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CHANGELOG.md

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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.

[0.3.0] - 2021-01-15

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)

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)

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)

[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

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

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

Changed

  • Dropped all dependencies except PyTorch Lightning and PyTorch
  • Decoupled datamodules from GAN (#206)
  • Modularize AE & VAE (#196)

Fixed

  • Fixed gym (#221)
  • Fix L1/L2 regularization (#216)
  • Fix max_depth recursion crash in AsynchronousLoader (#191)

[0.2.0] - 2020-09-10

Added

  • Enabled Apache License, Version 2.0

Changed

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

Fixed

  • Fixed CPC STL10 finetune (#173)

[0.1.1] - 2020-08-23

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)

Fixed

  • Fixed simclr finetuner (#165)
  • Fixed STL10 finetuner (#164)
  • Fixed Image GPT (#108)
  • Fixed unused MNIST transforms in tran/val/test (#109)

Changed

  • Enhanced train batch function (#107)

[0.1.0] - 2020-07-02

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

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.

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

Fixed

  • Documentation
  • Doct tests
  • CI pipeline
  • Imports and pkg
  • CPC fixes