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Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[unReleased] - 2021-MM-DD

[unReleased] - Added

  • Added YOLO model (#552)

[unReleased] - Changed

[unReleased] - Deprecated

[unReleased] - Removed

[unReleased] - Fixed

  • Fix doctest fails with ImportError: cannot import name ‘Env’ from ‘gym’ (#751)

[0.4.0] - 2021-09-09

[0.4.0] - Added

  • Added Soft Actor Critic (SAC) Model (#627)

  • Added EMNISTDataModule, BinaryEMNISTDataModule, and BinaryEMNIST dataset (#676)

  • Added Advantage Actor-Critic (A2C) Model (#598)

  • Added Torch ORT Callback (#720)

  • Added SparseML Callback (#724)

[0.4.0] - Changed

  • Changed the default values pin_memory=False, shuffle=False and num_workers=16 to pin_memory=True, shuffle=True and num_workers=0 of datamodules (#701)

  • Supporting deprecated attribute usage (#699)

[0.4.0] - Fixed

  • Fixed ImageNet val loader to use val transform instead of train transform (#713)

  • Fixed the MNIST download giving HTTP 404 with torchvision>=0.9.1 (#674)

  • Removed momentum updating from val step and add separate val queue (#631)

  • Fixed moving the queue to GPU when resuming checkpoint for SwAV model (#684)

  • Fixed FP16 support with vision GPT model (#694)

  • Removing bias from linear model regularisation (#669)

  • Fixed CPC module issue (#680)

[0.3.4] - 2021-06-17

[0.3.4] - Changed

  • Replaced load_boston with load_diabetes in the docs and tests (#629)

  • Added base encoder and MLP dimension arguments to BYOL constructor (#637)

[0.3.4] - Fixed

  • Fixed the MNIST download giving HTTP 503 (#633)

  • Fixed type annotation of ExperienceSource.__iter__ (#645)

  • Fixed pretrained_urls on Windows (#652)

  • Fixed logistic regression (#655, #664)

  • Fixed double softmax in SSLEvaluator (#663)

[0.3.3] - 2021-04-17

[0.3.3] - Changed

  • Suppressed missing package warnings, conditioned by WARN_MISSING_PACKAGE="1" (#617)

  • Updated all scripts to LARS (#613)

[0.3.3] - Fixed

  • Add missing dataclass requirements (#618)

[0.3.2] - 2021-03-20

[0.3.2] - Changed

  • Renamed SSL modules: CPCV2 >> CPC_v2 and MocoV2 >> Moco_v2 (#585)

  • Refactored setup.py to be typing friendly (#601)

[0.3.1] - 2021-03-09

[0.3.1] - Added

  • Added Pix2Pix model (#533)

[0.3.1] - Changed

  • Moved vision models (GPT2, ImageGPT, SemSegment, UNet) to pl_bolts.models.vision (#561)

[0.3.1] - Fixed

  • Fixed BYOL moving average update (#574)

  • Fixed custom gamma in rl (#550)

  • Fixed PyTorch 1.8 compatibility issue (#580, #579)

  • Fixed handling batchnorms in BatchGradientVerification (#569)

  • Corrected num_rows calculation in LatentDimInterpolator callback (#573)

[0.3.0] - 2021-01-20

[0.3.0] - Added

  • Added input_channels argument to UNet (#297)

  • Added SwAV (#239, #348, #323)

  • Added data monitor callbacks ModuleDataMonitor and TrainingDataMonitor (#285)

  • Added DCGAN module (#403)

  • Added VisionDataModule as parent class for BinaryMNISTDataModule, CIFAR10DataModule, FashionMNISTDataModule, and MNISTDataModule (#400)

  • Added GIoU loss (#347)

  • Added IoU loss (#469)

  • Added semantic segmentation model SemSegment with UNet backend (#259)

  • Added pption to normalize latent interpolation images (#438)

  • Added flags to datamodules (#388)

  • Added metric GIoU (#347)

  • Added Intersection over Union Metric/Loss (#469)

  • Added SimSiam model (#407)

  • Added gradient verification callback (#465)

  • Added Backbones to FRCNN (#475)

[0.3.0] - Changed

  • Decoupled datamodules from models (#332, #270)

  • Set PyTorch Lightning 1.0 as the minimum requirement (#274)

  • Moved pl_bolts.callbacks.self_supervised.BYOLMAWeightUpdate to pl_bolts.callbacks.byol_updates.BYOLMAWeightUpdate (#288)

  • Moved pl_bolts.callbacks.self_supervised.SSLOnlineEvaluator to pl_bolts.callbacks.ssl_online.SSLOnlineEvaluator (#288)

  • Moved pl_bolts.datamodules.*_dataset to pl_bolts.datasets.*_dataset (#275)

  • Ensured sync across val/test step when using DDP (#371)

  • Refactored CLI arguments of models (#394)

  • Upgraded DQN to use .log (#404)

  • Decoupled DataModules from models - CPCV2 (#386)

  • Refactored datamodules/datasets (#338)

  • Refactored Vision DataModules (#400)

  • Refactored pl_bolts.callbacks (#477)

  • Refactored the rest of pl_bolts.models.self_supervised (#481, #479

  • Update [torchvision.utils.make_grid(https://pytorch.org/docs/stable/torchvision/utils.html#torchvision.utils.make_grid)] kwargs to TensorboardGenerativeModelImageSampler (#494)

[0.3.0] - Fixed

  • Fixed duplicate warnings when optional packages are unavailable (#341)

  • Fixed ModuleNotFoundError when importing datamoules (#303)

  • Fixed cyclic imports in pl_bolts.utils.self_suprvised (#350)

  • Fixed VAE loss to use KL term of ELBO (#330)

  • Fixed dataloders of MNISTDataModule to use self.batch_size (#331)

  • Fixed missing outputs in SSL hooks for PyTorch Lightning 1.0 (#277)

  • Fixed stl10 datamodule (#369)

  • Fixes SimCLR transforms (#329)

  • Fixed binary MNIST datamodule (#377)

  • Fixed the end of batch size mismatch (#389)

  • Fixed batch_size parameter for DataModules remaining (#344)

  • Fixed CIFAR num_samples (#432)

  • Fixed DQN run_n_episodes using the wrong environment variable (#525)

[0.2.5] - 2020-10-12

  • Enabled PyTorch Lightning 1.0 compatibility

[0.2.4] - 2020-10-12

  • Enabled manual returns (#267)

[0.2.3] - 2020-10-12

[0.2.3] - Added

  • Enabled PyTorch Lightning 0.10 compatibility (#264)

  • Added dummy datasets (#266)

  • Added KittiDataModule (#248)

  • Added UNet (#247)

  • Added reinforcement learning models, losses and datamodules (#257)

[0.2.2] - 2020-09-14

  • Fixed confused logit (#222)

[0.2.1] - 2020-09-13

[0.2.1] - Added

  • Added pretrained VAE with resnet encoders and decoders

  • Added pretrained AE with resnet encoders and decoders

  • Added CPC pretrained on CIFAR10 and STL10

  • Verified BYOL implementation

[0.2.1] - Changed

  • Dropped all dependencies except PyTorch Lightning and PyTorch

  • Decoupled datamodules from GAN (#206)

  • Modularize AE & VAE (#196)

[0.2.1] - Fixed

  • Fixed gym (#221)

  • Fix L1/L2 regularization (#216)

  • Fix max_depth recursion crash in AsynchronousLoader (#191)

[0.2.0] - 2020-09-10

[0.2.0] - Added

  • Enabled Apache License, Version 2.0

[0.2.0] - Changed

  • Moved unnecessary dependencies to __main__ section in BYOL (#176)

[0.2.0] - Fixed

  • Fixed CPC STL10 finetune (#173)

[0.1.1] - 2020-08-23

[0.1.1] - Added

  • Added Faster RCNN + Pscal VOC DataModule (#157)

  • Added a better lars scheduling LARSWrapper (#162)

  • Added CPC finetuner (#158)

  • Added BinaryMNISTDataModule (#153)

  • Added learning rate scheduler to BYOL (#148)

  • Added Cityscapes DataModule (#136)

  • Added learning rate scheduler LinearWarmupCosineAnnealingLR (#138)

  • Added BYOL (#144)

  • Added ConfusedLogitCallback (#118)

  • Added an asynchronous single GPU dataloader. (#1521)

[0.1.1] - Fixed

  • Fixed simclr finetuner (#165)

  • Fixed STL10 finetuner (#164)

  • Fixed Image GPT (#108)

  • Fixed unused MNIST transforms in tran/val/test (#109)

[0.1.1] - Changed

  • Enhanced train batch function (#107)

[0.1.0] - 2020-07-02

[0.1.0] - Added

  • Added setup and repo structure

  • Added requirements

  • Added docs

  • Added Manifest

  • Added coverage

  • Added MNIST template

  • Added VAE template

  • Added GAN + AE + MNIST

  • Added Linear Regression

  • Added Moco2g

  • Added simclr

  • Added RL module

  • Added Loggers

  • Added Transforms

  • Added Tiny Datasets

  • Added regularization to linear + logistic models

  • Added Linear and Logistic Regression tests

  • Added Image GPT

  • Added Recommenders module

[0.1.0] - Changed

  • Device is no longer set in the DQN model init

  • Moved RL loss function to the losses module

  • Moved rl.common.experience to datamodules

  • train_batch function to VPG model to generate batch of data at each step (POC)

  • Experience source no longer gets initialized with a device, instead the device is passed at each step()

  • Refactored ExperienceSource classes to be handle multiple environments.

[0.1.0] - Removed

  • Removed N-Step DQN as the latest version of the DQN supports N-Step by setting the n_step arg to n

  • Deprecated common.experience

[0.1.0] - Fixed

  • Documentation

  • Doct tests

  • CI pipeline

  • Imports and pkg

  • CPC fixes

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