A library of helpers to train, evaluate and visualize deep nets with PyTorch.
Project description
Readme
A library of helpers for PyTorch.
Michaël Gharbi <mgharbi@adobe.com>
Installation
From pip: pip install torch-tools
From source: python setup.py install
Documentation
The documentation webpage can be found here https://torch-tools.readthedocs.io/en/latest/
Demo
For a simple demo, look at the MNIST example in examples/train_mnist.py:
python examples/train_mnist.py data out
Contributors
Dima Smirnov implemented the tensorboard hooks and callbacks.
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
torch-tools-0.0.13.tar.gz
(21.6 kB
view details)
Built Distribution
File details
Details for the file torch-tools-0.0.13.tar.gz.
File metadata
- Download URL: torch-tools-0.0.13.tar.gz
- Upload date:
- Size: 21.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.1 CPython/3.7.4
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 897b3bfc1717594177f9b6f3a0fd687a349d49e75ef070e34b8ac94edfe5972f |
|
| MD5 | 6e64f3f78304c75557fad274492b3f6a |
|
| BLAKE2b-256 | 1951e6d17dc5977b9da1bf810b3724e36505323aebf8433858a12c17351f3889 |
File details
Details for the file torch_tools-0.0.13-py3-none-any.whl.
File metadata
- Download URL: torch_tools-0.0.13-py3-none-any.whl
- Upload date:
- Size: 26.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.1 CPython/3.7.4
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 32b3137f9cf5a9bad5aa561ec7e587ebd82d50fc24186569e47fce3c3bfd2e1d |
|
| MD5 | e94dee221350d849f5c5d28a5ad0bf40 |
|
| BLAKE2b-256 | 2052a9a0806ae91a37b6d3ae4a9ffa1c25680f0ed3a2348c112ffe6c388ebc8d |
