I think this is no longer needed on the main page, now that all the major documentation versions should be easily available. The page with info for this remains visilble in the documentation
Adds two classmethods to CDIModel and its ptychography subclasses that
allow models to be reconstructed from saved .h5 result files without
needing the original dataset.
- CDIModel base class: add model_class and cdtools_version to
save_results(); add _load_results_dict() helper (restores state_dict
+ training metadata); add from_results_dict() interface method and a
concrete from_results_h5() that reads a file and delegates to
from_results_dict() — subclasses inherit this for free.
- SimplePtycho: make save_results(dataset=None) optional (dataset was
accepted but never used); add from_results_dict() which reconstructs
from probe, obj, wavelength, probe_basis, and min_translation stored
in the state_dict.
- FancyPtycho: add optional translations parameter to __init__,
registered as original_translations buffer; update from_dataset to
pass translations; make corrected_translations(dataset=None) fall back
to self.original_translations when no dataset is provided; make
save_results(dataset=None) use stored translations when no dataset is
provided; add from_results_dict() that detects all optional features
(mask, translation_offsets, weights, near-field propagators, etc.)
from the state_dict and reconstructs the full model. Also fix a latent
bug where background was passed to t.nn.Parameter() without
t.as_tensor(), which now fails when given a numpy array.
All existing tests pass; new tests added for both models verifying that
state_dict, training metadata, and forward pass output are all restored
exactly after a round-trip through from_results_dict and from_results_h5.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Revert test_Adam_gold_balls to default amplitude_mse
- Add new test_intensity_MSE test (gold balls + AdamReconstructor)
- Update near_field threshold to 17 (poisson_nll scale)
Thresholds for test_intensity_MSE to be tuned after GPU run.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Use poisson_nll in test_near_field_ptycho and intensity_mse in
test_Adam_gold_balls to exercise these loss paths end-to-end.
Thresholds left as-is pending re-running on a GPU machine.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
poisson_nll now returns a sum rather than a mean, consistent with the
normalizer pattern. Remove the per-pixel divisions from the numpy
reference calculations accordingly.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Abe Levitan
levita_a
sheng_p1