Tags: wangshaofan1993/learn2learn
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Added ===== * `l2l.vision.datasets.CUBirds200`. Changed ------- * Optimization transforms can be accessed directly through `l2l.optim`, e.g. `l2l.optim.KroneckerTransform`. * All vision models adhere to the `.features` and `.classifier` interface. Fixed ----- * Fix `clone_module` for Modules whose submodules share parameters.
v0.1.2 ====== Added ----- * New example: [Meta-World](https://github.com/rlworkgroup/metaworld) example with MAML-TRPO with it's own env wrapper. (@[Kostis-S-Z](https://github.com/Kostis-S-Z)) * `l2l.vision.benchmarks` interface. * Differentiable optimization utilities in `l2l.optim`. (including `l2l.optim.LearnableOptimizer` for meta-descent) * General gradient-based meta-learning wrapper in `l2l.algorithms.GBML`. * Various `nn.Modules` in `l2l.nn`. * `l2l.update_module` as a more general alternative to `l2l.algorithms.maml_update`. Fixed ----- * clone_module supports non-Module objects. * VGG flowers now relies on tarfile.open() instead of tarfile.TarFile().
Added ----- * A CHANGELOG.md file. * New vision datasets: FC100, tiered-Imagenet, FGVCAircraft, VGGFlowers102. * New vision examples: Reptile & ANIL. * Extensive benchmarks of all vision examples. Changed ------- * Re-wrote TaskDataset and task transforms in Cython, for a 20x speed-up. * Travis testing with different versions of Python (3.6, 3.7), torch (1.1, 1.2, 1.3, 1.4), and torchvision (0.3, 0.4, 0.5). * New Material doc theme with links to changelog and examples. Fixed ----- * Support for `RandomClassRotation` with newer versions of torchvision. * Various minor fixes in the examples. * Add Dropbox download if GDrive fails for FC100.