PyTorch implementation of Dilated Recurrent Neural Networks (DilatedRNN).
Installation:
pip install -r requirements.txt
Run the tests:
python tests.py
Define a dilated RNN based on GRU cells with 9 layers, dilations 1, 2, 4, 8, 16, ... Then pass the hidden state to a further update
import drnn
import torch
n_input = 20
n_hidden = 32
n_layers = 9
cell_type = 'GRU'
model = drnn.DRNN(n_input, n_hidden, n_layers, cell_type)
x1 = torch.autograd.Variable(torch.randn(23, 2, n_input))
x2 = torch.autograd.Variable(torch.randn(23, 2, n_input))
out, hidden = model(x1)
out, hidden = model(x2, hidden)python3 -m copy_memory.copymem_test --help
python3 -m char_rnn.char_rnn_test --help
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