super-gradients

What's Changed

• Added warning for drop_last when train_loader is not divisible by batch_size by @shaydeci in https://github.com/Deci-AI/super-gradients/pull/586
• fix compute_detection_metrics_per_cls return value when no detection … by @ofrimasad in https://github.com/Deci-AI/super-gradients/pull/583
• Quantization infra mods for different calibrators and learnable amax by @spsancti in https://github.com/Deci-AI/super-gradients/pull/537
• PLFM-3331 Register experiments with model name by @roikoren755 in https://github.com/Deci-AI/super-gradients/pull/585
• fix ignore index for DiceCEEdgeLoss by @lkdci in https://github.com/Deci-AI/super-gradients/pull/588

Full Changelog: https://github.com/Deci-AI/super-gradients/compare/3.0.4...3.0.5

What's Changed

• Reorganisation README by @Shani-Perl in https://github.com/Deci-AI/super-gradients/pull/526
• Apply black formatting on pretrained model zoo by @BloodAxe in https://github.com/Deci-AI/super-gradients/pull/524
• Remove imports from factory.init by @Louis-Dupont in https://github.com/Deci-AI/super-gradients/pull/516
• Feature/sg 416 albumentations plugin for classification by @shaydeci in https://github.com/Deci-AI/super-gradients/pull/495
• Feature/sg 404 ssd reproduce by @BloodAxe in https://github.com/Deci-AI/super-gradients/pull/525
• Added indexing support for meshgrid by @BloodAxe in https://github.com/Deci-AI/super-gradients/pull/528
• Feature/al 441 ptq detection by @spsancti in https://github.com/Deci-AI/super-gradients/pull/527
• Add DDP doc by @Louis-Dupont in https://github.com/Deci-AI/super-gradients/pull/523
• SG-448- dataset_params and arch_params logging by @shaydeci in https://github.com/Deci-AI/super-gradients/pull/532
• Fix clearml comment by @Louis-Dupont in https://github.com/Deci-AI/super-gradients/pull/530
• Bug/sg 000 torch version fix by @shaydeci in https://github.com/Deci-AI/super-gradients/pull/535
• fix pplite-seg prep conversion by @lkdci in https://github.com/Deci-AI/super-gradients/pull/538
• SGLogger fix - add warning and multiprocess_safe system_monitoring by @Louis-Dupont in https://github.com/Deci-AI/super-gradients/pull/534
• Add self to recipes by @Louis-Dupont in https://github.com/Deci-AI/super-gradients/pull/539
• replace head for UNet module by @lkdci in https://github.com/Deci-AI/super-gradients/pull/543
• Rename gpu_mode to multi_gpu and setup_gpu_mode to setup_device by @Louis-Dupont in https://github.com/Deci-AI/super-gradients/pull/517
• Add version_base to hydra to remove warning by @Louis-Dupont in https://github.com/Deci-AI/super-gradients/pull/541
• Hotfix/sg 000 add data structure and link to cityscape desc by @Louis-Dupont in https://github.com/Deci-AI/super-gradients/pull/550
• add stringcase by @ofrimasad in https://github.com/Deci-AI/super-gradients/pull/553
• Hotfix/sg 000 add data structure to cityscape desc v2 by @Louis-Dupont in https://github.com/Deci-AI/super-gradients/pull/551
• Improve PascalVOC detection error msg by @Louis-Dupont in https://github.com/Deci-AI/super-gradients/pull/556
• Improve evaluate_from_recipe usability by @Louis-Dupont in https://github.com/Deci-AI/super-gradients/pull/558
• Feature/sg 458 support for any user dataloader using dataset registry by @shaydeci in https://github.com/Deci-AI/super-gradients/pull/547
• Features/sg 409 check all params used by @BloodAxe in https://github.com/Deci-AI/super-gradients/pull/546
• Split and rename the modules from super_gradients.common.environment by @Louis-Dupont in https://github.com/Deci-AI/super-gradients/pull/548
• Feature/sg 468 detection transform support for any number of channels by @shaydeci in https://github.com/Deci-AI/super-gradients/pull/559
• Feature/sg 518 update evaluate from recipe to add output by @Louis-Dupont in https://github.com/Deci-AI/super-gradients/pull/560
• error raised for torch version and formatting by @shaydeci in https://github.com/Deci-AI/super-gradients/pull/540
• Feature/sg 356 ddp silent mode and multi process safe docs by @shaydeci in https://github.com/Deci-AI/super-gradients/pull/563
• Apply black on some files by @Louis-Dupont in https://github.com/Deci-AI/super-gradients/pull/565
• Fix runtime warning of accessing non-contiguous tensor in mAP metric by @BloodAxe in https://github.com/Deci-AI/super-gradients/pull/566
• fix F1 Precision Recall to represent all the defined rage and not onl… by @ofrimasad in https://github.com/Deci-AI/super-gradients/pull/564
• Fix Multigpu.OFF factory by @Louis-Dupont in https://github.com/Deci-AI/super-gradients/pull/569
• Import AutoLoggerConfig and ConsoleSink separatly by @Louis-Dupont in https://github.com/Deci-AI/super-gradients/pull/567
• remove user guide from docs by @ofrimasad in https://github.com/Deci-AI/super-gradients/pull/570
• new generated docs by @ofrimasad in https://github.com/Deci-AI/super-gradients/pull/572
• update documentation by @ofrimasad in https://github.com/Deci-AI/super-gradients/pull/573
• Make ConvBNReLU a subclass of ConvBNAct to keep backward compatibililty by @BloodAxe in https://github.com/Deci-AI/super-gradients/pull/554
• Update README.md by @ofrimasad in https://github.com/Deci-AI/super-gradients/pull/575
• Apply black on losses by @Louis-Dupont in https://github.com/Deci-AI/super-gradients/pull/576
• Feature/sg 516 support head replacement for local pretrained weights unknown dataset by @shaydeci in https://github.com/Deci-AI/super-gradients/pull/578
• Fix bug of not respecting dilation argument in RepVGGBlock by @BloodAxe in https://github.com/Deci-AI/super-gradients/pull/555
• Feature/sg 431 check classes by @BloodAxe in https://github.com/Deci-AI/super-gradients/pull/531
• register unet cls module by @lkdci in https://github.com/Deci-AI/super-gradients/pull/580
• feature: Accept an arbitrary WandB ID by @yurkovak in https://github.com/Deci-AI/super-gradients/pull/582
• Bug/sg 512 shuffle bugfix in recipe datalaoders by @shaydeci in https://github.com/Deci-AI/super-gradients/pull/581
• Added import of quantized modules so they get registered by @spsancti in https://github.com/Deci-AI/super-gradients/pull/542
• Use unpack_batch_items on first batch (Respect additional batch items) by @BloodAxe in https://github.com/Deci-AI/super-gradients/pull/584

Full Changelog: https://github.com/Deci-AI/super-gradients/compare/3.0.3...3.0.4

• ClearML integration.
• Console logging + upload (Lab visibility).
• Epoch summary (visual improvement).
• Registry for Phase Callbacks and Transforms.
• Infrastructure for crash tips.
• Detection output adapter.
• Train from recipe example- external dataset.
• QAT infrastructure + examples.
• System Logger (i.e device attributes etc).

• dataloaders.get() supports Dataset objects.
• Behind the scenes sampler handling (warning + initialization).
• Black formatter.
• New DetectionBase.
• Logs moved from ~/sg_log/{module_name}
• CSP Resnet Backbone, new place for modules in repo.
• Plenty new factories.
• Message on effective batch size
• External checkpoints resume- fix
• Passing external classes list for CocoDetection
• Fix for loading weights from the platform

What's new?

• Eval recipe- perform validation by recipe name.
• Supported strings class for convenient autocomplete in IDE's.
• Registry: metrics, dataloaders, models, losses (so they can be passed as strings when using train_from_config).
• Return model, results from train
• Load backbone fix https://github.com/Deci-AI/super-gradients/pull/408/files
• PPLiteSeg training recipes.
• AWS env check removal
• New resolvers support: "+" "if" for yaml recipes (i.e Hydra resolvers).
• Support for custom STDC.
• ShelfNet "classes_num" -> "num_classes" bug fix.
• Improve cross-platform compatibility when parsing a readme description.
• Added the ability to download and import external code for models from ADK.

• DatasetInterface class removal- refactored as torch.DataLoader objects configured by src/training/recipes, using super_gradients.dataloaders.get() (see new updated tutorials and snippets).

• Trainer.build_model() removal- models initialisation refactored with super_gradients.models.get() (see updated tutorials and notebooks).

• Coded DDP launch (no need for python -m torch.distributed.launch ...), see new snippets here .

• Updated notebooks, tutorials and code snippets in readme.md.

• Extract recipes training hyper_params config with super_gradients.training_hyperparams.get() (see updated tutorials and notebooks).

• Simplfied resume- now passed through train_params in SgTrainer.train() (see updated snippets in readme.md).

• Removal of "loss_loggging_items_names" from train_params in Trainer.train().

• Trainer.init old, unnecessary args removed.

• Add support for getting models from Deci's platform using super_gradients.models.get(), more info regarding Deci's platform in readme.md.

This GitHub Release was done automatically by CircleCI

This GitHub Release was done automatically by CircleCI

This GitHub Release was done automatically by CircleCI

• YoloX architectures.
• SSDLite Mobilenet V2 COCO recipe
• QAT support with Nvidia's pytorch-quantization (optional dependency).
• COCO mAP calculation support in DDP (torch metric object, supports "crowd" labels).
• Pre_prediction_callback- support for input and targets manipulation right before forward pass + multiscaling pre_prediction_callbacks that work out of the box in DDP (classification and Object detection).
• Training stage switch callback to support multi-stage training.

This GitHub Release was done automatically by CircleCI

Features:

• KD trainer and resnet50 recipe (81.92 % accuracy)
• Repeated augmentation sampler
• Cooldown epochs
• Beit architecture
• Lamb Optimizer
• Passing torch data loaders directly to SgModel.

Refactoring:

• Checkpoint and architecture params decoupled.

• STDC architectures binary segmentation support bug fix.

torchmetrics version requirement set to 0.7.3 to avoid metric names depreciation bug.

This GitHub Release was done automatically by CircleCI

This GitHub Release was done automatically by CircleCI

What's new ?

• BCE with Dice loss.
• Binary IOU metric object (I.e IOU only for target class).
• Binary segmentation visualisation callback.
• Supervisely dataset interface.
• Different lr assignment for head and backbone for RegSeg.
• Google Colab notebook for semantic segmentation quick start - Check it out in our GitHub repo README.md
• Google Colab notebook for semantic segmentation transfer learning - Check it out in our GitHub repo README.md

• Added RegSeg model, recipe, and pre-trained checkpoints.
• Updated EfficientNet recipe.
• Updated Resnet50 recipe + pre-trained checkpoint (Top-1=79.47)

• Detection visualisation callback, wrong color ordering for images in tensor board fix.