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v0.4.0
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@mannatsingh mannatsingh released this 29 Apr 23:00
v0.4.0
e5b9873

New Features

  • Release EfficientNet model implementation (#475)
  • Add support to convert any PyTorch model to a ClassyModel with the ability to attach heads to it (#461)
    • Added a corresponding tutorial on ClassyModel and ClassyHeads (#485)
  • Squeeze and Excitation support for ResNe(X)t and DenseNet models (#426, #427)
  • Made ClassyHooks registrable (#401) and configurable (#402)
  • Migrated to TorchElastic v0.2.0 (#464)
  • Add SyncBatchNorm support (#423)
  • Implement mixup train augmentation (#469)
  • Support LARC for SGD optimizer (#408)
  • Added convenience wrappers for Iterable datasets (#455)
  • Tensorboard improvements
    • Plot histograms of model weights to Tensorboard (#432)
    • Reduce data logged to tensorboard (#436)
  • Invalid (NaN / Inf) loss detection
  • Revamped logging (#478)
  • Add bn_weight_decay configuration option for ResNe(X)t models
  • Support specifying update_interval to Parameter Schedulers (#418)

Breaking changes

  • ClassificationTask API improvement and train_step, eval_step simplification
    • Removed local_variables from ClassificationTask (#411, #412, #413, #414, #416, #421)
    • Move use_gpu from ClassyTrainer to ClassificationTask (#468)
    • Move num_dataloader_workers out of ClassyTrainer (#477)
  • Rename lr to value in parameter schedulers (#417)
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