| Name | wandb JSON |
| Version |
0.18.7
JSON |
| download |
| home_page | None |
| Summary | A CLI and library for interacting with the Weights & Biases API. |
| upload_time | 2024-11-13 23:26:21 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.7 |
| license | MIT License Copyright (c) 2021 Weights and Biases, Inc. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
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| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
<div align="center">
<img src="https://i.imgur.com/RUtiVzH.png" width="600" /><br><br>
</div>
# Weights and Biases [](https://pypi.python.org/pypi/wandb) [](https://anaconda.org/conda-forge/wandb) [](https://circleci.com/gh/wandb/wandb) [](https://codecov.io/gh/wandb/wandb)
Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to production machine learning models. Get started with W&B today, [sign up for an account!](https://wandb.com?utm_source=github&utm_medium=code&utm_campaign=wandb&utm_content=readme)
See the [W&B Developer Guide](https://docs.wandb.ai/?utm_source=github&utm_medium=code&utm_campaign=wandb&utm_content=documentation) and [API Reference Guide](https://docs.wandb.ai/ref?utm_source=github&utm_medium=code&utm_campaign=wandb&utm_content=documentation) for a full technical description of the W&B platform.
# Quickstart
Get started with W&B in four steps:
1. First, sign up for a [W&B account](https://wandb.ai/login?utm_source=github&utm_medium=code&utm_campaign=wandb&utm_content=quickstart).
2. Second, install the W&B SDK with [pip](https://pip.pypa.io/en/stable/). Navigate to your terminal and type the following command:
```shell
pip install wandb
```
3. Third, log into W&B:
```python
wandb.login()
```
4. Use the example code snippet below as a template to integrate W&B to your Python script:
```python
import wandb
# Start a W&B Run with wandb.init
run = wandb.init(project="my_first_project")
# Save model inputs and hyperparameters in a wandb.config object
config = run.config
config.learning_rate = 0.01
# Model training code here ...
# Log metrics over time to visualize performance with wandb.log
for i in range(10):
run.log({"loss": ...})
# Mark the run as finished, and finish uploading all data
run.finish()
```
For example, if the preceding code was stored in a script called train.py:
```shell
python train.py
```
You will see a URL in your terminal logs when your script starts and finishes. Data is staged locally in a directory named _wandb_ relative to your script. Navigate to the W&B App to view a dashboard of your first W&B Experiment. Use the W&B App to compare multiple experiments in a unified place, dive into the results of a single run, and much more!
# Integrations
Use your favorite framework with W&B. W&B integrations make it fast and easy to set up experiment tracking and data versioning inside existing projects. For more information on how to integrate W&B with the framework of your choice, see [W&B Integrations](https://docs.wandb.ai/guides/integrations) in the W&B Developer Guide.
# Contribution guidelines
Weights & Biases ❤️ open source, and we welcome contributions from the community! See the [Contribution guide](https://github.com/wandb/wandb/blob/main/CONTRIBUTING.md) for more information on the development workflow and the internals of the wandb library. For wandb bugs and feature requests, visit [GitHub Issues](https://github.com/wandb/wandb/issues) or contact support@wandb.com.
# Academic Researchers
Reach out to W&B Support at support@wandb.com to get a [free academic license](https://www.wandb.com/academic) for you and your research group.
# W&B Community
Be a part of the growing W&B Community and interact with the W&B team in our [Discord](https://wandb.me/discord). Stay connected with the latest ML updates and tutorials with [W&B Fully Connected](https://wandb.ai/fully-connected).
# License
[MIT License](https://github.com/wandb/wandb/blob/main/LICENSE)
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