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<div align="center"> <div align="center">
<a href="https://app.community.clear.ml"><img src="https://github.com/allegroai/trains/blob/master/docs/clearml-logo.svg?raw=true" width="250px"></a> <a href="https://app.community.clear.ml"><img src="https://github.com/allegroai/clearml/blob/master/docs/clearml-logo.svg?raw=true" width="250px"></a>
**ClearML - Auto-Magical Suite of tools to streamline your ML workflow **ClearML - Auto-Magical Suite of tools to streamline your ML workflow
@ -20,9 +20,9 @@ Experiment Manager, ML-Ops and Data-Management**
#### *Formerly known as Allegro Trains* #### *Formerly known as Allegro Trains*
ClearML is a ML/DL development and production suite, it contains three main modules: ClearML is a ML/DL development and production suite, it contains three main modules:
- [Experiment Manager](#clearml-experiment-management) - Automagical experiment tracking, environments and results - [Experiment Manager](#clearml-experiment-manager) - Automagical experiment tracking, environments and results
- [ML-Ops](https://github.com/allegroai/trains-agent) - Automation, Pipelines & Orchestration solution for ML/DL jobs (K8s / Cloud / bare-metal) - [ML-Ops](https://github.com/allegroai/clearml-agent) - Automation, Pipelines & Orchestration solution for ML/DL jobs (K8s / Cloud / bare-metal)
- [Data-Management](https://github.com/allegroai/clearml/doc/clearml-data.md) - Fully differentiable data management & version control solution on top of object-storage - [Data-Management](https://github.com/allegroai/clearml/blob/master/docs/clearml-task.md) - Fully differentiable data management & version control solution on top of object-storage
(S3/GS/Azure/NAS) (S3/GS/Azure/NAS)
@ -37,7 +37,7 @@ Instrumenting these components is the **ClearML-server**, see [Self-Hosting]() &
</div> </div>
--- ---
<a href="https://app.community.clear.ml"><img src="https://github.com/allegroai/trains/blob/master/docs/webapp_screenshots.gif?raw=true" width="100%"></a> <a href="https://app.community.clear.ml"><img src="https://github.com/allegroai/clearml/blob/master/docs/webapp_screenshots.gif?raw=true" width="100%"></a>
## ClearML Experiment Manager ## ClearML Experiment Manager
@ -58,10 +58,10 @@ Instrumenting these components is the **ClearML-server**, see [Self-Hosting]() &
* Model snapshots (With optional automatic upload to central storage: Shared folder, S3, GS, Azure, Http) * Model snapshots (With optional automatic upload to central storage: Shared folder, S3, GS, Azure, Http)
* Artifacts log & store (Shared folder, S3, GS, Azure, Http) * Artifacts log & store (Shared folder, S3, GS, Azure, Http)
* Tensorboard/TensorboardX scalars, metrics, histograms, **images, audio and video samples** * Tensorboard/TensorboardX scalars, metrics, histograms, **images, audio and video samples**
* [Matplotlib & Seaborn](https://github.com/allegroai/trains/tree/master/examples/frameworks/matplotlib) * [Matplotlib & Seaborn](https://github.com/allegroai/clearml/tree/master/examples/frameworks/matplotlib)
* [ClearML Explicit Logging](https://allegro.ai/clearml/docs/examples/reporting/) interface for complete flexibility. * [ClearML Explicit Logging](https://allegro.ai/clearml/docs/examples/reporting/) interface for complete flexibility.
* Extensive platform support and integrations * Extensive platform support and integrations
* Supported ML/DL frameworks: [PyTorch](https://github.com/allegroai/trains/tree/master/examples/frameworks/pytorch)(incl' ignite/lightning), [Tensorflow](https://github.com/allegroai/trains/tree/master/examples/frameworks/tensorflow), [Keras](https://github.com/allegroai/trains/tree/master/examples/frameworks/keras), [AutoKeras](https://github.com/allegroai/trains/tree/master/examples/frameworks/autokeras), [XGBoost](https://github.com/allegroai/trains/tree/master/examples/frameworks/xgboost) and [Scikit-Learn](https://github.com/allegroai/trains/tree/master/examples/frameworks/scikit-learn) * Supported ML/DL frameworks: [PyTorch](https://github.com/allegroai/clearml/tree/master/examples/frameworks/pytorch)(incl' ignite/lightning), [Tensorflow](https://github.com/allegroai/clearml/tree/master/examples/frameworks/tensorflow), [Keras](https://github.com/allegroai/clearml/tree/master/examples/frameworks/keras), [AutoKeras](https://github.com/allegroai/clearml/tree/master/examples/frameworks/autokeras), [XGBoost](https://github.com/allegroai/clearml/tree/master/examples/frameworks/xgboost) and [Scikit-Learn](https://github.com/allegroai/clearml/tree/master/examples/frameworks/scikit-learn)
* Seamless integration (including version control) with **Jupyter Notebook** * Seamless integration (including version control) with **Jupyter Notebook**
and [*PyCharm* remote debugging](https://github.com/allegroai/trains-pycharm-plugin) and [*PyCharm* remote debugging](https://github.com/allegroai/trains-pycharm-plugin)
@ -93,8 +93,8 @@ The ClearML run-time components:
## Additional Modules ## Additional Modules
- [clearml-session](https://github.com/allegroai/clearml-session) - **Launch remote JupyterLab / VSCode-server inside any docker, on Cloud/On-Prem machines** - [clearml-session](https://github.com/allegroai/clearml-session) - **Launch remote JupyterLab / VSCode-server inside any docker, on Cloud/On-Prem machines**
- [clearml-task](https://github.com/allegroai/clearml/doc/clearml-task.md) - Run any codebase on remote machines with full remote logging of Tensorboard, Matplotlib & Console outputs - [clearml-task](https://github.com/allegroai/clearml/blob/master/docs/clearml-task.md) - Run any codebase on remote machines with full remote logging of Tensorboard, Matplotlib & Console outputs
- [clearml-data](https://github.com/allegroai/clearml/doc/clearml-data.md) - **CLI for managing and versioning your datasets, including creating / uploading / downloading of data from S3/GS/Azure/NAS** - [clearml-data](https://github.com/allegroai/clearml/blob/master/docs/datasets.md) - **CLI for managing and versioning your datasets, including creating / uploading / downloading of data from S3/GS/Azure/NAS**
- [AWS Auto-Scaler](examples/services/aws-autoscaler/aws_autoscaler.py) - Automatically spin EC2 instances based on your workloads with preconfigured budget! No need for K8s! - [AWS Auto-Scaler](examples/services/aws-autoscaler/aws_autoscaler.py) - Automatically spin EC2 instances based on your workloads with preconfigured budget! No need for K8s!
- [Hyper-Parameter Optimization](examples/services/hyper-parameter-optimization/hyper_parameter_optimizer.py) - Optimize any code with black-box approach and state of the art Bayesian optimization algorithms - [Hyper-Parameter Optimization](examples/services/hyper-parameter-optimization/hyper_parameter_optimizer.py) - Optimize any code with black-box approach and state of the art Bayesian optimization algorithms
- [Automation Pipeline](examples/pipeline/pipeline_controller.py) - Build pipelines based on existing experiments / jobs, supports building pipelines of pipelines! - [Automation Pipeline](examples/pipeline/pipeline_controller.py) - Build pipelines based on existing experiments / jobs, supports building pipelines of pipelines!
@ -138,17 +138,17 @@ Apache License, Version 2.0 (see the [LICENSE](https://www.apache.org/licenses/L
More information in the [official documentation](https://allegro.ai//clearml/docs) and [on YouTube](https://www.youtube.com/c/AllegroAI). More information in the [official documentation](https://allegro.ai//clearml/docs) and [on YouTube](https://www.youtube.com/c/AllegroAI).
For examples and use cases, check the [examples folder](https://github.com/allegroai/trains/tree/master/examples) and [corresponding documentation](https://allegro.ai/clearml/docs/examples/examples_overview/). For examples and use cases, check the [examples folder](https://github.com/allegroai/clearml/tree/master/examples) and [corresponding documentation](https://allegro.ai/clearml/docs/examples/examples_overview/).
If you have any questions: post on our [Slack Channel](https://join.slack.com/t/allegroai-trains/shared_invite/enQtOTQyMTI1MzQxMzE4LTY5NTUxOTY1NmQ1MzQ5MjRhMGRhZmM4ODE5NTNjMTg2NTBlZGQzZGVkMWU3ZDg1MGE1MjQxNDEzMWU2NmVjZmY), or tag your questions on [stackoverflow](https://stackoverflow.com/questions/tagged/trains) with '**trains**' tag. If you have any questions: post on our [Slack Channel](https://join.slack.com/t/allegroai-trains/shared_invite/enQtOTQyMTI1MzQxMzE4LTY5NTUxOTY1NmQ1MzQ5MjRhMGRhZmM4ODE5NTNjMTg2NTBlZGQzZGVkMWU3ZDg1MGE1MjQxNDEzMWU2NmVjZmY), or tag your questions on [stackoverflow](https://stackoverflow.com/questions/tagged/trains) with '**trains**' tag.
For feature requests or bug reports, please use [GitHub issues](https://github.com/allegroai/trains/issues). For feature requests or bug reports, please use [GitHub issues](https://github.com/allegroai/clearml/issues).
Additionally, you can always find us at *clearml@allegro.ai* Additionally, you can always find us at *clearml@allegro.ai*
## Contributing ## Contributing
See the ClearML [Guidelines for Contributing](https://github.com/allegroai/trains/blob/master/docs/contributing.md). See the ClearML [Guidelines for Contributing](https://github.com/allegroai/clearml/blob/master/docs/contributing.md).
_May the force (and the goddess of learning rates) be with you!_ _May the force (and the goddess of learning rates) be with you!_