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Changes

Most recent releases are shown at the top. Each release shows:

  • New: New classes, methods, functions, etc
  • Changed: Additional paramaters, changes to inputs or outputs, etc
  • Fixed: Bug fixes that don't change documented behaviour

Note that the top-most release is changes in the unreleased master branch on Github. Parentheses after an item show the name or github id of the contributor of that change.

1.0.15.dev0 (Work In Progress)

New:

Changed:

Fixed:

1.0.14 (2018-10-25)

New:

  • download_images: multi-process download of a file or URLs
  • verify_images: multi-process verification of directory of images with optional deletion

Changed:

  • ImageDataBunch.from_folder now takes valid_pct
  • master bar support in download_url
  • various fixes to support the latest of fastprogress
  • Learner.normalize() (without args) stores calculated stats in Learner.stats
  • pred_batch moved to basic_train and fixed for multiple inputs
  • lr_find() prints the next step to type when completed
  • New version of fastprogress used; doesn't require ipywidgets
  • Removed cifar_norm,cifar_denorm,imagenet_norm,imagenet_denorm

Fixed:

1.0.13 (2018-10-24)

New:

  • pretrained language model is now downloaded directly in the .fastai/models/ folder. Use pretrained_model=URLs.WT103
  • add an argument stop_div to Learner.lr_find() to prevent early stopping, useful for negative losses.
  • add an argument convert_mode to open_mask and SegmentationDataset to choose the PIL conversion mode of the masks.

Changed:

  • URLs.download_wt103() has been removed

1.0.12 (2018-10-23)

Fixed:

  • change TextDataBunchClass method [from_ids_files, from_tokens, from_df, from_csv, from_folder] so that classes argument is passed to the call to TextDataset
  • Strip space from file name when CSV has spaces
  • Handle missing loss_func attr
  • Pass on the use_bn parameter in get_tabular_learner
  • Bad handling when final batch has size of 1
  • rolled back numpy dependency to >=1.12 (anaconda package has a upper pin on it) and to pip>=9.0.1, the old version are buggy but should be ok for fastai

1.0.11 (2018-10-20)

Fixed:

  • Added missing pyyaml dependency to conda too

Changed:

  • Use spacy.blank instead of spacy.load to avoid having to download english model

1.0.10 (2018-10-20)

Fixed:

  • Added missing pyyaml dependency

1.0.9 (2018-10-20)

New:

  • EarlyStoppingCallback, SaveModelCallback, TerminateOnNaNCallback (initial draft: fredguth)
  • datapath4file(filename) returns suitable path to store or find data file called filename, using config file ~/.fastai/config.yml, and default data directory ~/.fastai/data, unless ./data exists and contains that file
  • MSELossFlat() loss function
  • Simple integration tests for all applications

Changed:

  • data is now called basic_data to avoid weird conflicts when naming our data objects data.
  • datasets.untar_data and datasets.download_data will now download to fastai home directory ~/.fastai/data if the dataset does not already exist locally ./data.

Fixed:

  • add dep_var column in test_df if it doesn't exists (Kevin Bird)
  • backwards=True when creating a LanguageModelLoader (mboyanov)

1.0.8 (2018-10-20)

  • Not released

1.0.7 (2018-10-19)

New:

  • New class ImagePoints for targets that are a set of point coordinates
  • New function Image.predict(learn:Learner) to get the activations of the model in Learner for an image
  • New function Learner.validate to validate on a given dl (default valid_dl), with maybe new metrics or callbacks
  • New function error_rate which is just 1-accuracy()

Changed:

  • All vision models are now in the models module, including torchvision models (where tested and supported). So use models instead of tvm now. If your preferred torchvision model isn't imported, feel free to test it out and tell us on the forum if it works. And if it doesn't, a PR with a test and a fix would be appreciated!
  • ImageBBox is now a subclass of ImagePoints
  • All metrics are now Callback. You can pass a regular function like accuracy that will get averaged over batch or a full Callback that can do more complex things
  • All datasets convenience functions and paths are inside the URLs class
  • URLs that are a sample have name now suffixed with _SAMPLE

Fixed:

  • Fix WeightDropout in RNNs when p=0
  • pad_collate gets its kwargs from TextClasDataBunch
  • Add small eps to std in TabularDataset to avoid division by zero
  • fit_one_cycle doesn't take other callbacks
  • Many broken docs links fixed

1.0.6 (2018-10-01)

  • Last release without CHANGES updates
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