TorchStudio 0.9.14
This release brings lots of performance, stability and UI improvements. It also adds a new GenericLoader dataset, which can handle most common image, audio and numpy tensors datasets formats, for either classification, segmentation or regression.
- new GenericLoader dataset, which can load several kinds of image, audio and numpy tensors datasets for either classification, segmentation or regression
- TorchStudio projects now use much less RAM
- transfers with local and remote servers is now much faster
- new weights and state transfers from local and remote servers is now asynchronous
- only best weights and state are transferred to speed up training and optimize memory use
- dataset can now be cached on local and remote trainign server to speed up the start of new trainings
- environment installer now compatible with the newest conda installers
- Patience value can now be defined (in number of epochs) when Early Stopping is checked
- channel colors can now be defined for Bitmap, Spectrogram and Volume renderers
- default threshold value for accuracy metric set to 0.01
- new best weights indicator in the loss and metric plots (both in Model tabs and Dashboard panel)
- loss indicator now plotted on a square root scale for easier readibility
- model color indicator added to the parameters plot (in the Dashboard panel)
- tool tips improved
- fix an issue when loading remote dataset
- fix an issue where inference could stop working
- fix an issue where tensor display and analysis could stop working
- fix an issue where tcp decoding could break
- fix project opening when a dataset is loaded from a remote server
- fix metrics not properly displaying epochs beyond 100