wandb-testing 0.5a3

A CLI and library for interacting with the Weights and Biases API.

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<img src="https://app.wandb.ai/logo.svg" width="350" /><br><br>
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# Weights and Biases [](https://circleci.com/gh/wandb/client) [](https://pypi.python.org/pypi/wandb)

The **Weights and Biases** client is an open source library, CLI (wandb), and local web application for organizing and analyzing your machine learning experiments. Think of it as a framework-agnostic lightweight TensorBoard that persists additional information such as the state of your code, system metrics, and configuration parameters.

## Local Features

* Store config parameters used in a training run
* Associate version control with your training runs
* Search, compare, and visualize training runs
* Analyze system usage metrics alongside runs

## Cloud Features

* Persist runs forever
* Collaborate with team members
* Run parameter sweeps

## Quickstart

```shell
pip install wandb
```

In your training script:

```python
import wandb
# Your custom arguments defined here
args = ...

run = wandb.init()
run.config.update(args)
run.config["custom"] = "parameter"

def training_loop():
while True:
# Do some machine learning
epoch, loss, val_loss = ...
run.history.add({"epoch": epoch, "loss": loss, "val_loss": val_loss})
```

Running your script will save run data in a directory named _wandb_ relative to your training script. To view your runs, call `wandb board` from the same directory as your training script.


## Cloud Usage

[Signup](https://app.wandb.ai/login?invited) for an account, then run `wandb init` from the directory with your training script. You can checkin _wandb/settings_ to version control to enable other users on your team to share experiments. Run your script with `wandb run my_script.py` and all metadata will be synced to the cloud.

## Detailed Usage

Framework specific and detailed usage can be found in our [documentation](http://docs.wandb.com/).

## Development

See https://github.com/wandb/client/blob/master/DEVELOPMENT.md