basenet
Classes wrapping basic pytorch functionality.
- Train for an epoch
- Eval for an epoch
- Predict
- Learning rate schedules
Installation
conda create -n basenet4_env python=3.6 pip -y
source activate basenet4_env
pip install -r requirements.txt
conda install -y pytorch torchvision cuda90 -c pytorch
pip install -e .
Examples
cd examples/cifar
./run.sh
Release files for basenet 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| basenet-0.1.0.tar.gz | 10.0 kB | Without provenance | Details for basenet-0.1.0.tar.gz |
Release files / basenet-0.1.0.tar.gz
| Download URL | basenet-0.1.0.tar.gz |
|---|---|
| Size | 10.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
b731f852d6d444897faca9bd86309d21d7b0bcf2a475138a2fa90be358c5e86f
|
|
BLAKE2b-256 checksum How to use checksums |
798b9ea5bdcb83c5729312f0e81bc738aec8ee0c25a3f3d7c19ec6268aec02a1
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.1.1 pkginfo/1.4.2 requests/2.22.0 setuptools/45.2.0 requests-toolbelt/0.8.0 tqdm/4.30.0 CPython/3.8.10
|
Security for basenet 0.1.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
