Skip to main content

Machine Learning tool allowing plug-and-play training for pytorch models

Project description

pyroml

🔥 Machine Learning tool allowing plug-and-play training for pytorch models

Installation

$ git clone https://github.com/peacefulotter/pyroml.git
$ cd pyroml
$ sudo apt install python3.10-venv # check you python version and change it here if !=
$ sudo apt install python3-virtualenv
$ python3 -m venv venv
$ source ./venv/bin/activate
$ pip install -r requirements.txt

Running tests

$ cd tests
$ python main.py # this will launch the training, goto https://wandb.ai/otters-gang/pyro_main_test/workspace  to see the training occuring (should be really fast)
$ python pretrain.py # will load the last checkpoint and compute mse on a small part of the dataset, outputs True if model predicts correctly!

Done

  • Metrics, with support for custom metrics
  • WandB
  • Checkpoints
  • Load pretrained models from checkpoints

TODO:

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pyroml-0.0.2.tar.gz (2.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pyroml-0.0.2-py3-none-any.whl (2.5 kB view details)

Uploaded Python 3

File details

Details for the file pyroml-0.0.2.tar.gz.

File metadata

  • Download URL: pyroml-0.0.2.tar.gz
  • Upload date:
  • Size: 2.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.12

File hashes

Hashes for pyroml-0.0.2.tar.gz
Algorithm Hash digest
SHA256 419a835258bec3968218df1d0ca4c195eda200ac2ab50393c9a908cd1f8cfa01
MD5 28dc9dfbf49dba5486507c61762aa299
BLAKE2b-256 c89219531d7819df6566445d9ac9a6b4de3aca507d1e6f16068d3b59a265bfcf

See more details on using hashes here.

File details

Details for the file pyroml-0.0.2-py3-none-any.whl.

File metadata

  • Download URL: pyroml-0.0.2-py3-none-any.whl
  • Upload date:
  • Size: 2.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.12

File hashes

Hashes for pyroml-0.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 02530b15aa9b22c0d7a7b291c6934749e2dc5596fbe7714f6f7aeabe3f1dc9d6
MD5 b8dccb4e63a3d98caa231f3ab344b5fe
BLAKE2b-256 6c4227c8aef9976aaecb712b0585b66fbf067f3b5315c0bd88a211653383d0d7

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page