Fastai

New Features

- new callback event: `after_create` ([2842](https://github.com/fastai/fastai/issues/2842))
- This event runs after a `Learner` is constructed. It's useful for initial setup which isn't needed for every `fit`, but just once for each `Learner` (such as setting initial defaults).

- Modified XResNet to support Conv1d / Conv3d ([2744](https://github.com/fastai/fastai/pull/2744)), thanks to [floleuerer](https://github.com/floleuerer)
- Supports different input dimensions, kernel sizes and stride (added parameters ndim, ks, stride). Tested with fastai_audio and fastai time series with promising results.

Bugs Squashed

- `img_size` attribute for `TensorPoint` is not updated properly ([2799](https://github.com/fastai/fastai/pull/2799)), thanks to [IRailean](https://github.com/IRailean)

Bugs Squashed

- Undo breaking num_workers fix ([2804](https://github.com/fastai/fastai/pull/2804))
- Some users found the recent addition of `num_workers` to inference
functions was causing problems, particularly on Windows. This PR
reverts that change, until we find a more reliable way to handle
`num_workers` for inference.
- learn.tta() fails on a learner imported with load_learner() ([2764](https://github.com/fastai/fastai/issues/2764))
- learn.summary() crashes out on 2nd transfer learning ([2735](https://github.com/fastai/fastai/issues/2735))

Bugs Squashed

- Undo breaking `num_workers` fix ([2804](https://github.com/fastai/fastai/pull/2804))

Bugs Squashed

- Fix `cont_cat_split` for multi-label classification ([2759](https://github.com/fastai/fastai/issues/2759))
- fastbook error: "index 3 is out of bounds for dimension 0 with size 3" ([2792](https://github.com/fastai/fastai/issues/2792))

New Features

- update for fastcore 1.0.5 ([2775](https://github.com/fastai/fastai/issues/2775))

New Features

- "Remove pandas min version requirement" ([2765](https://github.com/fastai/fastai/issues/2765))
- Modify XResNet to support Conv1d / Conv3d ([2744](https://github.com/fastai/fastai/issues/2744))
- Also support different input dimensions, kernel sizes and stride (added parameters ndim, ks, stride).
- Add support for multidimensional arrays for RNNDropout ([2737](https://github.com/fastai/fastai/issues/2737))
- MCDropoutCallback to enable Monte Carlo Dropout in fastai. ([2733](https://github.com/fastai/fastai/issues/2733))
- A new callback to enable Monte Carlo Dropout in fastai in the `get_preds` method.
Monte Carlo Dropout is simply enabling dropout during inference.
Calling get_preds multiple times and stacking them yield of a distribution of predictions that you can use to evaluate your prediction uncertainty.
- adjustable workers in `get_preds` ([2721](https://github.com/fastai/fastai/issues/2721))