https://github.com/tnbar/tednet

TedNet: A Pytorch Toolkit for Tensor Decomposition Networks
https://github.com/tnbar/tednet

artificial-intelligence deep-neural-networks pytorch tensor-decomposition

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TedNet: A Pytorch Toolkit for Tensor Decomposition Networks

• Host: GitHub
• URL: https://github.com/tnbar/tednet
• Owner: tnbar
• License: mit
• Created: 2020-12-04T09:36:43.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2022-04-06T03:00:27.000Z (almost 3 years ago)
• Last Synced: 2025-01-18T09:11:36.885Z (15 days ago)
• Topics: artificial-intelligence, deep-neural-networks, pytorch, tensor-decomposition
• Language: Python
• Homepage:
• Size: 313 KB
• Stars: 91
• Watchers: 3
• Forks: 12
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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# TedNet: A Pytorch Toolkit for Tensor Decomposition Networks

`tednet` is a toolkit for tensor decomposition networks. Tensor decomposition networks are neural networks whose layers are decomposed by tensor decomposition, including CANDECOMP/PARAFAC, Tucker2, Tensor Train, Tensor Ring and so on. For a convenience to do research on it, ``tednet`` provides excellent tools to deal with tensorial networks.

Now, **tednet** is easy to be installed by `pip`:

```shell script

pip install tednet

```

More information could be found in [Document](https://tednet.readthedocs.io/en/latest/index.html).

---

### Quick Start

##### Operation

There are some operations supported in `tednet`, and it is convinient to use them. First, import it:

```python

import tednet as tdt

```

Create matrix whose diagonal elements are ones:

```python

diag_matrix = tdt.eye(5, 5)

```

A way to transfer the Pytorch tensor into numpy array:

```python

diag_matrix = tdt.to_numpy(diag_matrix)

```

Similarly, the numpy array can be taken into Pytorch tensor by:

```python

diag_matrix = tdt.to_tensor(diag_matrix)

```

##### Tensor Decomposition Networks (Tensor Ring for Sample)

To use tensor ring decomposition models, simply calling the tensor ring module is enough.

```python

import tednet.tnn.tensor_ring as tr

# Define a TR-LeNet5

model = tr.TRLeNet5(10, [6, 6, 6, 6])

```

---

### Citing

If you use `tednet` in an academic work, we will appreciate you for citing our paper with:

```bibtex

@article{DBLP:journals/ijon/PanWX22,

  author    = {Yu Pan and

               Maolin Wang and

               Zenglin Xu},

  title     = {TedNet: {A} Pytorch toolkit for tensor decomposition networks},

  journal   = {Neurocomputing},

  volume    = {469},

  pages     = {234--238},

  year      = {2022}

}

```