Skip to content

matinhosseiny/ConvLSTM_pytorch

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

6 Commits
 
 
 
 
 
 
 
 

Repository files navigation

ConvLSTM_pytorch

This file contains the implementation of Convolutional LSTM in PyTorch made by me and DavideA.

We started from this implementation and heavily refactored it add added features to match our needs.

How to Use

The ConvLSTM module derives from nn.Module so it can be used as any other PyTorch module.

The ConvLSTM class supports an arbitrary number of layers. In this case, it can be specified the hidden dimension (that is, the number of channels) and the kernel size of each layer. In the case more layers are present but a single value is provided, this is replicated for all the layers. For example, in the following snippet each of the three layers has a different hidden dimension but the same kernel size.

Example usage:

model = ConvLSTM(input_size=(height, width),
                 input_dim=channels,
                 hidden_dim=[64, 64, 128],
                 kernel_size=(3, 3),
                 num_layers=3,
                 batch_first=True
                 bias=True,
                 return_all_layers=False)

TODO (in progress...)

  • Comment code
  • Add docs
  • Add example usage on a toy problem
  • Implement stateful mechanism
  • ...

Disclaimer

This is still a work in progress and is far from being perfect: if you find any bug please don't hesitate to open an issue.

About

Implementation of Convolutional LSTM in PyTorch.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%