Changelog

Breaking changes

Made torch_one_hot and nnf_one_hot use 1-based indexing. (#410)
nn_module$eval() and nn_module$train() now return a callable nn_module instead of a nn_Module. (#425)

Added a custom CPU allocator to call gc when torch might need more memory (#402)
Updated to LibTorch 1.7.1 (#412)
Allow listing all nested modules in a nn_module (#417)
Allow modifying the requires_grad attribute using the $<- operator (#419)
Added length method for the nn_sequential container. (#423)
Added support for CUDA 11 on linux (#424)

Small improvement to nn_module documentation (#399).
The getting started section has been removed from the pkgdown website in favor of the new guide in the landing page (#401)
Updated the landing page to include a getting started tutorial (#400)

Dataloaders now returns a coro::exhausted intead of raising stop_iteration_error when the dataloader exceeds. (#366)
Fixed bug that would happen with functions that need to transform tensors from 0-based to 1-based in the GPU. (#317)
Fixed torch_argsort and x$argsort to return 1-based indexes (#342)
Fixed torch_argmax, torch_argmin, x$argmax() and x$argmin() return 1-based indexes. (#389)

Added $element_size() method (@dirkschumacher #322)
Added $bool() method (@dirkschumacher #323)
torch__addr and torch__addr_ have been removed as they are no longer available in LibTorch 1.7.
We now check the MD5 hashes of downloaded LibTorch binaries. (@dirkschumacher #325)
Added a Distribution abstract class (@krzjoa #333)
Updated to LibTorch 1.7 (#337)
We now warn when converting long tensors to R and there’s a chance of an integer overflow. (#347)
Allow private and active methods in nn_module’s and dataset’s. (#349)
Added nn_batch_norm3d (@mattwarkentin #354)
Added nn_lstm and nn_gru modules. (#362)
Added distribution constraints (@krzjoa #364)
Dataloaders now use the num_workers argument to load data in parallel (#366)
Added Exponential Family classs to distributions (#373)
Added Dockerfile and docker compose file with GPU support, with a how-to guide. (#380 #386)
Added R 3.6 to the CI system and fixed compilation from source with it on Windows (#387)
Initial support for JIT tracing (#377)
Added LBFGS optimizer (#392)
Improved the nn_module UI by improving autocomplete support and adding a print method (#391)

Fixed bug when trying to print the grad_fn of a Tensor that doesn’t have one. See (#321)
Refactored the optimizers code to avoid duplication of parameter checks, etc. (@dirkschumacher #328)
Fixed torch_norm so it can be called with a dim argument. (#345)
Fixed crash when calling torch_hann_window with an invalid NULL window_length. (#351)
Fixed torch_stft calls for LibTorch 1.7 (added the return_complex argument) (#355)
Fixed bug when strides were NULL in some pooling operations. (#361)
Use nvcc --version instead of nvidia-smi to find the CUDA version as nvidia-smi reports the latest supported version and not the installed one. (#363)
Corrected URL to download LibTorch under Linux with CUDA 10.2 (#367)
Fixed handling of integer tensors when indexing tensors (#385)
Fixed bug when passing length zero vectors to lantern/libtorch. (#388)

Fixed bug that made RandomSampler(replacement = TRUE) to never take the last element in the dataset. (84861fa)
Fixed torch_topk and x$topk so the returned indexes are 1-based (#280)
Fixed a bug (#275) that would cause 1 - torch_tensor(1, device = "cuda") to fail because 1 was created in the CPU. (#279)
We now preserve names in the dataloader output (#286)
torch_narrow, Tensor$narrow() and Tensor$narrow_copy are now indexed starting at 1. (#294)
Tensor$is_leaf is now an active method. (#295)
Fixed bug when passing equations to torch_einsum. (#296)
Fixed nn_module_list() to correctly name added modules, otherwise they are not returned when doing state_dict() on it. (#300)
Fixed bug related to random number seeds when using in-place methods. (#303)
Fixed nn_batchnorm* so it returns the same results as PyTorch (#302)
Fixed a bug that made nn_module$parameter when there were shared parameters between layers. (#306)
Fixed $max and $min to return 1-based indexes. (#315)

Expanded the utils_data_default_collate to support converting R objects to torch tensors when needed. (#269)
Added an as.matrix method for torch Tensors. (#282)
By default we now truncate the output of print(totrch_tensor(1:40)) if it spans for more than 30 lines. This is useful for not spamming the console or taking very long to print when you print a very large tensor. (#283)
Added the Adadelta optimizer (@krzjoa #284)
Added support for GPU’s on Windows (#281)
Added the Adagrad optimizer (@krzjoa #289)
Added RMSprop optimizer (@krzjoa #290)
Added the Rprop optimizer (@krzjoa #297)
Added gradient clipping utilities (#299)
Added nnf_contrib_sparsemax and nn_contrib_sparsemax. (#309)
Added ASGD optimizer (@krzjoa #307)
Getters and setters for the number of threads used by torch (#311)