A CLI and library for interacting with the Weights and Biases API.
Project description
# Weights and Biases
[![ci](https://circleci.com/gh/wandb/client.svg?style=svg)](https://circleci.com/gh/wandb/client) [![pypi](https://img.shields.io/pypi/v/wandb.svg)](https://pypi.python.org/pypi/wandb) [![coveralls](https://coveralls.io/repos/github/wandb/client/badge.svg?branch=master)](https://coveralls.io/github/wandb/client?branch=master)
A CLI and library for interacting with the Weights and Biases API. Sign up for an account at [wandb.ai](https://wandb.ai)
## Features
* Keep a history of your weights and models from every training run
* Store all configuration parameters used in a training run
* Associate version control with your training runs
* Search and visualize training runs in a project
* Sync canonical models in your preferred format
## Usage
### CLI:
```shell
cd myproject
# Initialize a directory
wandb init
# Push files to W&B
wandb push bucket model.json weights.h5
# Sync training logs and push files when they change
./my_training.py | wandb bucket model.json weights.h5
# Manage configuration
wandb config set epochs=30
```
### Client:
```python
import wandb
conf = wandb.sync(["weights.h5", "model.json"], config={'existing': 'config'})
if conf.turbo:
print("TURBO MODE!!!")
```
Detailed usage can be found in our [documentation](http://wb-client.readthedocs.io/en/latest/usage.html).
[![ci](https://circleci.com/gh/wandb/client.svg?style=svg)](https://circleci.com/gh/wandb/client) [![pypi](https://img.shields.io/pypi/v/wandb.svg)](https://pypi.python.org/pypi/wandb) [![coveralls](https://coveralls.io/repos/github/wandb/client/badge.svg?branch=master)](https://coveralls.io/github/wandb/client?branch=master)
A CLI and library for interacting with the Weights and Biases API. Sign up for an account at [wandb.ai](https://wandb.ai)
## Features
* Keep a history of your weights and models from every training run
* Store all configuration parameters used in a training run
* Associate version control with your training runs
* Search and visualize training runs in a project
* Sync canonical models in your preferred format
## Usage
### CLI:
```shell
cd myproject
# Initialize a directory
wandb init
# Push files to W&B
wandb push bucket model.json weights.h5
# Sync training logs and push files when they change
./my_training.py | wandb bucket model.json weights.h5
# Manage configuration
wandb config set epochs=30
```
### Client:
```python
import wandb
conf = wandb.sync(["weights.h5", "model.json"], config={'existing': 'config'})
if conf.turbo:
print("TURBO MODE!!!")
```
Detailed usage can be found in our [documentation](http://wb-client.readthedocs.io/en/latest/usage.html).
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
wandb-0.4.19.tar.gz
(78.5 kB
view hashes)
Built Distribution
wandb-0.4.19-py2.py3-none-any.whl
(28.4 kB
view hashes)
Close
Hashes for wandb-0.4.19-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b15db681c791deb8600593897bb3c467529c36864f90e9fd0ca19b6d0a43b1c0 |
|
MD5 | 62ef6134367ad0f2d3033b25dd8f562f |
|
BLAKE2b-256 | 6daacb51b84ad44d2e3df2c605912dc598b354aa10a85d66d9c9662a86bd9099 |