formatting for README

README.md

@@ -11,40 +11,54 @@ pip install k3-addons
 - ## Layers
 - ### Pooling:
  - `k3_addons.layers.AdaptiveAveragePooling1D`
+
  Multibackend Implementation of `torch.nn.AdaptiveAvgPool1d`. The results are close to PyTorch. 
  - `k3_addons.layers.AdaptiveMaxPooling1D`
+
  Multibackend Implementation of `torch.nn.AdaptiveMaxPool1d`. The results are close to PyTorch. 
  - `k3_addons.layers.AdaptiveAveragePooling2D`
+
  Multibackend Implementation of `torch.nn.AdaptiveAvgPool2d`. The results are close to PyTorch. 
  - `k3_addons.layers.AdaptiveMaxPooling2D`
+
  Multibackend Implementation of `torch.nn.AdaptiveMaxPool2d`. The results are close to PyTorch. 
  - `k3_addons.layers.Maxout`
+
  Multibackend port of `tensorflow_addons.layers.Maxout`. [Paper](https://arxiv.org/abs/1302.4389)
 
 - #### Normalization
  - `k3_addons.layers.InstanceNormalization`
- specific case of `keras.layers.GroupNormalization` since
+
+ Specific case of `keras.layers.GroupNormalization` since
  it normalizes all features of one channel. The Groupsize is equal to the
  channel size. 
 - #### Attention:
  - `k3_addons.layers.DoubleAttention`
+
  [Paper](https://arxiv.org/pdf/1810.11579.pdf)
  - `k3_addons.layers.AFTFull`
+
  [An Attention Free Transformer](https://arxiv.org/pdf/2105.14103v1.pdf)
  - `k3_addons.layers.ChannelAttention2D`
  - `k3_addons.layers.SpatialAttention2D`
  - `k3_addons.layers.ECAAttention`
+
  [ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks](https://arxiv.org/pdf/1910.03151.pdf)
  - `k3_addons.layers.ExternalAttention`
+
  [Beyond Self-attention: External Attention using Two Linear Layers for Visual Tasks](https://arxiv.org/abs/2105.02358)
  - `k3_addons.layers.ResidualAttention`
+
  [Residual Attention: A Simple but Effective Method for Multi-Label Recognition](https://arxiv.org/abs/2108.02456)
  - `k3_addons.layers.MobileViTAttention`
+
  [Coordinate Attention for Efficient Mobile Network Design](https://arxiv.org/abs/2103.02907)
  - `k3_addons.layers.BAMBlock`
  - `k3_addons.layers.CBAM`
  - `k3_addons.layers.MobileViTv2Attention`
+
  [Separable Self-attention for Mobile Vision Transformers](https://arxiv.org/abs/2206.02680)
+
  - `k3_addons.layers.ParNetAttention`
  [Non-deep Networks](https://arxiv.org/abs/2110.07641)
  - `k3_addons.layers.SimAM`