Aligner - PyTorch
Project description
Sequence alignement methods with helpers for PyTorch.
Install
pip install aligner-pytorch
Usage
MAS
MAS (Monotonic Alignment Search) from GlowTTS. This can be used to get the alignment of any (similarity) matrix. Implementation in optimized Cython.
from aligner_pytorch import mas
sim = torch.rand(1, 4, 6) # [batch_size, m_rows, n_cols]
alignment = mas(x)
"""
sim = tensor([[
[0.2, 0.8, 0.9, 0.9, 0.9, 0.4],
[0.6, 0.8, 0.9, 0.7, 0.1, 0.4],
[1.0, 0.4, 0.4, 0.2, 1.0, 0.7],
[0.1, 0.3, 0.1, 0.7, 0.6, 0.9]
]])
alignment = tensor([[
[1, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 0, 0],
[0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 1]
]], dtype=torch.int32)
"""
Citations
Monotonic Alignment Search
@misc{2005.11129,
Author = {Jaehyeon Kim and Sungwon Kim and Jungil Kong and Sungroh Yoon},
Title = {Glow-TTS: A Generative Flow for Text-to-Speech via Monotonic Alignment Search},
Year = {2020},
Eprint = {arXiv:2005.11129},
}
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
aligner-pytorch-0.0.1.tar.gz
(3.2 kB
view details)
Built Distribution
File details
Details for the file aligner-pytorch-0.0.1.tar.gz
.
File metadata
- Download URL: aligner-pytorch-0.0.1.tar.gz
- Upload date:
- Size: 3.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.9.15
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | dce3d2e94188cf88021b8a9412eb9fe3dd8589991892e7830a76e88e49e0f52f |
|
MD5 | 5e87cf39b10f07b904eb61cbd2691c15 |
|
BLAKE2b-256 | f20ced2f11dbaf53c7c6b3e47c2a02fa4b8ffc78512d5ebd2e9d53a8e7d516b1 |
File details
Details for the file aligner_pytorch-0.0.1-py3-none-any.whl
.
File metadata
- Download URL: aligner_pytorch-0.0.1-py3-none-any.whl
- Upload date:
- Size: 3.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.9.15
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0b981ac14bb6b8362f6d99dc53306c432f8ac3b557aec532936a24a2d27502d0 |
|
MD5 | 6343df2b3c6e235f6202afc94f96c718 |
|
BLAKE2b-256 | 7169a0c29fcbc6894635138fd83ab9ff7cf95bb31941afa8add8dadcfca03050 |