Liquid Net - Pytorch
Project description
LiquidNet
This is a simple implementation of the Liquid net official repo translated into pytorch for simplicity. Find the original repo here:
Install
pip install liquid-net
Usage
import torch
from liquidnet.main import LiquidNet
# Create an LiquidNet with a specified number of units
num_units = 64
ltc_cell = LiquidNet(num_units)
# Generate random input data with batch size 4 and input size 32
batch_size = 4
input_size = 32
inputs = torch.randn(batch_size, input_size)
# Initialize the cell state (hidden state)
initial_state = torch.zeros(batch_size, num_units)
# Forward pass through the LiquidNet
outputs, final_state = ltc_cell(inputs, initial_state)
# Print the shape of outputs and final_state
print("Outputs shape:", outputs.shape)
print("Final state shape:", final_state.shape)
Citation
@article{DBLP:journals/corr/abs-2006-04439,
author = {Ramin M. Hasani and
Mathias Lechner and
Alexander Amini and
Daniela Rus and
Radu Grosu},
title = {Liquid Time-constant Networks},
journal = {CoRR},
volume = {abs/2006.04439},
year = {2020},
url = {https://arxiv.org/abs/2006.04439},
eprinttype = {arXiv},
eprint = {2006.04439},
timestamp = {Fri, 12 Jun 2020 14:02:57 +0200},
biburl = {https://dblp.org/rec/journals/corr/abs-2006-04439.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
License
MIT
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