches.0.5 # /home/csgrad/tianyulu/.venvs/medotter-eval-v2/lib/python3.12/site-packages/torch/nn/functional.py:1769:0 ) (type 'Tensor')"
|
| 75 |
+
},
|
| 76 |
+
"verification": null
|
| 77 |
+
},
|
| 78 |
+
{
|
| 79 |
+
"mode": "static",
|
| 80 |
+
"exporter": "dynamo",
|
| 81 |
+
"outcome": "kept",
|
| 82 |
+
"reason": "dynamic_export_error",
|
| 83 |
+
"error": null,
|
| 84 |
+
"verification": [
|
| 85 |
+
{
|
| 86 |
+
"shape": [
|
| 87 |
+
1,
|
| 88 |
+
3,
|
| 89 |
+
256,
|
| 90 |
+
256
|
| 91 |
+
],
|
| 92 |
+
"torch": "ok",
|
| 93 |
+
"graph": "ok",
|
| 94 |
+
"max_abs_diff": 0.0012664794921875,
|
| 95 |
+
"scale": 1246.71435546875,
|
| 96 |
+
"rel_diff": 1.0158537812868278e-06
|
| 97 |
+
}
|
| 98 |
+
]
|
| 99 |
+
}
|
| 100 |
+
],
|
| 101 |
+
"verification": [
|
| 102 |
+
{
|
| 103 |
+
"shape": [
|
| 104 |
+
1,
|
| 105 |
+
3,
|
| 106 |
+
256,
|
| 107 |
+
256
|
| 108 |
+
],
|
| 109 |
+
"torch": "ok",
|
| 110 |
+
"graph": "ok",
|
| 111 |
+
"max_abs_diff": 0.0012664794921875,
|
| 112 |
+
"scale": 1246.71435546875,
|
| 113 |
+
"rel_diff": 1.0158537812868278e-06
|
| 114 |
+
}
|
| 115 |
+
],
|
| 116 |
+
"exported_at": "2026-09-07T16:03:34+00:00",
|
| 117 |
+
"release": {
|
| 118 |
+
"repo": "MedOtter/MFMSNet",
|
| 119 |
+
"revision": "0f4ed1a62fb8c0c88fc30a511a7ca0a2bf6124ea",
|
| 120 |
+
"pth_file": "UWaterlooSkinCancer.pth",
|
| 121 |
+
"pth_sha256": "54d9539b65159567b29f15e9109949c043934c678134f0d6cb3131f4ca22b1f7",
|
| 122 |
+
"sidecar_sha256": "402e4863796b2530120ab02b07d1cb1732e28237a9d98398dec1bbc4a73d5594",
|
| 123 |
+
"sidecar_source": "existing",
|
| 124 |
+
"group": "checkout_only",
|
| 125 |
+
"reference_check": {
|
| 126 |
+
"dataset": "UWaterlooSkinCancer",
|
| 127 |
+
"split": "val",
|
| 128 |
+
"samples": 4,
|
| 129 |
+
"reproducible": true,
|
| 130 |
+
"status": "pass",
|
| 131 |
+
"sizes": [
|
| 132 |
+
{
|
| 133 |
+
"size": [
|
| 134 |
+
256,
|
| 135 |
+
256
|
| 136 |
+
],
|
| 137 |
+
"predict_masks_equal": 4,
|
| 138 |
+
"pixels": 262144,
|
| 139 |
+
"disagreeing_pixels": 0,
|
| 140 |
+
"unexplained_pixels": 0,
|
| 141 |
+
"max_abs_diff": 4.6312808990478516e-05,
|
| 142 |
+
"scale": 12.196309089660645,
|
| 143 |
+
"rel_diff": 3.797280689593211e-06,
|
| 144 |
+
"float32_vs_float64": {
|
| 145 |
+
"max_abs_diff": 4.698388443546975e-05,
|
| 146 |
+
"scale": 12.196306630248156,
|
| 147 |
+
"rel_diff": 3.852304296691315e-06,
|
| 148 |
+
"samples": 4,
|
| 149 |
+
"of": 4,
|
| 150 |
+
"complete": true
|
| 151 |
+
}
|
| 152 |
+
}
|
| 153 |
+
]
|
| 154 |
+
},
|
| 155 |
+
"tool": "tools/hf_onnx_export.py",
|
| 156 |
+
"stamped_at": "2026-09-07T16:04:29+00:00"
|
| 157 |
+
}
|
| 158 |
+
}
|