fastai 2.2.0 on Python PyPI

Promote NativeMixedPrecision to default MixedPrecision (and similar for Learner.to_fp16); old MixedPrecision is now called NonNativeMixedPrecision (#3127)
- Use the new GradientClip callback instead of the clip parameter to use gradient clipping
Adding a Callback which has the same name as an attribute no longer raises an exception (#3109)
RNN training now requires RNNCallback, but does not require RNNRegularizer; out and raw_out have moved to RNNRegularizer (#3108)
- Call rnn_cbs to get all callbacks needed for RNN training, optionally with regularization
replace callback run_after with order; do not run after cbs on exception (#3101)

Add GradientClip callback (#3107)
Make Flatten cast to TensorBase to simplify type compatibility (#3106)
make flattened metrics compatible with all tensor subclasses (#3105)
New class method TensorBase.register_func to register types for __torch_function__ (#3097)
new dynamic flag for controlling dynamic loss scaling in NativeMixedPrecision (#3096)
remove need to call to_native_fp32 before predict; set skipped in NativeMixedPrecision after NaN from dynamic loss scaling (#3095)
make native fp16 extensible with callbacks (#3094)
Calculate correct nf in create_head based on concat_pool (#3115) thanks to @muellerzr

fastai 2.2.0 v2.2.0 on Python PyPI