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Fix Tutorial Export + Add Dynamic Tests #640

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@dario-coscia dario-coscia commented Sep 14, 2025 •
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Description

This PR fixes #587 .

Detail description

  • Updated deployer.yml
    Export tutorials in HTML format. Each month, when the documentation is built, tutorials are automatically built alongside the docs. This removes the need to store tutorials in the repository, reducing repo size and speeding up clones.

  • Updated tester.yml
    Added a step to dynamically generate placeholder tutorials for the documentation build.
    This ensures that documentation can be successfully tested even when the actual tutorials haven’t been exported yet, while keeping tutorial execution checks separate.

  • Added a monthly tutorial test workflow
    Ensures that all tutorials run successfully, catching errors early. It also works on workflow_dispatch, so it can be used for PR.

  • Added a comment-triggered tutorial export workflow
    By commenting /tutorial-exporter [tutorial number] on a PR, the corresponding Jupyter notebook can be exported to a .py file. This is useful for exporting tutorials when creating a new PR.

Checklist

  • Code follows the project’s Code Style Guidelines
  • Tests have been added or updated
  • Documentation has been updated if necessary
  • Pull request is linked to an open issue

@dario-coscia dario-coscia self-assigned this Sep 14, 2025
@dario-coscia dario-coscia added pr-to-review Label for PR that are ready to been reviewed maintenance labels Sep 14, 2025
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github-actions bot commented Sep 14, 2025 •
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Code Coverage Summary

Filename                                                                  Stmts    Miss  Cover    Missing
----------------------------------------------------------------------  -------  ------  -------  -------------------------------------------------------------------------------------------------------
__init__.py                                                                   7       0  100.00%
graph.py                                                                    114      11  90.35%   99-100, 112, 124, 126, 142, 144, 166, 169, 182, 271
label_tensor.py                                                             251      28  88.84%   81, 121, 144-148, 165, 177, 182, 188-193, 273, 280, 332, 334, 348, 444-447, 490, 537, 629, 664-673, 710
operator.py                                                                  72       2  97.22%   269, 465
trainer.py                                                                   75       5  93.33%   195-204, 293, 314, 318
type_checker.py                                                              22       0  100.00%
utils.py                                                                     73      11  84.93%   59, 75, 141, 178, 181, 184, 220-223, 268
adaptive_function/__init__.py                                                 3       0  100.00%
adaptive_function/adaptive_function.py                                       55       0  100.00%
adaptive_function/adaptive_function_interface.py                             51       6  88.24%   98, 141, 148-151
callback/__init__.py                                                          5       0  100.00%
callback/normalizer_data_callback.py                                         68       1  98.53%   141
callback/optimizer_callback.py                                               23       0  100.00%
callback/processing_callback.py                                              49       5  89.80%   42-43, 73, 168, 171
callback/refinement/__init__.py                                               3       0  100.00%
callback/refinement/r3_refinement.py                                         28       1  96.43%   88
callback/refinement/refinement_interface.py                                  50       5  90.00%   32, 59, 67, 72, 78
condition/__init__.py                                                         7       0  100.00%
condition/condition.py                                                       19       1  94.74%   141
condition/condition_interface.py                                             37       4  89.19%   32, 76, 95, 125
condition/data_condition.py                                                  26       1  96.15%   78
condition/domain_equation_condition.py                                       19       0  100.00%
condition/input_equation_condition.py                                        43       1  97.67%   157
condition/input_target_condition.py                                          44       1  97.73%   172
data/__init__.py                                                              3       0  100.00%
data/data_module.py                                                         201      22  89.05%   41-52, 132, 172, 193, 232, 313-317, 323-327, 399, 466, 546, 637, 639
data/dataset.py                                                              82       7  91.46%   42, 123-126, 256, 293
domain/__init__.py                                                           10       0  100.00%
domain/cartesian.py                                                         112      10  91.07%   37, 47, 75-76, 92, 97, 103, 246, 256, 264
domain/difference_domain.py                                                  25       2  92.00%   54, 87
domain/domain_interface.py                                                   20       5  75.00%   37-41
domain/ellipsoid.py                                                         104      24  76.92%   52, 56, 127, 250-257, 269-282, 286-287, 290, 295
domain/exclusion_domain.py                                                   28       1  96.43%   86
domain/intersection_domain.py                                                28       1  96.43%   85
domain/operation_interface.py                                                26       1  96.15%   88
domain/simplex.py                                                            72      14  80.56%   62, 207-225, 246-247, 251, 256
domain/union_domain.py                                                       25       1  96.00%   43
equation/__init__.py                                                          4       0  100.00%
equation/equation.py                                                         15       1  93.33%   56
equation/equation_factory.py                                                101       1  99.01%   181
equation/equation_interface.py                                                4       0  100.00%
equation/system_equation.py                                                  20       0  100.00%
loss/__init__.py                                                              9       0  100.00%
loss/linear_weighting.py                                                     14       0  100.00%
loss/loss_interface.py                                                       17       2  88.24%   45, 51
loss/lp_loss.py                                                              15       0  100.00%
loss/ntk_weighting.py                                                        18       0  100.00%
loss/power_loss.py                                                           15       0  100.00%
loss/scalar_weighting.py                                                     16       0  100.00%
loss/self_adaptive_weighting.py                                              12       0  100.00%
loss/weighting_interface.py                                                  29       3  89.66%   35, 41-42
model/__init__.py                                                            13       0  100.00%
model/average_neural_operator.py                                             31       2  93.55%   73, 82
model/deeponet.py                                                            93      13  86.02%   187-190, 209, 240, 283, 293, 303, 313, 323, 333, 488, 498
model/equivariant_graph_neural_operator.py                                   51       1  98.04%   217
model/feed_forward.py                                                        89      11  87.64%   58, 195, 200, 278-292
model/fourier_neural_operator.py                                             78      10  87.18%   96-100, 110, 155-159, 218, 220, 242, 342
model/graph_neural_operator.py                                               40       2  95.00%   58, 60
model/kernel_neural_operator.py                                              34       6  82.35%   83-84, 103-104, 123-124
model/low_rank_neural_operator.py                                            27       2  92.59%   89, 98
model/multi_feed_forward.py                                                  12       5  58.33%   25-31
model/pirate_network.py                                                      27       1  96.30%   118
model/sindy.py                                                               21       0  100.00%
model/spline.py                                                              89      37  58.43%   30, 41-66, 69, 128-132, 135, 159-177, 180
model/block/__init__.py                                                      13       0  100.00%
model/block/average_neural_operator_block.py                                 12       0  100.00%
model/block/convolution.py                                                   64      13  79.69%   77, 81, 85, 91, 97, 111, 114, 151, 161, 171, 181, 191, 201
model/block/convolution_2d.py                                               146      27  81.51%   155, 162, 282, 314, 379-433, 456
model/block/embedding.py                                                     48       7  85.42%   93, 143-146, 155, 168
model/block/fourier_block.py                                                 31       0  100.00%
model/block/gno_block.py                                                     22       4  81.82%   73-77, 87
model/block/integral.py                                                      18       4  77.78%   22-25, 71
model/block/low_rank_block.py                                                24       0  100.00%
model/block/orthogonal.py                                                    37       0  100.00%
model/block/pirate_network_block.py                                          25       1  96.00%   89
model/block/pod_block.py                                                     75      10  86.67%   56-59, 71, 84, 114, 151-156, 191, 216
model/block/rbf_block.py                                                    179      25  86.03%   18, 42, 53, 64, 75, 86, 97, 223, 280, 282, 298, 301, 329, 335, 363, 367, 511-524
model/block/residual.py                                                      46       0  100.00%
model/block/spectral.py                                                      83       4  95.18%   132, 140, 262, 270
model/block/stride.py                                                        28       7  75.00%   55, 58, 61, 67, 72-74
model/block/utils_convolution.py                                             22       3  86.36%   58-60
model/block/message_passing/__init__.py                                       6       0  100.00%
model/block/message_passing/deep_tensor_network_block.py                     21       0  100.00%
model/block/message_passing/en_equivariant_network_block.py                  47       1  97.87%   164
model/block/message_passing/equivariant_graph_neural_operator_block.py       36       0  100.00%
model/block/message_passing/interaction_network_block.py                     23       0  100.00%
model/block/message_passing/radial_field_network_block.py                    20       0  100.00%
optim/__init__.py                                                             5       0  100.00%
optim/optimizer_interface.py                                                  7       0  100.00%
optim/scheduler_interface.py                                                  7       0  100.00%
optim/torch_optimizer.py                                                     14       0  100.00%
optim/torch_scheduler.py                                                     19       2  89.47%   5-6
problem/__init__.py                                                           6       0  100.00%
problem/abstract_problem.py                                                 117      12  89.74%   39-40, 59-70, 149, 161, 179, 253, 257, 286
problem/inverse_problem.py                                                   22       0  100.00%
problem/parametric_problem.py                                                 8       1  87.50%   29
problem/spatial_problem.py                                                    8       0  100.00%
problem/time_dependent_problem.py                                             8       0  100.00%
problem/zoo/__init__.py                                                       8       0  100.00%
problem/zoo/advection.py                                                     23       4  82.61%   20, 73-75
problem/zoo/allen_cahn.py                                                    23       3  86.96%   20-22
problem/zoo/diffusion_reaction.py                                            32       5  84.38%   103-113
problem/zoo/helmholtz.py                                                     22       4  81.82%   59, 78-82
problem/zoo/inverse_poisson_2d_square.py                                     48       3  93.75%   44-50
problem/zoo/poisson_2d_square.py                                             16       3  81.25%   61-66
problem/zoo/supervised_problem.py                                            11       0  100.00%
solver/__init__.py                                                            6       0  100.00%
solver/garom.py                                                             107       2  98.13%   129-130
solver/solver.py                                                            188      10  94.68%   195, 218, 290, 293-294, 353, 435, 518, 559, 565
solver/ensemble_solver/__init__.py                                            4       0  100.00%
solver/ensemble_solver/ensemble_pinn.py                                      23       1  95.65%   104
solver/ensemble_solver/ensemble_solver_interface.py                          27       0  100.00%
solver/ensemble_solver/ensemble_supervised.py                                 9       0  100.00%
solver/physics_informed_solver/__init__.py                                    8       0  100.00%
solver/physics_informed_solver/causal_pinn.py                                47       3  93.62%   157, 166-167
solver/physics_informed_solver/competitive_pinn.py                           58       0  100.00%
solver/physics_informed_solver/gradient_pinn.py                              17       0  100.00%
solver/physics_informed_solver/pinn.py                                       18       0  100.00%
solver/physics_informed_solver/pinn_interface.py                             54       3  94.44%   75, 166, 222
solver/physics_informed_solver/rba_pinn.py                                   74       1  98.65%   324
solver/physics_informed_solver/self_adaptive_pinn.py                        104       1  99.04%   392
solver/supervised_solver/__init__.py                                          4       0  100.00%
solver/supervised_solver/reduced_order_model.py                              24       1  95.83%   137
solver/supervised_solver/supervised.py                                        7       0  100.00%
solver/supervised_solver/supervised_solver_interface.py                      25       1  96.00%   90
TOTAL                                                                      5008     434  91.33%

Results for commit: 9d465fc

Minimum allowed coverage is 80.123%

♻️ This comment has been updated with latest results

@dario-coscia dario-coscia force-pushed the fix_tut_exporter branch 2 times, most recently from f053ad2 to 547a4b0 Compare September 14, 2025 17:19
GiovanniCanali
GiovanniCanali approved these changes Sep 15, 2025
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Thank you @dario-coscia for the PR.

Everything looks good to me. I just have one point regarding reducing the repository size. I believe that although we are removing the HTML files, they still remain in the Git history, which means the repository size will not actually decrease. I’m not entirely sure, but it’s worth checking.

Perhaps @ndem0 can provide more insight on this.

@dario-coscia
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Thank you @dario-coscia for the PR.

Everything looks good to me. I just have one point regarding reducing the ?epository size. I believe that although we are removing the HTML files, they still remain in the Git history, which means the repository size will not actually decrease. I’m not entirely sure, but it’s worth checking.

Perhaps @ndem0 can provide more insight on this.

Ok I will check this more in details, why do you say so?

@GiovanniCanali
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Thank you @dario-coscia for the PR.
Everything looks good to me. I just have one point regarding reducing the ?epository size. I believe that although we are removing the HTML files, they still remain in the Git history, which means the repository size will not actually decrease. I’m not entirely sure, but it’s worth checking.
Perhaps @ndem0 can provide more insight on this.

Ok I will check this more in details, why do you say so?

It happened to me on a different repository, solved via git filter-repo. To be used carefully.

@dario-coscia dario-coscia mentioned this pull request Sep 19, 2025
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@dario-coscia dario-coscia deleted the fix_tut_exporter branch October 10, 2025 10:26
@dario-coscia dario-coscia restored the fix_tut_exporter branch October 13, 2025 12:29
@dario-coscia dario-coscia reopened this Oct 13, 2025
@dario-coscia dario-coscia requested a review from a team as a code owner October 13, 2025 12:29
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dario-coscia commented Oct 13, 2025 •
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I think this PR was closed by mistake, reopen it now. @ndem0 waiting for your review

@dario-coscia dario-coscia removed the request for review from a team October 13, 2025 12:30
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