[22.04] - 2022-04-29

Added

catalyst-tune for Config API added #1411
tests for python 3.9 and 3.10 #1414

Fixed

catalyst compatibility with python 3.10 #1409

- Python
Published by Scitator almost 4 years ago

[22.02.1] - 2022-02-27

"Few fixes and Config API v22 MVP".

Added

catalyst-run for Config API support added #1406

Fixed

Logger API naming #1405

- Python
Published by Scitator almost 4 years ago

[22.02] - 2022-02-13

Tl;dr

Catalyst architecture simplification.
#1395, #1396, #1397, #1398, #1399, #1400, #1401, #1402, #1403.

Added

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.
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.

- Python
Published by Scitator about 4 years ago

[22.02rc0] - 2022-02-07

Tl;dr

Beta version of Catalyst 22 edition.

core architecture moved to Animus-like (stages were removed)
engines moved to Accelerate
config/hydra APIs deprecated in favor of hydra-slayer-custom config runners
dl-based scripts removed from the API
self-supervised runner moved to examples - it's better to have custom still
contrib and utils - truncated
requirements - simplified
codestyle moved to -l 89 (better view on 16'' screen ;) )

- Python
Published by Scitator about 4 years ago

[21.12] - 2021-12-28

Tl;dr

Distributed engines update (multi-node support) and many other improvements.

Added

MNIST dataset for SSL banchmark (#1368)
MoveiLens 20M dataset #1336
logger property for logging customization (#1372)
MacridVAE example (#1363)
SSL benchmark results (#1374)
Neptune example (#1377)
multi-node support for engines (#1364)

Changed

RL examples update to last version (#1370)
DDPLoaderWrapper updated to new version (#1385)
num_classes for classification metrics became optional (#1379)
colab ci/cd update to new verion

Removed

-

Fixed

requests requirements for catalyst[cv] added (#1371)
loader step counter (#1374)
detection example data preprocessing (#1369)
gradient clipping with fp16 runs (#1378)
config API fix for DDP runs (#1383)
checkpoint creation for fp16 engines (#1382)

Contributors ❤️

@bagxi @ditwoo @MrNightSky @Nimrais @y-ksenia @sergunya17 @Thiefwerty @zkid18

- Python
Published by Scitator about 4 years ago

[21.11] - 2021-11-30

Tl;dr

Framework architecture simplification and speedup + SSL & RecSys extensions.

Added

MultiVAE RecSys example (#1340)`
Returned resume support - resolved #1193 (#1349)
Smoothing dice loss to contrib (#1344)
profile flag for runner.train (#1348)
MultiDAE RecSys example (#1356)
SETTINGS.log_batch_metrics, SETTINGS.log_epoch_metrics, SETTINGS.compute_per_class_metrics for framework-wise Metric & Logger APIs specification (#1357)
log_batch_metrics and log_epoch_metrics options for all available Loggers (#1357)
compute_per_class_metrics option for all available multiclass/label metrics (#1357)
pytorch benchmark script and simplified MNIST (#1360)

Changed

A few framework simplifications were made (#1346):
- catalyst-contrib scripts reduced to collect-env and project-embeddings only
- catalyst-dl scripts recuded to run and tune only
- transforms. prefix deprecated for Catalyst-based transforms
- catalyst.tools moved to catalyst.extras
- task-dependent extensions from catalyst.data moved to catalyst.contrib.data
- catalyst.data.transforms moved to catalyst.contrib.data.transforms
- Normalize, ToTensor transforms renamed to NormalizeImage, ImageToTensor
- metric learning extensions moved to catalyst.contrib.data
- catalyst.contrib moved to code-as-a-documentation development
- catalyst[cv] and catalyst[ml] extensions moved to flatten architecture design; examples: catalyst.contrib.data.dataset_cv, catalyst.contrib.data.dataset_ml
- catalyst.contrib moved to flatten architecture design; exampels: catalyst.contrib.data, catalyst.contrib.datasets, catalyst.contrib.layers, catalyst.contrib.models, catalyst.contrib.optimizers, catalyst.contrib.schedulers
- internal functionality moved to ***._misc modules
- catalyst.utils.mixup moved to catalyst.utils.torch
- catalyst.utils.numpy moved to catalyst.contrib.utils.numpy
default logging logic moved from "batch & epoch" to "epoch"-only to save computation time during logging; to respecify, please use:
- SETTINGS.log_batch_metrics=True/False or os.environ["CATALYST_LOG_BATCH_METRICS"]
- SETTINGS.log_epoch_metrics=True/False or os.environ["CATALYST_LOG_EPOCH_METRICS"]
default metrics computation moved from "per-class & aggregations" to "aggregations"-only to save computation time during logging; to respecify, please use:
- SETTINGS.compute_per_class_metrics=True/False or os.environ["CATALYST_COMPUTE_PER_CLASS_METRICS"]
no transformations required for MNIST contrib dataset (#1360

Removed

A few framework simplifications were made (#1346):
- catalyst.contrib.pandas
- catalyst.contrib.parallel
- catalyst.contrib.models.cv
- a few catalyst.utils.misc functions
- catalyst.extras removed from the public documentation

Fixed

documentation search error (21.10 only) (#1346)
docs examples (#1362)
Self-Supervised benchmark: (#1365), (#1361)

Contributors ❤️

@asteyo @Dokholyan @Nimrais @y-ksenia @sergunya17

- Python
Published by Scitator about 4 years ago

[21.10] - 2021-10-30

Tl;dr

Readmes and tutorials with a few ddp fixes.

Added

RSquareLoss (#1313)
Self-Supervised example updates: (#1305), (#1322), (#1325), (#1335)
Albert training example (#1326)
YOLO-X (new) detection example and refactoring (#1324)
TopKMetric asbtraction (#1330)

Changed

simlified readme (#1312)
improved DDP tutorial (#1327)
CMCMetric renamed from <prefix>cmc<suffix><k> to <prefix>cmc<k><suffix> (#1330)

Removed

-

Fixed

Zero seed error (#1329)
updated codestyle issues (#1331)
TopK metrics: (#1330), (#1334), (#1339)
--expdir param for catalyst-dl run (#1338)
ControlFlowCallback for distributed setup (#1341)

- Python
Published by Scitator over 4 years ago

[21.09] - 2021-09-30

Added

CometLogger support (#1283)
CometLogger examples (#1287)
XLA docs (#1288)
Contarstive loss functions: NTXentLoss (#1278), SupervisedContrastiveLoss (#1293)
Self supervised learning: ISelfSupervisedRunner, SelfSupervisedConfigRunner, SelfSupervisedRunner, SelfSupervisedDatasetWrapper (#1278)
SimCLR example (#1278)
Superivised Contrastive example (#1293)
extra warnings for runner-callbacks interaction (#1295)
CategoricalRegressionLoss and QuantileRegressionLoss to the contrib (#1295)
R2 score metric (#1274)

Changed

Improved WandbLogger to support artifacts and fix logging steps (#1309)
full Runner cleanup, with callbacks and loaders destruction, moved to PipelineParallelFairScaleEngine only (#1295)
HuberLoss renamed to HuberLossV0 for the PyTorch compatibility (#1295)
codestyle update (#1298)
BalanceBatchSampler - deprecated (#1303)

Removed

-

Fixed

CI/CD (#1292), (#1299), (#1304), (#1306)
Optuna configs (#1296), (#1296)

Contributors ❤️

@asteyo @AyushExel @bagxi @DN6 @gr33n-made @Nimrais @Podidiving @y-ksenia

- Python
Published by Scitator over 4 years ago

catalyst - Catalyst 21.09rc1 - release wheels update check 2.0

- Python
Published by Scitator over 4 years ago

catalyst - Catalyst 21.09rc0 - release wheels update check

Hi guys, nice project!

This is the test case release to check out our updated infrastructure.

- Python
Published by Scitator over 4 years ago

[21.08] - 2021-08-31

Added

RecSys loss functions: AdaptiveHingeLoss, BPRLoss, HingeLoss, LogisticLoss, RocStarLoss, WARPLoss (#1269, #1282)
object detection examples (#1271)
SklearnModelCallback (#1261)
Barlow Twins example (#1261)
TPU/XLA support (#1275)
- with updated example
native sync_bn support for all available engines (#1275)
- Torch, AMP, Apex, FairScale

Changed

Registry moved to hydra-slayer (#1264))
(#1275)
- batch metrics sync removed from ddp-runs to speedup training process
- AccumulationMetric renamed to AccumulativeMetric
- moved from catalyst.metrics._metric to catalyst.metrics._accumulative
- accululative_fields renamed to keys

Removed

-

Fixed

PeriodicLoaderCallback docsting (#1279)
matplotlib issue (#1272)
sample counter for the loader (#1285)

Contributors ❤️

@bagxi @Casyfill @ditwoo @Nimrais @penguinflys @sergunya17 @zkid18

- Python
Published by Scitator over 4 years ago

[21.07] - 2021-07-29

Added

added pre-commit hook to run codestyle checker on commit (#1257)
on publish github action for docker and docs added (#1260)
MixupCallback and utils.mixup_batch (#1241)
Barlow twins loss (#1259)
BatchBalanceClassSampler (#1262)

Changed

-

Removed

-

Fixed

make expdir in catalyst-dl run optional (#1249)
Bump neptune-client from 0.9.5 to 0.9.8 in requirements-neptune.txt (#1251)
automatic merge for master (with Mergify) fixed (#1250)
Evaluate loader custom model bug was fixed (#1254)
BatchPrefetchLoaderWrapper issue with batch-based PyTorch samplers (#1262)
Adapted MlflowLogger for new config hierarchy (#1263)

Contributors ❤️

@AlekseySh @bagxi @Casyfill @Dokholyan @leoromanovich @Nimrais @y-ksenia

- Python
Published by Scitator over 4 years ago

[21.06] - 2021-06-29

Added

(#1230)
- FairScale support
- DeepSpeed support
- utils.ddp_sync_run function for synchronous ddp run
- CIFAR10 and CIFAR100 datasets from torchvision (no cv-based requirements)
- Catalyst Engines demo
dataset_from_params support in config API (#1231)
transform from params support for config API added (#1236)
samplers from params support for config API added (#1240)
recursive registry.getfromparams added (#1241)
albumentations integration (#1238)
Profiler callback (#1226)

Changed

(#1230)
- loaders creation now wrapper with utils.ddp_sync_run for utils.ddp_sync_run data preparation
- runner support stage cleanup: loaders and callbacks will be deleted on the stage end
- Apex-based engines now support both APEXEngine and ApexEngine registry names

Fixed

multiprocessing in minimal tests hotfix (#1232)
Tracing callback hotfix (#1234)
Engine hotfix for predict_loader (#1235)
(#1230)
- Hydra hotfix due to 1.1.0 version changes
HuberLoss name conflict for pytorch 1.9 hotfix (#1239)

Contributors ❤️

@bagxi @y-ksenia @ditwoo @BorNick @Inkln

- Python
Published by Scitator over 4 years ago

[21.05] - 2021-05-31

Added

Reinforcement learning tutorials (#1205)
customization demo (#1207)
FAQ docs: multiple input and output keys, engine tutorial (#1202)
minimal Config API example (#1215)
Distributed RL example (Catalyst.RL 2.0 concepts) (#1224)
SklearnCallback as integration of sklearn metrics (#1198)

Changed

tests moved to tests folder (#1208)
pipeline tests moved to tests/pipelines (#1215)
updated NeptuneLogger docstrings (#1223)

Removed

-

Fixed

customizing what happens in train() notebook (#1203)
transforms imports under catalyst.data (#1211)
change layerwise to layerwise_params (#1210)
add torch metrics support (#1195)
add Config API support for BatchTransformCallback (#1209)

BONUS: Catalyst workshop videos!

- Python
Published by Scitator over 4 years ago

[21.04.2] - 2021-04-30

Added

Weights and Biases Logger (WandbLogger) (#1176)
Neptune Logger (NeptuneLogger) (#1196)
log_artifact method for logging arbitrary files like audio, video, or model weights to ILogger and IRunner (#1196)

- Python
Published by Scitator almost 5 years ago

catalyst - Catalyst 21.04.1

a small hotfix for catalyst.contrib module

- Python
Published by Scitator almost 5 years ago

[21.04] - 2021-04-17

Added

Nifti Reader (NiftiReader) (#1151)
CMC score and callback for ReID task (ReidCMCMetric and ReidCMCScoreCallback) (#1170)
Market1501 metric learning datasets (Market1501MLDataset and Market1501QGDataset) (#1170)
extra kwargs support for Engines (#1156)
engines exception for unknown model type (#1174)
a few docs to the supported loggers (#1174)

Changed

TensorboardLogger switched from global_batch_step counter to global_sample_step one (#1174)
TensorboardLogger logs loader metric on_loader_end rather than on_epoch_end (#1174)
prefix renamed to metric_key for MetricAggregationCallback (#1174)
micro, macro and weighted aggregations renamed to _micro, _macro and _weighted (#1174)
BatchTransformCallback updated (#1153)

Removed

auto torch.sigmoid usage for metrics.AUCMetric and metrics.auc (#1174)

Fixed

hitrate calculation issue (#1155)
ILoader wrapper usage issue with Runner (#1174)
counters for ddp case (#1174)

- Python
Published by Scitator almost 5 years ago

Fixed

minimal requirements issue (#1147)

- Python
Published by Scitator almost 5 years ago

[21.03.1] - 2021-03-28

Added

Additive Margin SoftMax(AMSoftmax)(#1125)
Generalized Mean Pooling(GeM)(#1084)
Key-value support for CriterionCallback (#1130)
Engine configuration through cmd (#1134)
Extra utils for thresholds (#1134)
Added gradient clipping function to optimizer callback (1124)
FactorizedLinear to contrib (1142)
Extra init params for ConsoleLogger (1142)
Tracing, Quantization, Onnx, Pruninng Callbacks (1127)
_key_value for schedulers in case of multiple optimizers fixed (#1146)

Changed

CriterionCallback now inherits from BatchMetricCallback #1130)
- united metrics computation logic

Removed

Config API deprecated parsings logic (1142) (1138)

Fixed

Data-Model device sync and Engine logic during runner.predict_loader (#1134)
BatchLimitLoaderWrapper logic for loaders with shuffle flag (#1136)
config description in the examples (1142)
Config API deprecated parsings logic (1142) (1138)
RecSys metrics Top_k calculations (#1140)

- Python
Published by Scitator almost 5 years ago

[21.03] - 2021-03-13 (#1095)

Added

Engine abstraction to support various hardware backends and accelerators: CPU, GPU, multi GPU, distributed GPU, TPU, Apex, and AMP half-precision training.
Logger abstraction to support various monitoring tools: console, tensorboard, MLflow, etc.
Trial abstraction to support various hyperoptimization tools: Optuna, Ray, etc.
Metric abstraction to support various of machine learning metrics: classification, segmentation, RecSys and NLP.
Full support for Hydra API.
Full DDP support for Python API.
MLflow support for metrics logging.
United API for model post-processing: tracing, quantization, pruning, onnx-exporting.
United API for metrics: classification, segmentation, RecSys, and NLP with full DDP and micro/macro/weighted/etc aggregations support.

Changed

Experiment abstraction merged into Runner one.
Runner, SupervisedRunner, ConfigRunner, HydraRunner architectures and dependencies redesigned.
Internal settings and registry mechanisms refactored to be simpler, user-friendly and more extendable.
Bunch of Config API test removed with Python API and pytest.
Codestyle now supports up to 99 symbols per line :)
All callbacks/runners moved for contrib to the library core if was possible.
Runner abstraction simplified to store only current state of the experiment run: all validation logic was moved to the callbacks (by this way, you could easily select best model on various metrics simultaneously).
Runner.input and Runner.output merged into united Runner.batch storage for simplicity.
All metric moved from catalyst.utils.metrics to catalyst.metrics.
All metrics now works on scores/metric-defined-input rather that logits (!).
Logging logic moved from Callbacks to appropriate Loggers.
KorniaCallbacks refactored to BatchTransformCallback.

Removed

Lots of unnecessary contrib extensions.
Transforms configuration support through Config API (could be returned in next releases).
Integrated Python cmd command for model pruning, swa, etc (should be returned in next releases).
CallbackOrder.Validation and CallbackOrder.Logging
All 2020 year backward compatibility fixes and legacy support.

Fixed

Docs rendering simplified.
LrFinderCallback.

Release docs, Python API minimal examples, Config/Hydra API example.

- Python
Published by Scitator almost 5 years ago

catalyst -

- Python
Published by bagxi about 5 years ago

[20.12] - 2020-12-20

Added

CVS Logger (#1005)
DrawMasksCallback (#999)
(#1002)
- a few docs
(#998)
- reciprocal_rank metric
- unified recsys metrics preprocessing
(#1018)
- readme examples for all supported metrics under catalyst.metrics
- wrap_metric_fn_with_activation for model outputs wrapping with activation
- extra tests for metrics
(#1039)
- per_class=False option for metrics callbacks
- PrecisionCallack, RecallCallack for multiclass problems
- extra docs

Changed

docs update (#1000)
AMPOptimizerCallback and OptimizerCallback were merged (#1007)
(#1017)
- fixed bug in SchedulerCallback
- Log LRs and momentums for all param groups, not only for the first one
(#1002)
- tensorboard, ipython, matplotlib, pandas, scikit-learn moved to optional requirements
- PerplexityMetricCallback moved to catalyst.callbacks from catalyst.contrib.callbacks
- PerplexityMetricCallback renamed to PerplexityCallback
- catalyst.contrib.utils.confusion_matrix renamed to catalyst.contrib.utils.torch_extra
- many parts of catalyst.data moved to catalyst.contrib.data
- catalyst.data.scripts moved to catalyst.contrib.scripts
- catalyst.utils, catalyst.data.utils and catalyst.contrib.utils restructured
- ReaderSpec renamed to IReader
- SupervisedExperiment renamed to AutoCallbackExperiment
gain functions renamed for dcg/ndcg metrics (#998)
(#1014)
- requirements respecification: catalyst[cv], catalyst[dev], catalyst[log], catalyst[ml], catalyst[nlp],catalyst[tune]
- settings respecification
- extra tests for settings
- contrib refactoring
iou and dice metrics moved to per-class computation (#1031)

Removed

(#1002)
- KNNMetricCallback
- sklearn mode for ConfusionMatrixLogger
- catalyst.data.utils
- unnecessary catalyst.tools.meters
- todos for unnecessary docs
(#1014)
- transformers-based contrib (too unstable)
(#1018)
- ClasswiseIouCallback/ClasswiseJaccardCallback as deprecated on (should be refactored in future releases)

Fixed

prevented modifying config during the experiment and runner initialization (#1004)
a few test for RecSys MAP computation (#1018)
leave batch size the same for default distributed training (#1023)
(#1032)
- Apex: now you can use apex for multiple models training
- Apex: DataParallel is allowed for opt_level other than "O1"

- Python
Published by Scitator about 5 years ago

[20.11] - 2020-11-12

Added

DCG, nDCG metrics (#881)
MAP calculations #968
hitrate calculations #975
extra functions for classification metrics (#966)
OneOf and OneOfV2 batch transforms (#951)
precision_recall_fbeta_support metric (#971)
Pruning tutorial (#987)
BatchPrefetchLoaderWrapper (#986)
DynamicBalanceClassSampler (#954)

Changed

update Catalyst version to 20.10.1 for tutorials (#967)
added link to dl-course (#967)
IRunner -> simplified IRunner (#984)
docs were restructured (#985)
set_global_seed moved from utils.seed to utils.misc (#986)

Removed

several deprecated tutorials (#967)
several deprecated func from utils.misc (#986)

Fixed

BatchTransformCallback - add nn.Module transforms support (#951)
moved to contiguous view for accuracy computation (#982)
fixed torch warning on optimizer.py:140 (#979)

- Python
Published by Scitator about 5 years ago

[20.10.1] - 2020-10-15

Added

MRR metrics calculation (#886)
docs for MetricCallbacks (#947)
SoftMax, CosFace, ArcFace layers to contrib (#939)
ArcMargin layer to contrib (#957)
AdaCos to contrib (#958)
Manual SWA to utils (#945)

Changed

fixed path to CHANGELOG.md file and add information about unit test to PULL_REQUEST_TEMPLATE.md ([#955])(https://github.com/catalyst-team/catalyst/pull/955)
catalyst-dl tune config specification - now optuna params are grouped under study_params (#947)
IRunner._prepare_for_stage logic moved to IStageBasedRunner.prepare_for_stage (#947)
- now we create components in the following order: datasets/loaders, model, criterion, optimizer, scheduler, callbacks
MnistMLDataset and MnistQGDataset data split logic - now targets of the datasets are disjoint (#949)
architecture redesign (#953)
- experiments, runners, callbacks grouped by primitives under catalyst.experiments/catalyst.runners/catalyst.callbacks respectively
- settings and typing moved from catalyst.tools.* to catalyst.*
- utils moved from catalyst.*.utils to catalyst.utils
swa moved to catalyst.utils (#963)

Removed

Fixed

AMPOptimizerCallback - fix grad clip fn support (#948)
removed deprecated docs types (#947) (#952)
docs for a few files (#952)
extra backward compatibility fixes (#963)

- Python
Published by Scitator about 5 years ago

[20.09.1] - 2020-09-25

Added

Runner registry support for Config API (#936)
catalyst-dl tune command - Optuna with Config API integration for AutoML hyperparameters optimization (#937)
OptunaPruningCallback alias for OptunaCallback (#937)
AdamP and SGDP to catalyst.contrib.nn.criterion (#942)

Changed

Config API components preparation logic moved to utils.prepare_config_api_components (#936)

Removed

Fixed

Logging double logging :) (#936)
CMCCallback (#941)

- Python
Published by Scitator about 5 years ago

[20.09] - 2020-09-07

Added

MovieLens dataset loader (#903)
force and bert-level keywords to catalyst-data text2embedding (#917)
OptunaCallback to catalyst.contrib (#915)
DynamicQuantizationCallback and catalyst-dl quantize script for fast quantization of your model (#890)
Multi-scheduler support for multi-optimizer case (#923)
Native mixed-precision training support (#740)
OptiomizerCallback - flag use_fast_zero_grad for faster (and hacky) version of optimizer.zero_grad() (#927)
IOptiomizerCallback, ISchedulerCallback, ICheckpointCallback, ILoggerCallback as core abstractions for Callbacks (#933)
flag USE_AMP for PyTorch AMP usage (#933)

Changed

Pruning moved to catalyst.dl (#933)
default USE_APEX changed to 0 (#933)

Removed

Fixed

autoresume option for Config API (#907)
a few issues with TF projector (#917)
batch sampler speed issue (#921)
add apex key-value optimizer support (#924)
runtime warning for PyTorch 1.6 (920)
Apex synbn usage (920)
Catalyst dependency on system git (922)

- Python
Published by Scitator about 5 years ago

[20.08] - 2020-08-09

Added

CMCScoreCallback (#880)
kornia augmentations BatchTransformCallback (#862)
average_precision and mean_average_precision metrics (#883)
MultiLabelAccuracyCallback, AveragePrecisionCallback and MeanAveragePrecisionCallback callbacks (#883)
minimal examples for multiclass and multilabel classification (#883)
experimental TPU support (#893)
add Imagenette, Imagewoof, and Imagewang datasets (#902)
IMetricCallback, IBatchMetricCallback, ILoaderMetricCallback, BatchMetricCallback, LoaderMetricCallback abstractions (#897)
HardClusterSampler inbatch sampler (#888)

Changed

all registries merged to one catalyst.registry (#883)
mean_average_precision logic merged with average_precision (#897)
all imports moved to absolute (#905)
catalyst.contrib.data merged to catalyst.data (#905)
{breaking} Catalyst transform ToTensor was renamed to ImageToTensor (#905)
TracerCallback moved to catalyst.dl (#905)
ControlFlowCallback, PeriodicLoaderCallback moved to catalyst.core (#905)

Removed

average_accuracy and mean_average_accuracy metrics (#883)
MultiMetricCallback abstraction (#897)

Fixed

utils.tokenize_text typo with punctuation (#880)
ControlFlowCallback logic (#892)
docs (#897)

- Python
Published by Scitator about 5 years ago

[20.07] - 2020-07-06

Added

log parameter to WandbLogger (#836)
hparams experiment property (#839)
add docs build on push to master branch (#844)
WrapperCallback and ControlFlowCallback (#842)
BatchOverfitCallback (#869)
overfit flag for Config API (#869)
InBatchSamplers: AllTripletsSampler and HardTripletsSampler (#825)

Changed

Renaming (#837)
- SqueezeAndExcitation -> cSE
- ChannelSqueezeAndSpatialExcitation -> sSE
- ConcurrentSpatialAndChannelSqueezeAndChannelExcitation -> scSE
- _MetricCallback -> IMetricCallback
- dl.Experiment.process_loaders -> dl.Experiment._get_loaders
LRUpdater become abstract class (#837)
calculate_confusion_matrix_from_arrays changed params order (#837)
dl.Runner.predict_loader uses _prepare_inner_state and cleans experiment (#863)
toml to the dependencies (#872)

Removed

crc32c dependency (#872)

Fixed

workflows/deploy_push.yml failed to push some refs (#864)
.dependabot/config.yml contained invalid details (#781)
LanguageModelingDataset (#841)
global_* counters in Runner (#858)
EarlyStoppingCallback considers first epoch as bad (#854)
annoying numpy warning (#860)
PeriodicLoaderCallback overwrites best state (#867)
OneCycleLRWithWarmup (#851)

- Python
Published by Scitator about 5 years ago

[20.06] - 2020-06-04

Added

Mergify (#831)
PerplexityMetricCallback (#819)
PeriodicLoaderRunnerCallback (#818)

Changed

docs structure were updated during (#822)
utils.process_components moved from utils.distributed to utils.components (#822)
catalyst.core.state.State merged to catalyst.core.runner._Runner (#823) (backward compatibility included)
- catalyst.core.callback.Callback now works directly with catalyst.core.runner._Runner
- state_kwargs renamed to stage_kwargs

Removed

Fixed

added missed dashes in docker perfixes (#828)

[20.05.1] - 2020-05-23

Added

Circle loss implementation (#802)
BatchBalanceSampler for metric learning and classification (#806)
CheckpointCallback: new argument load_on_stage_start which accepts str and Dict[str, str] (#797)
LanguageModelingDataset to catalyst[nlp] (#808)
Extra counters for batches, loaders and epochs (#809)
TracerCallback (#789)

Changed

CheckpointCallback: additional logic for argument load_on_stage_end - accepts str and Dict[str, str] (#797)
counters names for batches, loaders and epochs (#809)
utils.trace_model: changed logic - runner argument was changed to predict_fn (#789)
redesigned contrib.data and contrib.datasets (#820)
catalyst.utils.meters moved to catalyst.tools (#820)
catalyst.contrib.utils.tools.tensorboard moved to catalyst.contrib.tools (#820)

Removed

Fixed

device selection fix for #798 (#815)
batch size counting fix for #799 and #755 issues (#809)

- Python
Published by Scitator over 5 years ago

catalyst - Catalyst 20.05.1

- Python
Published by Scitator over 5 years ago

catalyst - Catalyst 20.06rc1

- Python
Published by Scitator over 5 years ago

catalyst - Catalyst 20.05

- Python
Published by Scitator over 5 years ago

tl;dr

We finally organise Experiment-Runner-State-Callback as it should be. We also have great documentation update!

Core

Experiment - an abstraction that contains information about the experiment – a model, a criterion, an optimizer, a scheduler, and their hyperparameters. It also contains information about the data and transformations used. In general, the Experiment knows what you would like to run.
Runner - a class that knows how to run an experiment. It contains all the logic of how to run the experiment, stages, epoch and batches.
State - some intermediate storage between Experiment and Runner that saves the current state of the Experiments – model, criterion, optimizer, schedulers, metrics, loaders, callbacks, etc
Callback - a powerful abstraction that lets you customize your experiment run logic. To give users maximum flexibility and extensibility we allow callback execution anywhere in the training loop ``` onstagestart onepochstart onloaderstart onbatchstart # ... onbatchend onepochend onstageend

on_exception ```

How to combine them together?

First of all - just read the docs for State, Experiment, Runner and Callback abstractions. Long story short, State just saves everything during experiment and passes to every Callback in Experiment through Runner.run_event. For example, usual case, for some custom metric implementation, all you need to do is ``` from catalyst.dl import Callback, State

class MyPureMetric(Callback): def onbatchend(self, state: State): """To store batch-based metrics""" state.batchmetrics[{metricname}] = metric_value

def onloaderend(self, state: State): """To store loader-based metrics""" state.loadermetrics[{metricname}] = metric_value

def onepochend(self, state: State): """To store epoch-based metrics""" state.epochmetrics[{metricname}] = metric_value

```

There are coming many more Catalyst concepts, tutorials and docs in near future.

Callback updates

CheckRunCallback - allows you to check the pipeline correctness during long-run training
TimerCallback - enables / disables the calculation of the work speed of your training, like data time per batch, model time per batch, samples per second
MetricManagerCallback - transfers torch tensors to numpy and calculates statistics
ValidationManagerCallback - collects validation metrics and checks if it's the best epoch

Catalyst best practices

Working with Catalyst.DL it's better to import everything in straightforward way like ``` from catalyst.dl import SomethingGreat from catalyst.dl import utils

utils.dosomethingcool() ```

Breaking changes

CriterionAggregatorCallback moved to catalyst.contrib and will be deprecated in 20.04 release.
For SchedulerCallback reduce_metric was renamed to reduced_metric :)
We have update metric recording mechanism for State-Callback,

Future work

During 20.03 -> 20.04 releases, we are going to deprecate all SomeContribRunner and transfer them to SomeContribLogger as more general purpose solution.

- Python
Published by Scitator almost 6 years ago

catalyst - 20.02.2

Catalyst 20.02.2

Overall

scripts update
formatting update
project manifesto https://github.com/catalyst-team/catalyst/pull/532
Alchemy intro https://github.com/catalyst-team/catalyst/pull/563 https://github.com/catalyst-team/catalyst/pull/564
Travis -> TeamCity CI https://github.com/catalyst-team/catalyst/pull/597 https://github.com/catalyst-team/catalyst/pull/616 https://github.com/catalyst-team/catalyst/pull/634
Core init https://github.com/catalyst-team/catalyst/pull/578
tests global update https://github.com/catalyst-team/catalyst/pull/661

DL

config wizard https://github.com/catalyst-team/catalyst/pull/499
Triplet loss contribution https://github.com/catalyst-team/catalyst/pull/504
TelegramLogger support https://github.com/catalyst-team/catalyst/pull/471
Trace support for fp16 and Nvidia Apex https://github.com/catalyst-team/catalyst/pull/497
runner params fix https://github.com/catalyst-team/catalyst/pull/545 https://github.com/catalyst-team/catalyst/pull/633
weighted sum support for loss calculation https://github.com/catalyst-team/catalyst/pull/535
classwise IOU support https://github.com/catalyst-team/catalyst/pull/533
BERT text classification example https://github.com/catalyst-team/catalyst/pull/540
Ralamb contribution https://github.com/catalyst-team/catalyst/pull/551
samplers params support https://github.com/catalyst-team/catalyst/pull/550
KNNMetricCallback contribution https://github.com/catalyst-team/catalyst/pull/560
MetricAggregationCallback contribution https://github.com/catalyst-team/catalyst/pull/591
text to embeddings script https://github.com/catalyst-team/catalyst/pull/596 https://github.com/catalyst-team/catalyst/pull/601
Several metric learning features https://github.com/catalyst-team/catalyst/pull/589 https://github.com/catalyst-team/catalyst/pull/598 https://github.com/catalyst-team/catalyst/pull/599
Neptune integration https://github.com/catalyst-team/catalyst/pull/571
transforms params support https://github.com/catalyst-team/catalyst/pull/595 https://github.com/catalyst-team/catalyst/pull/604
SMP integration https://github.com/catalyst-team/catalyst/pull/600
GAN 2.0 https://github.com/catalyst-team/catalyst/pull/607 https://github.com/catalyst-team/catalyst/pull/585
Cutmix callback contribution https://github.com/catalyst-team/catalyst/pull/635
RMS Normalization contribution https://github.com/catalyst-team/catalyst/pull/649
EarlyStoppingCallback fix https://github.com/catalyst-team/catalyst/pull/664
better distributed & slurm support https://github.com/catalyst-team/catalyst/pull/639 https://github.com/catalyst-team/catalyst/pull/629 https://github.com/catalyst-team/catalyst/pull/662 https://github.com/catalyst-team/catalyst/pull/628

- Python
Published by Scitator about 6 years ago

catalyst - Catalyst 19.11

Catalyst 19.10 -> 19.11

Achievements

NeurIPS 2019: Learn to Move - Walk Around, 2nd place

Overall

pergpuscale feature for multi-gpu experiment runs https://github.com/catalyst-team/catalyst/pull/406
contribution guide update https://github.com/catalyst-team/catalyst/pull/422
image extension check https://github.com/catalyst-team/catalyst/pull/432
pytorch.tensorboard support https://github.com/catalyst-team/catalyst/pull/439
docker update https://github.com/catalyst-team/catalyst/pull/463 https://github.com/catalyst-team/catalyst/pull/476
documentation update https://github.com/catalyst-team/catalyst/pull/475
codestyle formatting update https://github.com/catalyst-team/catalyst/pull/477

DL

GAN example https://github.com/catalyst-team/catalyst/pull/407
wandb fix https://github.com/catalyst-team/catalyst/pull/410
data mixins https://github.com/catalyst-team/catalyst/pull/412
jupyter notebooks dump feature https://github.com/catalyst-team/catalyst/pull/413
segmentation tutorial https://github.com/catalyst-team/catalyst/pull/415 https://github.com/catalyst-team/catalyst/pull/441 https://github.com/catalyst-team/catalyst/pull/451
exponential format support for Config API https://github.com/catalyst-team/catalyst/pull/418
pytorch 1.3 naming issue fix https://github.com/catalyst-team/catalyst/pull/447
MaskReader https://github.com/catalyst-team/catalyst/pull/446
Epoch num: 0 to 1 https://github.com/catalyst-team/catalyst/pull/411
wandb logging fix https://github.com/catalyst-team/catalyst/pull/458
all metrics logging to checkpoint https://github.com/catalyst-team/catalyst/pull/455
imread fix https://github.com/catalyst-team/catalyst/pull/473
Global Precision/Recall/F1 Callback https://github.com/catalyst-team/catalyst/pull/433
Loggers logic update https://github.com/catalyst-team/catalyst/pull/443
runner device fix https://github.com/catalyst-team/catalyst/pull/482
checkpoint callback path correctness fix https://github.com/catalyst-team/catalyst/pull/484

RL

observation inconsistency exception feature https://github.com/catalyst-team/catalyst/pull/461
RL-2019 comments & updates https://github.com/catalyst-team/catalyst/pull/483

- Python
Published by Scitator over 6 years ago

catalyst - Catalyst 19.10

Catalyst 19.09 -> 19.10

Achievements

NeurIPS 2019: Recursion Cellular Image Classification - 4th place solution writeup - 8th place solution

Kaggle integration

Weights & Biases integration

Overall

LAMA refactoring https://github.com/catalyst-team/catalyst/pull/353
TemporalConcatPooling https://github.com/catalyst-team/catalyst/pull/355
Extensions on/off support https://github.com/catalyst-team/catalyst/pull/368
Hall of Glory update https://github.com/catalyst-team/catalyst/pull/385
binarymasktooverlayimage refactoring https://github.com/catalyst-team/catalyst/pull/387
getutcnowtime feature https://github.com/catalyst-team/catalyst/pull/389
image preprocessing refactoring https://github.com/catalyst-team/catalyst/pull/398
TF seed fix https://github.com/catalyst-team/catalyst/pull/399
shorthand for bool flag https://github.com/catalyst-team/catalyst/pull/405

DL

Table data tutorial https://github.com/catalyst-team/catalyst/pull/351
Wandb integration tutorial https://github.com/catalyst-team/catalyst/commit/365ed7d6fdb9e5aa515ef52612e403fdd3270ac8
lovasz loss fix https://github.com/catalyst-team/catalyst/pull/359
SupervisedRunner, one loader handling https://github.com/catalyst-team/catalyst/pull/362
SupervisedRunner.predict_loader, model support https://github.com/catalyst-team/catalyst/pull/367
resume from previous stage fix https://github.com/catalyst-team/catalyst/pull/328
CriterionAggregator https://github.com/catalyst-team/catalyst/pull/361
Weight decay decoupling https://github.com/catalyst-team/catalyst/pull/370
Binary class support for AccuracyCallback https://github.com/catalyst-team/catalyst/pull/374
SupervisedRunner.train, resume feature https://github.com/catalyst-team/catalyst/pull/377
Apex distributed synchronised batchnorm support https://github.com/catalyst-team/catalyst/pull/379
Catalyst Init feature https://github.com/catalyst-team/catalyst/pull/372
Dict transform support for MergeDataset https://github.com/catalyst-team/catalyst/pull/388
BCEDiceLoss weights support https://github.com/catalyst-team/catalyst/pull/394
Multi-label accuracy support https://github.com/catalyst-team/catalyst/pull/381
PyTorch loaders additional params support https://github.com/catalyst-team/catalyst/pull/397

RL

RL networks refactoring – MLP and CNN policies support https://github.com/catalyst-team/catalyst/pull/352
Mongo reconnection support https://github.com/catalyst-team/catalyst/pull/354
RL tests refactoring https://github.com/catalyst-team/catalyst/pull/357 https://github.com/catalyst-team/catalyst/pull/369
EnvWrapper feature https://github.com/catalyst-team/catalyst/pull/358
Raw reward fix https://github.com/catalyst-team/catalyst/pull/373
deterministic RL https://github.com/catalyst-team/catalyst/pull/393
Large files support for MongoDB https://github.com/catalyst-team/catalyst/pull/396

- Python
Published by Scitator over 6 years ago

catalyst - Catalyst 19.09

Catalyst 19.08 -> 19.09

Ecosystem

We are happy to announce MLComp release – a distributed DAG (Directed acyclic graph) framework for machine learning with UI. Powered by Catalyst.Team.

We also release a detailed classification tutorial and comprehensive classification pipeline.

Slowly-slowly, more and more challenges are powered by catalyst https://github.com/catalyst-team/catalyst/pull/302.

We also update the licence to Apache 2.0, start the Patreon and even run catalyst-info repo!

And finally, we have integrate wandb to the catalyst, both DL & RL!

Overall

config dump to tensorboard https://github.com/catalyst-team/catalyst/pull/284 – even more reproducibility for both DL and RL
bash scripts for parallel-gpu-run and catalyst-rl-run https://github.com/catalyst-team/catalyst/pull/288
improver CUDNN deterministic and CUDNN benchmark support https://github.com/catalyst-team/catalyst/pull/299 https://github.com/catalyst-team/catalyst/pull/309
available gpus check feature https://github.com/catalyst-team/catalyst/pull/300
SequentialNet update with "soft" residual mode https://github.com/catalyst-team/catalyst/pull/301
docs update https://github.com/catalyst-team/catalyst/pull/303 https://github.com/catalyst-team/catalyst/pull/336
layer-wise learning rate support https://github.com/catalyst-team/catalyst/pull/283
torchnet dependency removal https://github.com/catalyst-team/catalyst/pull/304
environment variables and packages versions dump to tensorboard https://github.com/catalyst-team/catalyst/pull/313 https://github.com/catalyst-team/catalyst/pull/317
tracing script update https://github.com/catalyst-team/catalyst/pull/319
additional general case CV scripts https://github.com/catalyst-team/catalyst/pull/321
RAdam, LookAhead, Ranger optimizers support https://github.com/catalyst-team/catalyst/pull/332
wandb integration https://github.com/catalyst-team/catalyst/pull/337 https://github.com/catalyst-team/catalyst/pull/339 https://github.com/catalyst-team/catalyst/pull/341

DL

Exception handling support for callbacks https://github.com/catalyst-team/catalyst/pull/281 https://github.com/catalyst-team/catalyst/pull/307
tests update https://github.com/catalyst-team/catalyst/pull/286
traced models support for dataset prediction https://github.com/catalyst-team/catalyst/pull/287
tensorboard logger fix https://github.com/catalyst-team/catalyst/pull/294
state_dict param support for all contrib encoders https://github.com/catalyst-team/catalyst/pull/292
bias weight decay autoremove https://github.com/catalyst-team/catalyst/pull/293
checkpoint save on exception https://github.com/catalyst-team/catalyst/pull/295
classification tutorial https://github.com/catalyst-team/catalyst/pull/296 https://github.com/catalyst-team/catalyst/pull/297 https://github.com/catalyst-team/catalyst/pull/326
better console logging https://github.com/catalyst-team/catalyst/pull/298
segmentation models support for dl registry https://github.com/catalyst-team/catalyst/pull/329
one-hot feature https://github.com/catalyst-team/catalyst/pull/331
accuracy metric fix https://github.com/catalyst-team/catalyst/pull/340
path dataset support https://github.com/catalyst-team/catalyst/pull/335
callback ordering support https://github.com/catalyst-team/catalyst/pull/343
encoders requires_grad logic update https://github.com/catalyst-team/catalyst/pull/346

RL

DB dump/load refactoring https://github.com/catalyst-team/catalyst/pull/318
mongo fix https://github.com/catalyst-team/catalyst/pull/345

- Python
Published by Scitator over 6 years ago

catalyst - Catalyst 19.08

Catalyst 19.07 -> 19.08

Overall

module import fix https://github.com/catalyst-team/catalyst/pull/240
TF projector fix https://github.com/catalyst-team/catalyst/pull/272
docs update https://github.com/catalyst-team/catalyst/pull/279

DL

updated InferMaskCallback https://github.com/catalyst-team/catalyst/pull/252
scientific notation https://github.com/catalyst-team/catalyst/pull/248
tracing tests https://github.com/catalyst-team/catalyst/pull/255
BaseExperiment update https://github.com/catalyst-team/catalyst/pull/269
BatchSamler support https://github.com/catalyst-team/catalyst/pull/271
metrics.json feature https://github.com/catalyst-team/catalyst/pull/266
auto accuracy args https://github.com/catalyst-team/catalyst/pull/274
lr linear scaling https://github.com/catalyst-team/catalyst/pull/273
BaseCheckpointCallback https://github.com/catalyst-team/catalyst/pull/276
SupervisedRunner update, new examples https://github.com/catalyst-team/catalyst/pull/278

RL

critic refactoring https://github.com/catalyst-team/catalyst/pull/253
host support for dbWrappers https://github.com/catalyst-team/catalyst/pull/254
RawObservationWrapper https://github.com/catalyst-team/catalyst/pull/247 and https://github.com/catalyst-team/catalyst/pull/261
distributional PPO PoC https://github.com/catalyst-team/catalyst/pull/257
PPO fix https://github.com/catalyst-team/catalyst/pull/258
RL tests: https://github.com/catalyst-team/catalyst/pull/259, https://github.com/catalyst-team/catalyst/pull/260, https://github.com/catalyst-team/catalyst/pull/262
RL epoch limit feature https://github.com/catalyst-team/catalyst/pull/263
additional policy heads support https://github.com/catalyst-team/catalyst/pull/264
Advantage & entropy regularization DQN support https://github.com/catalyst-team/catalyst/pull/265
mongo wrapper update https://github.com/catalyst-team/catalyst/pull/267, https://github.com/catalyst-team/catalyst/pull/268
atari example update https://github.com/catalyst-team/catalyst/pull/270
code saving https://github.com/catalyst-team/catalyst/pull/277

- Python
Published by Scitator over 6 years ago

catalyst - Catalyst 19.07

Catalyst 19.06.3 -> 19.07

Overall

module import fix https://github.com/catalyst-team/catalyst/pull/240
config fix https://github.com/catalyst-team/catalyst/pull/241
hash update https://github.com/catalyst-team/catalyst/pull/243
codestyle update https://github.com/catalyst-team/catalyst/pull/244
python dependencies fix https://github.com/catalyst-team/catalyst/pull/245

DL

updated MiniEpochSampler https://github.com/catalyst-team/catalyst/pull/229
updated events sequence https://github.com/catalyst-team/catalyst/pull/230
MixupCallback https://github.com/catalyst-team/catalyst/pull/238
image read with turbojpeg support https://github.com/catalyst-team/catalyst/pull/239

RL

multi-input support https://github.com/catalyst-team/catalyst/pull/231
max updates per sample feature https://github.com/catalyst-team/catalyst/pull/246
rl validation https://github.com/catalyst-team/catalyst/pull/250

- Python
Published by Scitator over 6 years ago

catalyst - Catalyst 19.06.3

Catalyst 19.06 -> 19.06.3

Overall

docker fix https://github.com/catalyst-team/catalyst/pull/216
global lib refactoring https://github.com/catalyst-team/catalyst/pull/223

DL

DataParallel for fp16 apex https://github.com/catalyst-team/catalyst/pull/213
cpu tracing support https://github.com/catalyst-team/catalyst/pull/217
config dump fix https://github.com/catalyst-team/catalyst/pull/221
batch2device fix https://github.com/catalyst-team/catalyst/pull/214
IterationCheckpointCallback & batch-size fix https://github.com/catalyst-team/catalyst/pull/228
fp16 flag fix https://github.com/catalyst-team/catalyst/pull/227

RL

Max length removal https://github.com/catalyst-team/catalyst/pull/211
RL refactoring https://github.com/catalyst-team/catalyst/pull/212
training seeds update https://github.com/catalyst-team/catalyst/pull/220
Multi-headed Value functions support https://github.com/catalyst-team/catalyst/pull/198

Breaking changes

UtilsFactory replaced with from catalyst.dl import utils
LossCallback replaced with CriterionCallback

- Python
Published by Scitator over 6 years ago

catalyst - Catalyst 19.06

Catalyst 19.05 -> 19.06

Overall

docs, docker and travis update (https://github.com/catalyst-team/catalyst/pull/205, https://github.com/catalyst-team/catalyst/pull/201, https://github.com/catalyst-team/catalyst/pull/203)
Removed dependency on TensorFlow, new tensorboard logs parsing mechanism (https://github.com/catalyst-team/catalyst/pull/182)

DL

FP16 & distributed training support, nvidia-apex support (https://github.com/catalyst-team/catalyst/pull/183, https://github.com/catalyst-team/catalyst/pull/207)
PyTorch auto-tracing support (https://github.com/catalyst-team/catalyst/pull/189)
logdir autonaming based on baselogdir, timestamp and config hash (https://github.com/catalyst-team/catalyst/pull/204/commits/a141e4c95dde81aa15d0eb0c6daaaf8648df8e20)
1Cycle PyTorch scheduler (https://github.com/catalyst-team/catalyst/pull/162)

RL

on-policy model-free algorithms support, PPO & REINFORCE implementations (https://github.com/catalyst-team/catalyst/pull/174)
mongo DB support fix (https://github.com/catalyst-team/catalyst/pull/190)
updated samplers, no trajectory length limit now (https://github.com/catalyst-team/catalyst/pull/196)

Contrib

segmentation contrib (https://github.com/catalyst-team/catalyst/pull/204)
losses and metrics refactoring (https://github.com/catalyst-team/catalyst/pull/191)

Improvements and fixes

optimizer transferring from previous stage support (https://github.com/catalyst-team/catalyst/pull/181)
additional checkpoint data support (https://github.com/catalyst-team/catalyst/pull/184)
--version feature (https://github.com/catalyst-team/catalyst/pull/188)

Breaking changes

all methods with prepare_*, that have returned something, renamed to get_*;
Experiment._prepare_logdir renamed to Experiment._get_logdir
UtilsFactory.prepare_models renamed to UtilsFactory.process_components and supports PyTorch model, criterion, optimizer and scheduler now
Previous segmentation models were moved to catalyst.contrib.models.segmentation.models: ResNetUnet and ResNetLinknet
per_gpu_batch_size renamed to per_gpu_scaling and affects on batchsize and numworkers now

Features examples

Segmentation

from catalyst.contrib.models.segmentation import \ Unet, Linknet, FPNUnet, PSPnet, \ ResnetUnet, ResnetLinknet, ResnetFPNUnet, ResnetPSPnet

Apex

runner = SupervisedRunner() runner.train( model=model, criterion=criterion, optimizer=optimizer, scheduler=scheduler, fp16=True ...) or runner = SupervisedRunner() runner.train( model=model, criterion=criterion, optimizer=optimizer, scheduler=scheduler, fp16={"opt_level": "O1"} # and other apex.initalize kwargs ...)

Distributed training bash example

```

!/usr/bin/env bash

export MASTERADDR="127.0.0.1" export MASTERPORT=29500 export WORLD_SIZE=2 # number of gpus

RANK=0 LOCALRANK=0 catalyst-dl run --config=config.yml --distributedparams/rank=0:int & # gpu 0 sleep 5 RANK=1 LOCALRANK=1 catalyst-dl run --config=config.yml --distributedparams/rank=1:int & # gpu 1 ```

- Python
Published by Scitator over 6 years ago

Recent Releases of catalyst

catalyst - Catalyst 22.04

[22.04] - 2022-04-29

Added

Fixed

catalyst - Catalyst 22.02.1

[22.02.1] - 2022-02-27

Added

Fixed

catalyst - Catalyst 22.02

[22.02] - 2022-02-13

Tl;dr

Added

Changed

Removed

catalyst - Catalyst 22.02rc0

[22.02rc0] - 2022-02-07

Tl;dr

catalyst - Catalyst 21.12

[21.12] - 2021-12-28

Tl;dr

Added

Changed

Removed

Fixed

Contributors ❤️

catalyst - Catalyst 21.11

[21.11] - 2021-11-30

Tl;dr

Added

Changed

Removed

Fixed

Contributors ❤️

catalyst - Catalyst 21.10

[21.10] - 2021-10-30

Tl;dr

Added

Changed

Removed

Fixed

catalyst - Catalyst 21.09

[21.09] - 2021-09-30

Added

Changed

Removed

Fixed

Contributors ❤️

catalyst - Catalyst 21.09rc1 - release wheels update check 2.0

catalyst - Catalyst 21.09rc0 - release wheels update check

catalyst - Catalyst 21.08

[21.08] - 2021-08-31

Added

Changed

Removed

Fixed

Contributors ❤️

catalyst - Catalyst 21.07

[21.07] - 2021-07-29

Added

Changed

Removed

Fixed

Contributors ❤️

catalyst - Catalyst 21.06

[21.06] - 2021-06-29

Added

Changed

Fixed

Contributors ❤️

catalyst - Catalyst 21.05

[21.05] - 2021-05-31

Added

Changed

Removed

Fixed

catalyst - Catalyst 21.04.2

[21.04.2] - 2021-04-30

Added

catalyst - Catalyst 21.04.1