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Project description
pytorch-stateful-lstm
Free software: MIT license
Features
Pytorch LSTM implementation powered by Libtorch, and with the support of:
Hidden/Cell Clip.
Skip Connections.
Variational Dropout & DropConnect.
Managed Initial State.
Built-in TBPTT.
Benchmark: https://github.com/cnt-dev/pytorch-stateful-lstm/tree/master/benchmark
Install
Prerequisite: torch>=1.0.0, supported C++11 compiler (see here). To install through pip:
pip install pytorch-stateful-lstm
Usage
Example:
import torch
from torch.nn.utils.rnn import pack_padded_sequence, PackedSequence
from pytorch_stateful_lstm import StatefulUnidirectionalLstm
lstm = StatefulUnidirectionalLstm(
num_layers=2,
input_size=3,
hidden_size=5,
cell_size=7,
)
inputs = pack_padded_sequence(torch.rand(4, 5, 3), [5, 4, 2, 1], batch_first=True)
raw_packed_outputs, lstm_state = lstm(
inputs.data,
inputs.batch_sizes
)
outputs = PackedSequence(raw_packed_outputs, inputs.batch_sizes)
For the definition of parameters, see https://github.com/cnt-dev/pytorch-stateful-lstm/tree/master/extension.
Credits
This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.
History
0.1.0 (2019-01-03)
First release on PyPI.
