Update README.md ready for merge

README.md

@@ -23,6 +23,39 @@ I'm fortunate to be able to dedicate significant time and money of my own suppor
 
 ## What's New
 
+### March 21, 2022
+* Merge `norm_norm_norm`. **IMPORTANT** this update for a coming 0.6.x release will likely de-stabilize the master branch for a while. Branch `0.5.x` or a previous 0.5.x release can be used if stability is required.
+* Significant weights update (all TPU trained) as described in this [release](https://github.com/rwightman/pytorch-image-models/releases/tag/v0.1-tpu-weights)
+  * `regnety_040` - 82.3 @ 224, 82.96 @ 288
+  * `regnety_064` - 83.0 @ 224, 83.65 @ 288
+  * `regnety_080` - 83.17 @ 224, 83.86 @ 288
+  * `regnetv_040` - 82.44 @ 224, 83.18 @ 288   (timm pre-act)
+  * `regnetv_064` - 83.1 @ 224, 83.71 @ 288   (timm pre-act)
+  * `regnetz_040` - 83.67 @ 256, 84.25 @ 320
+  * `regnetz_040h` - 83.77 @ 256, 84.5 @ 320 (w/ extra fc in head)
+  * `resnetv2_50d_gn` - 80.8 @ 224, 81.96 @ 288 (pre-act GroupNorm)
+  * `resnetv2_50d_evos` 80.77 @ 224, 82.04 @ 288 (pre-act EvoNormS)
+  * `regnetz_c16_evos`  - 81.9 @ 256, 82.64 @ 320 (EvoNormS)
+  * `regnetz_d8_evos`  - 83.42 @ 256, 84.04 @ 320 (EvoNormS)
+  * `xception41p` - 82 @ 299   (timm pre-act)
+  * `xception65` -  83.17 @ 299
+  * `xception65p` -  83.14 @ 299   (timm pre-act)
+  * `resnext101_64x4d` - 82.46 @ 224, 83.16 @ 288
+  * `seresnext101_32x8d` - 83.57 @ 224, 84.270 @ 288
+  * `resnetrs200` - 83.85 @ 256, 84.44 @ 320
+* HuggingFace hub support fixed w/ initial groundwork for allowing alternative 'config sources' for pretrained model definitions and weights (generic local file / remote url support soon)
+* SwinTransformer-V2 implementation added. Submitted by [Christoph Reich](https://github.com/ChristophReich1996). Training experiments and model changes by myself are ongoing so expect compat breaks.
+* MobileViT models w/ weights adapted from https://github.com/apple/ml-cvnets (
+* PoolFormer models w/ weights adapted from https://github.com/sail-sg/poolformer
+* VOLO models w/ weights adapted from https://github.com/sail-sg/volo
+* Significant work experimenting with non-BatchNorm norm layers such as EvoNorm, FilterResponseNorm, GroupNorm, etc
+* Enhance support for alternate norm + act ('NormAct') layers added to a number of models, esp EfficientNet/MobileNetV3, RegNet, and aligned Xception
+* Grouped conv support added to EfficientNet family
+* Add 'group matching' API to all models to allow grouping model parameters for application of 'layer-wise' LR decay, lr scale added to LR scheduler
+* Gradient checkpointing support added to many models
+* `forward_head(x, pre_logits=False)` fn added to all models to allow separate calls of `forward_features` + `forward_head`
+* All vision transformer and vision MLP models update to return non-pooled / non-token selected features from `foward_features`, for consistency with CNN models, token selection or pooling now applied in `forward_head`
+
 ### Feb 2, 2022
 * [Chris Hughes](https://github.com/Chris-hughes10) posted an exhaustive run through of `timm` on his blog yesterday. Well worth a read. [Getting Started with PyTorch Image Models (timm): A Practitioner’s Guide](https://towardsdatascience.com/getting-started-with-pytorch-image-models-timm-a-practitioners-guide-4e77b4bf9055)
 * I'm currently prepping to merge the `norm_norm_norm` branch back to master (ver 0.6.x) in next week or so.