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Additional tests for different hardware accelerators setups. Please check out the tests/pipelines folder for more information.
BackwardCallback and BackwardCallbackOrder as an abstraction on top of loss.backward. Now you could easily log model gradients or transform them before OptimizerCallback.
CheckpointCallbackOrder for ICheckpointCallback.
Changed
Minimal python version moved to 3.7, minimal PyTorch version moved to 1.4.0.
Engines were rewritten on top of Accelerate. First, we found these two abstractions very close to each other. Second, Accelerate provides additional user-friendly API and more stable API for "Nvidia APEX" and "Facebook Fairscale" - it does not support them.
SelfSupervisedRunner moved to the examples folder from the Catalyst API. The only Runners API, that will be supported in the future: IRunner, Runner, ISupervisedRunner, SupervisedRunner due to their consistency. If you are interested in any other Runner API - feel free to write your own CustomRunner and use SelfSupervisedRunner as an example.
Runner.{global/stage}_{batch/loader/epoch}_metrics renamed to Runner.{batch/loader/epoch}_metrics
CheckpointCallback rewritten from scratch.
Catalyst registry moved to full-imports-paths only.
Logger API changed to receive IRunner for all log_* methods.
Metric API: topk_args renamed to topk.
Contrib API: init imports from catalyst.contrib - removed, use from catalyst.contrib.{smth} import {smth}. Could be change to full-imports-only in future versions for stability.
All quickstarts, minimal examples, notebooks, and pipelines moved to the new version.
Codestyle moved to 89 right margin. Honestly speaking, it's much easier to maintain Catalyst with 89 right margin on MBP'16.
Removed
ITrial removed.
Stages support removed. While we embrace stages in deep learning experiments, current hardware accelerators are not prepared well for such setups. Additionally, ~95% of dl pipelines are single-stage. Multi-stage runner support is under review. For multi-stage support, please define a CustomRunner with rewritten API.
Config/Hydra API support removed. Config API is under review. For now, you could write your own Config API with hydra-slayer if needed.
catalyst-dl scripts removed. Without Config API we don't need them anymore.
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[22.02] - 2022-02-13
Tl;dr
Added
tests/pipelines
folder for more information.BackwardCallback
andBackwardCallbackOrder
as an abstraction on top ofloss.backward
. Now you could easily log model gradients or transform them beforeOptimizerCallback
.CheckpointCallbackOrder
forICheckpointCallback
.Changed
3.7
, minimal PyTorch version moved to1.4.0
.examples
folder from the Catalyst API. The only Runners API, that will be supported in the future:IRunner
,Runner
,ISupervisedRunner
,SupervisedRunner
due to their consistency. If you are interested in any other Runner API - feel free to write your ownCustomRunner
and useSelfSupervisedRunner
as an example.Runner.{global/stage}_{batch/loader/epoch}_metrics
renamed toRunner.{batch/loader/epoch}_metrics
CheckpointCallback
rewritten from scratch.IRunner
for alllog_*
methods.topk_args
renamed totopk
.catalyst.contrib
- removed, usefrom catalyst.contrib.{smth} import {smth}
. Could be change to full-imports-only in future versions for stability.89
right margin. Honestly speaking, it's much easier to maintain Catalyst with89
right margin on MBP'16.Removed
ITrial
removed.CustomRunner
with rewritten API.catalyst-dl
scripts removed. Without Config API we don't need them anymore.Nvidia Apex
,Fairscale
,Albumentations
,Nifti
,Hydra
requiremets removed.OnnxCallback
,PruningCallback
,QuantizationCallback
,TracingCallback
removed from callbacks API. These callbacks are under review now.If you have any questions on the Catalyst 22 edition updates, please join Catalyst slack for discussion.
This discussion was created from the release Catalyst 22.02.
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