Release v0.11.0 · mlverse/torch

Breaking changes

load_state_dict() for optimizers now default to cloning the tensors in the state dict, so they don't keep references to objects in the dict. (#1041)

Added nn_utils_weight_norm (#1025)
Added support for reading from ordered state dicts serialized with PyTorch. (#1031)
Added jit_ops allowing to access JIT operators. (#1023)
Added with_device and local_device to allow temporarily modify the default device tensors get initialized. (#1034)
nnf_gelu() and nn_gelu() gained the approximate argument. (#1043)
Implemented != for torch devices. (#1042)
Allows setting the dtype with a string. (#1045)
You can now create a named list of modules using nn_module_dict(). (#1046)
Faster load_state_dict(), also using less memory. It' possible to use the legacy implementation if required, see PR. (#1051)
Export helpers for handling RNG state, and temprarily modifying it. (#1057)
Added support for converting half tensors into R with as.numeric(). (#1056)
Added new torch_tensor_from_buffer() and buffer_from_torch_tensor() that allow low level creation of torch tensors. (#1061, #1062)

Improved documentation for LBFGS optimizer. (#1035)
Added a message asking the user to restart the session after a manual installation with install_torch(). (#1055)

Fixed bug related to handling of non-persistent buffers. They would get added to the state_dict() even if they should not. (#1036)
Fixed a typo in the optim_adamw class name.
Fixed nn_cross_entropy_loss class name. (#1043)
Fixed bug in LBFGS w/ line search. (#1048)
Correctly handle the installation when RemoteSha is a package version. (#1058)

Started building LibLantern on macOS 11 instead of macOS12 for maximum compatibility. (#1026)
Added CXXSTD to Makevars to enable C+11 compilation options.
Refactored codepath for TensorOptions and now all tensors initialization are handled by the same codepath. (#1033)
Added internal argument .refer_to_state_dict to the load_state_dict() nn_module() method. Allows loading the state dict into the model keeping parmaters as references to that state dict. (#1036)