Add ONNX graphs: KvasirSEG.onnx, KvasirSEG.onnx.config.json, KvasirSEG.onnx.provenance.json (tools/hf_onnx_export.py)

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KvasirSEG.onnx +3 -0
KvasirSEG.onnx.config.json +30 -0
KvasirSEG.onnx.provenance.json +165 -0

KvasirSEG.onnx ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:6123e402bd01b997dd5eb6bdfebc12239e147c4099a5f0482bcc65a829fc5a48
+size 347291569

KvasirSEG.onnx.config.json ADDED Viewed

	@@ -0,0 +1,30 @@

+{
+  "schema": "medotter/model-sidecar/v1",
+  "model": {
+    "graph": "onnx",
+    "args": {
+      "input_channel": 3,
+      "num_classes": 1
+    }
+  },
+  "inference": {
+    "normalize": {
+      "mean": [
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+        0.456,
+        0.406
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+      "std": [
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+        0.224,
+        0.225
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+    "scale": 255.0,
+    "size": [
+      256,
+      256
+    ],
+    "threshold": 0.5
+  }
+}

KvasirSEG.onnx.provenance.json ADDED Viewed

	@@ -0,0 +1,165 @@

+{
+  "schema": "medotter/graph-provenance/v1",
+  "source": {
+    "file": "KvasirSEG.pth",
+    "sha256": "6855082f4b8f429837f742dc00cbc60fd351bce7bb18726e577835a967c73584",
+    "reference": "KvasirSEG.pth",
+    "model": "MFMSNet",
+    "declaration_source": "sidecar",
+    "declaration": [
+      {
+        "file": "KvasirSEG.pth.config.json",
+        "sha256": "6f8ba6d8e12c8f02c97d64b6b3077e2169b3bf62fa79e901d3e039c3f4e807e4"
+      }
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+    "float32_vs_float64": {
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+        3,
+        256,
+        256
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+      "torch": "ok",
+      "float64": "ok",
+      "threads": 6,
+      "max_abs_diff": 1.0247418181341672e-05,
+      "scale": 4.114137811282087,
+      "rel_diff": 2.4907814592988253e-06,
+      "kernel_noise_rel": 2.4629200147891104e-06
+    }
+  },
+  "graph": {
+    "kind": "onnx",
+    "file": "KvasirSEG.onnx",
+    "sha256": "6123e402bd01b997dd5eb6bdfebc12239e147c4099a5f0482bcc65a829fc5a48",
+    "bytes": 347291569,
+    "opset": 20,
+    "dynamic": false,
+    "reason": "dynamic_export_error",
+    "input": "image",
+    "output": "logits",
+    "input_channel": 3,
+    "num_classes": 1,
+    "size": [
+      256,
+      256
+    ]
+  },
+  "exporter": {
+    "api": "torch.onnx.export",
+    "name": "dynamo",
+    "dynamo": true,
+    "registered_symbolics": {},
+    "producer": "pytorch 2.13.0+cpu",
+    "torch": "2.13.0+cpu",
+    "onnx": "1.22.0",
+    "onnxruntime": "1.29.0"
+  },
+  "verification_input": {
+    "kind": "smooth_random_field",
+    "distribution": "normal",
+    "coarse_factor": 16,
+    "min_coarse": 4,
+    "interpolation": "bilinear",
+    "align_corners": false,
+    "seed": 0,
+    "pixel_domain": "uint8-range smooth field through the declaration's intensity contract",
+    "pixel_mean": 127.5,
+    "pixel_std": 45.0,
+    "through_contract": true
+  },
+  "attempts": [
+    {
+      "mode": "dynamic",
+      "exporter": "torchscript",
+      "outcome": "fell_back",
+      "reason": "dynamic_export_error",
+      "error": {
+        "kind": "export",
+        "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-research/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-research/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-research/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-research/medotter/agent/tools/export_graph.py(913): 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-research/medotter/agent/tools/export_graph.py(961): _export_onnx /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-research/medotter/agent/tools/export_graph.py(1699): attempt /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-research/medotter/agent/tools/export_graph.py(1736): cmd_export /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-research/medotter/agent/tools/export_graph.py(1847): main /home/csgrad/tianyulu/code/medotter/.worktrees/onnx-research/medotter/agent/tools/export_graph.py(1851): <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')"
+      },
+      "verification": null
+    },
+    {
+      "mode": "static",
+      "exporter": "dynamo",
+      "outcome": "kept",
+      "reason": "dynamic_export_error",
+      "error": null,
+      "verification": [
+        {
+          "shape": [
+            1,
+            3,
+            256,
+            256
+          ],
+          "torch": "ok",
+          "graph": "ok",
+          "max_abs_diff": 9.834766387939453e-06,
+          "scale": 4.114136695861816,
+          "rel_diff": 2.3904811908247246e-06
+        }
+      ]
+    }
+  ],
+  "verification": [
+    {
+      "shape": [
+        1,
+        3,
+        256,
+        256
+      ],
+      "torch": "ok",
+      "graph": "ok",
+      "max_abs_diff": 9.834766387939453e-06,
+      "scale": 4.114136695861816,
+      "rel_diff": 2.3904811908247246e-06
+    }
+  ],
+  "exported_at": "2026-09-09T23:19:37+00:00",
+  "release": {
+    "repo": "MedOtter/MFMSNet",
+    "revision": "839d4dce7f85ed278e3393d94ec2fc19b140d357",
+    "pth_file": "KvasirSEG.pth",
+    "pth_sha256": "6855082f4b8f429837f742dc00cbc60fd351bce7bb18726e577835a967c73584",
+    "sidecar_sha256": "1445f651ec927f1196af8ad861bf4ef54128f23d2812ee825908fa7d98195fa6",
+    "sidecar_source": "hub",
+    "group": "checkout_only",
+    "reason": "dynamic_export_error",
+    "dynamic_attempt": null,
+    "reference_check": {
+      "dataset": "KvasirSEG",
+      "split": "val",
+      "samples": 4,
+      "reproducible": true,
+      "status": "pass",
+      "sizes": [
+        {
+          "size": [
+            256,
+            256
+          ],
+          "predict_masks_equal": 4,
+          "pixels": 262144,
+          "disagreeing_pixels": 0,
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+          "max_abs_diff": 1.8358230590820312e-05,
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+            "samples": 4,
+            "of": 4,
+            "complete": true
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+      ]
+    },
+    "tool": "tools/hf_onnx_export.py",
+    "stamped_at": "2026-09-09T23:19:55+00:00"
+  }
+}