ChangeLog

CHANGES
=======

v0.1.2
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* get_vote_weights_*: use softmax to avoid overflow issues

v0.1.1
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* Priority Vote: Adjusting kernel size for priority vote operations will now affect blurring
* Priority Vote: Consensus threshold can be 0

v0.1.0
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* Add priority\_vote
* Add vote\_with\_distances
* Add voting\_with\_variances to include prior weights

v0.0.6
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* feat(use\_identity\_mapping\_cache): allow caching identity\_mapping() results
* fix: 0.7.0 compatibility (#8)
* Update license in setup.cfg

v0.0.5
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* Update documentation for sample()
* Allow non-square displacement fields
* Clean up identity mapping code
* Remove caching of identity mappings
* Use align\_corners=False from PyTorch 1.3.0 Will no longer work with earlier PyTorch versions
* Convert to using MIT License

v0.0.4
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* Prevent producing NaN in inverse backward pass
* Allow accessing field type as torchfields.Field
* Ensure contiguous gradients in inversion backward pass
* Allow padding to be explicitly given in \_pad()
* Bump required pytorch version to 1.1.0
* Factor out voting, inversion, and util functions
* Update README.md
* Update README.md

v0.0.3
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* Change ndim to ndimension() to support wider range of PyTorch versions

v0.0.2
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* [Fix] affine\_field incorrect dimensions bug

v0.0.1
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* [Fix] inverse not working on cpu
* Add setup.py, setup.cfg, README.md, .gitignore, and requirements.txt
* DisplacementField: minor bug fixes, refactors, and comments
* Safe division to avoid NaNs during backward pass
* Use winding number to test inclusion rather than bounding i,j
* Epsilon for comparison to zero
* Autopad functionality in left inverse
* More efficient left inverse using sparse tensors
* Mean finite vector function
* Inefficient implementation of left inverse
* Add DisplacementField class to abstract displacement field operations
* Initial commit