luz 0.2.0
New features
- Allow users to provide the minimum and maximum number of epochs when calling
fit.luz_module_generator()
. Removed ctx$epochs
from context object and replaced it with ctx$min_epochs
and ctx$max_epochs
(#53, @mattwarkentin).
- Early stopping will now only occur if the minimum number of training epochs has been met (#53, @mattwarkentin).
- Added
cuda_index
argument to accelerator
to allow selecting an specific GPU when multiple are present (#58, @cmcmaster1).
- Implemented
lr_finder
(#59, @cmcmaster1).
- We now handle different kinds of data arguments passed to
fit
using the as_dataloader()
method (#66).
valid_data
can now be scalar value indicating the proportion of data
that will be used for fitting. This only works if data
is a torch dataset or a list. (#69)
- You can now supply
dataloader_options
to fit
to pass additional information to as_dataloader()
. (#71)
- Implemented the
evaluate
function allowing users to get metrics from a model in a new dataset. (#73)
Bug fixes
- Fixed bug in CSV logger callback that was saving the logs as a space delimited file (#52, @mattwarkentin).
- Fixed bug in the length of the progress bar for the validation dataset (#52, @mattwarkentin).
- Fixed bugs in early stopping callback related to them not working properly when
patience = 1
and when they are specified before other logging callbacks. (#76)
Internal changes
ctx$data
now refers to the current in use data
instead of always refering to ctx$train_data
. (#54)
- Refactored the
ctx
object to make it safer and avoid returing it in the output. (#73)
luz 0.1.0
- Added a
NEWS.md
file to track changes to the package.