Core layer todo list for 2.2.X [NEED CONTRIBUTION]

[zsdonghao]

• Discuss in Slack (invited link)

• Docs

  • [ ] installation
  • [ ] layers
  • [ ] the links in https://github.com/tensorlayer/awesome-tensorlayer
  • [ ] https://tensorlayer.readthedocs.io/en/2.0.0/user/examples.html
  • [x] https://tensorlayer.readthedocs.io/en/latest/modules/layers.html#batch-normalization batchnorm1d 2d 3d should be separated Rundi
  • [x] others

• Layer

  • [x] Activation act supports string inputs e.g., Dense(100, act='relu') Ruihai
  • [ ] RNN cell supports string inputs e.g., cell_fn='LSTM')
  • [ ] Remove as_layer()
  • [ ] Quantized layers should be refactored
  • [ ] tl.optimizers should be refactored
  • [ ] Optimize the `build' of core layer
  • [x] InstanceNorm 1d 2d 3d should be implemented Yingda
  • [ ] automatically deal with in_channels: super(MyLayer, self).__init__(name, in_channel=in_channel)
  • [ ] refactor QuanConv2dWithBN and etc
  • [ ] Remove below codes in layers

    self.build()
    self._built = True

• Model

  • [x] Fix model core _construct_graph BFS. @ChrisWu1997
  • [x] Add callback features for specific layer output. @ChrisWu1997

• Visualize

  • [ ] tl.vis.save_images if input is a tensor, run x.numpy() automatically.
  • Examples (Tutorial)
  • [x] text_generation
  • [x] text_ptb
  • [ ] database [WIP] @ChrisWu1997
  • [ ] distributed_training
  • [ ] tutorial_binarynet_cifar10_tfrecord.py
  • [ ] tutorial_binarynet_mnist_cnn.py
  • [ ] more in quantized_net

• Initializer

  • [ ] ours vs Keras's

• Other Examples

  • [ ] https://github.com/tensorlayer/srgan
  • [ ] https://github.com/tensorlayer/openpose-plus
  • [ ] https://github.com/tensorlayer/adaptive-style-transfer
  • [ ] https://github.com/tensorlayer/seq2seq-chatbot
  • [ ] more in https://github.com/tensorlayer/awesome-tensorlayer

• Next step

  • [ ] PointCNN
  • [ ] RL - ray/rllib