Fix wrong module loading - #66
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Jun 25, 2026 2:04p.m. | Review ↗ |
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mkofler96
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* fix bounds slicing for xmin and xmax calculations (#64) * Add homogenization (#65) * Add test experiment for homogenization model with training artifacts - Introduced new experiment directory for testing homogenization. - Added latest model, optimizer parameters, latent codes, and logs as binary files. - Created specs.json to define network architecture and training parameters. - Added training summary in training_summary.json. - Implemented a test function to train the homogenization model in test_train_model.py. * Add homogenization network and update training loss calculation * added xlim option back to plot sdf * Update test experiment specs and data directory for homogenization model * Refactor homogenization model tests to use shared data directory fixture * set default dtype to float32 in test train model * reduced test duration by reducing sampling points * fix retry 429 error * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Fix negative Jacobian at mesh resolution 10 by filtering tets in float64 The orientation check ran in float32 but torchfem evaluates Jacobians in float64 (after verts.to(float64)). Tets with a tiny positive float32 volume can flip negative in float64, causing the "Negative Jacobian" exception. Compute the final validity mask in float64 so the filter is consistent with torchfem. * added HF secret --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Claude <noreply@anthropic.com> * Fix wrong module loading (#66) * Refactor model loading to handle module prefix in state_dict more efficiently * added some additional output checks for the model export * replaced deprecated torch.linalg.norm argument axes * Fix type comparison in optimization (#67) * Fix type comparison * Add previous type checks for compatibility reasons --------- Co-authored-by: Aron Längert <e11916873@student.ilsb.tuwien.ac.at> * added pypi publish workflow * Fix publish workflow (#69) * added pypi environment * fixed version criteria * added guard to only trigger on main * Potential fix for pull request finding Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> * Skip publish job on non-tag pushes in PyPI workflow (#70) * Initial plan * chore: start publish failure investigation Co-authored-by: mkofler96 <18218171+mkofler96@users.noreply.github.com> * fix(ci): skip publish job on branch pushes Co-authored-by: mkofler96 <18218171+mkofler96@users.noreply.github.com> * chore: revert unintended uv lockfile changes Co-authored-by: mkofler96 <18218171+mkofler96@users.noreply.github.com> --------- Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com> Co-authored-by: mkofler96 <18218171+mkofler96@users.noreply.github.com> * add threshold_factor argument * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: Michael Kofler <michael.kofler@tuwien.ac.at> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Claude <noreply@anthropic.com> Co-authored-by: Aron Längert <e11916873@student.ilsb.tuwien.ac.at> Co-authored-by: Michael Kofler <rasta.kof@gmail.com> Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> Co-authored-by: Copilot <198982749+Copilot@users.noreply.github.com> Co-authored-by: mkofler96 <18218171+mkofler96@users.noreply.github.com>
mkofler96
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Jul 15, 2026
* Fix inverted tetrahedra in FlexiCubes volume mesh output FlexiCubes' _tetrahedralize builds tets from two sub-procedures (surface pyramids and interior edges) whose vertex orderings do not share a consistent winding. As a result a large fraction of elements came out inverted (negative signed volume) - nearly all surface tets and ~40% of interior tets - which breaks FEA solvers that require a positive signed volume / Jacobian on every element. Add _orient_tets to normalize every tet to positive orientation by swapping two vertices where the signed volume is negative. This only reorders integer indices, so element geometry, |volume|, and gradients to the vertices are all preserved (the extractor stays differentiable). Add regression tests asserting no inverted tets are produced. * Remove degenerate zero-volume tets from FlexiCubes output The interior tetrahedralization sub-procedure can emit elements whose four vertices are exactly coplanar (the two dual-mesh vertices land symmetric about the grid edge), yielding zero-volume tets that fail the positive-Jacobian requirement of FEA solvers just like inverted ones. Drop these elements in _orient_tets and log 'removed x elements with 0 volume'. Coplanarity is detected with a tolerance relative to the Hadamard bound of the determinant rather than an exact zero compare, since the rounding of an exactly-degenerate triple product depends on association order. The measured relative volumes are cleanly bimodal (degenerates at <=1e-7, real elements at >=1e-5), so the 1e-5 cutoff removes only degenerate elements. * Drop caplog assertion from degenerate-tet test * style: format code with Black This commit fixes the style issues introduced in efe750d according to the output from Black. Details: #63 * Address review: explicit grid bounds in test, no_grad in _orient_tets construct_voxel_grid defaults to bounds [-0.05, 1.05] in this repo, so scaling by 2 did not produce the [-1, 1] domain the test comment claimed; pass explicit bounds instead. Also wrap the orientation classification in torch.no_grad() since it only derives integer index masks. * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * add the threshold factor as an argument and merge main (#71) * fix bounds slicing for xmin and xmax calculations (#64) * Add homogenization (#65) * Add test experiment for homogenization model with training artifacts - Introduced new experiment directory for testing homogenization. - Added latest model, optimizer parameters, latent codes, and logs as binary files. - Created specs.json to define network architecture and training parameters. - Added training summary in training_summary.json. - Implemented a test function to train the homogenization model in test_train_model.py. * Add homogenization network and update training loss calculation * added xlim option back to plot sdf * Update test experiment specs and data directory for homogenization model * Refactor homogenization model tests to use shared data directory fixture * set default dtype to float32 in test train model * reduced test duration by reducing sampling points * fix retry 429 error * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Fix negative Jacobian at mesh resolution 10 by filtering tets in float64 The orientation check ran in float32 but torchfem evaluates Jacobians in float64 (after verts.to(float64)). Tets with a tiny positive float32 volume can flip negative in float64, causing the "Negative Jacobian" exception. Compute the final validity mask in float64 so the filter is consistent with torchfem. * added HF secret --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Claude <noreply@anthropic.com> * Fix wrong module loading (#66) * Refactor model loading to handle module prefix in state_dict more efficiently * added some additional output checks for the model export * replaced deprecated torch.linalg.norm argument axes * Fix type comparison in optimization (#67) * Fix type comparison * Add previous type checks for compatibility reasons --------- Co-authored-by: Aron Längert <e11916873@student.ilsb.tuwien.ac.at> * added pypi publish workflow * Fix publish workflow (#69) * added pypi environment * fixed version criteria * added guard to only trigger on main * Potential fix for pull request finding Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> * Skip publish job on non-tag pushes in PyPI workflow (#70) * Initial plan * chore: start publish failure investigation Co-authored-by: mkofler96 <18218171+mkofler96@users.noreply.github.com> * fix(ci): skip publish job on branch pushes Co-authored-by: mkofler96 <18218171+mkofler96@users.noreply.github.com> * chore: revert unintended uv lockfile changes Co-authored-by: mkofler96 <18218171+mkofler96@users.noreply.github.com> --------- Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com> Co-authored-by: mkofler96 <18218171+mkofler96@users.noreply.github.com> * add threshold_factor argument * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: Michael Kofler <michael.kofler@tuwien.ac.at> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Claude <noreply@anthropic.com> Co-authored-by: Aron Längert <e11916873@student.ilsb.tuwien.ac.at> Co-authored-by: Michael Kofler <rasta.kof@gmail.com> Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> Co-authored-by: Copilot <198982749+Copilot@users.noreply.github.com> Co-authored-by: mkofler96 <18218171+mkofler96@users.noreply.github.com> * Revert "add the threshold factor as an argument and merge main (#71)" This reverts commit 7081e77. * add threshold_factor argument * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: Claude <noreply@anthropic.com> Co-authored-by: deepsource-autofix[bot] <62050782+deepsource-autofix[bot]@users.noreply.github.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Aron Längert <18172321+ALaengert99@users.noreply.github.com> Co-authored-by: Aron Längert <e11916873@student.ilsb.tuwien.ac.at> Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> Co-authored-by: Copilot <198982749+Copilot@users.noreply.github.com> Co-authored-by: mkofler96 <18218171+mkofler96@users.noreply.github.com>
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