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allegroai 2021-06-07 01:01:50 +03:00
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@ -58,13 +58,13 @@ Instrumenting these components is the **ClearML-server**, see [Self-Hosting](htt
* 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/clearml/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/docs/tutorials/tutorial_explicit_reporting.html#step-2-logger-class-reporting-methods) interface for complete flexibility. * [ClearML Logger](https://clear.ml/docs/latest/docs/fundamentals/logger) interface for complete flexibility.
* Extensive platform support and integrations * Extensive platform support and integrations
* 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) * 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)
#### [Start using ClearML](https://allegro.ai/clearml/docs/rst/getting_started/index.html) #### [Start using ClearML](https://clear.ml/docs/latest/docs/getting_started/ds/ds_first_steps)
```bash ```bash
pip install clearml pip install clearml
@ -77,7 +77,7 @@ task = Task.init(project_name='examples', task_name='hello world')
``` ```
You are done, everything your process outputs is now automagically logged into ClearML. You are done, everything your process outputs is now automagically logged into ClearML.
<br>Next step automation! **Learn more on ClearML two clicks automation [here](https://allegro.ai/clearml/docs/rst/clearml_agent/index.html)** <br>Next step automation! **Learn more on ClearML two clicks automation [here](https://clear.ml/docs/latest/docs/getting_started/mlops/mlops_first_steps)**
## ClearML Architecture ## ClearML Architecture
@ -87,17 +87,17 @@ The ClearML run-time components:
* The ClearML Server storing experiment, model, and workflow data, and supporting the Web UI experiment manager, and ML-Ops automation for reproducibility and tuning. It is available as a hosted service and open source for you to deploy your own ClearML Server. * The ClearML Server storing experiment, model, and workflow data, and supporting the Web UI experiment manager, and ML-Ops automation for reproducibility and tuning. It is available as a hosted service and open source for you to deploy your own ClearML Server.
* The ClearML Agent for ML-Ops orchestration, experiment and workflow reproducibility, and scalability. * The ClearML Agent for ML-Ops orchestration, experiment and workflow reproducibility, and scalability.
<img src="https://allegro.ai/clearml/docs/_images/ClearML_Architecture.png" width="100%" alt="clearml-architecture"> <img src="https://raw.githubusercontent.com/allegroai/clearml-docs/main/docs/img/clearml_architecture.png" width="100%" alt="clearml-architecture">
## 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/blob/master/docs/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/blob/master/docs/datasets.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](https://allegro.ai/clearml/docs/docs/examples/services/aws_autoscaler/aws_autoscaler.html) - Automatically spin EC2 instances based on your workloads with preconfigured budget! No need for K8s! - [AWS Auto-Scaler](https://clear.ml/docs/latest/docs/guides/services/aws_autoscaler) - Automatically spin EC2 instances based on your workloads with preconfigured budget! No need for K8s!
- [Hyper-Parameter Optimization](https://allegro.ai/clearml/docs/docs/examples/frameworks/pytorch/notebooks/image/hyperparameter_search.html) - Optimize any code with black-box approach and state of the art Bayesian optimization algorithms - [Hyper-Parameter Optimization](https://clear.ml/docs/latest/docs/guides/optimization/hyper-parameter-optimization/examples_hyperparam_opt) - Optimize any code with black-box approach and state of the art Bayesian optimization algorithms
- [Automation Pipeline](https://allegro.ai/clearml/docs/docs/examples/frameworks/pytorch/notebooks/table/tabular_training_pipeline.html) - Build pipelines based on existing experiments / jobs, supports building pipelines of pipelines! - [Automation Pipeline](https://clear.ml/docs/latest/docs/guides/pipeline/pipeline_controller) - Build pipelines based on existing experiments / jobs, supports building pipelines of pipelines!
- [Slack Integration](https://allegro.ai/clearml/docs/docs/examples/services/monitoring/slack_alerts.html) - Report experiments progress / failure directly to Slack (fully customizable!) - [Slack Integration](https://clear.ml/docs/latest/docs/guides/services/slack_alerts) - Report experiments progress / failure directly to Slack (fully customizable!)
## Why ClearML? ## Why ClearML?
@ -135,9 +135,9 @@ Apache License, Version 2.0 (see the [LICENSE](https://www.apache.org/licenses/L
## Documentation, Community & Support ## Documentation, Community & Support
More information in the [official documentation](https://allegro.ai/clearml/docs) and [on YouTube](https://www.youtube.com/c/ClearML). More information in the [official documentation](https://clear.ml/docs) and [on YouTube](https://www.youtube.com/c/ClearML).
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/rst/examples/index.html). For examples and use cases, check the [examples folder](https://github.com/allegroai/clearml/tree/master/examples) and [corresponding documentation](https://clear.ml/docs/latest/docs/guides).
If you have any questions: post on our [Slack Channel](https://join.slack.com/t/clearml/shared_invite/zt-c0t13pty-aVUZZW1TSSSg2vyIGVPBhg), or tag your questions on [stackoverflow](https://stackoverflow.com/questions/tagged/clearml) with '**[clearml](https://stackoverflow.com/questions/tagged/clearml)**' tag (*previously [trains](https://stackoverflow.com/questions/tagged/trains) tag*). If you have any questions: post on our [Slack Channel](https://join.slack.com/t/clearml/shared_invite/zt-c0t13pty-aVUZZW1TSSSg2vyIGVPBhg), or tag your questions on [stackoverflow](https://stackoverflow.com/questions/tagged/clearml) with '**[clearml](https://stackoverflow.com/questions/tagged/clearml)**' tag (*previously [trains](https://stackoverflow.com/questions/tagged/trains) tag*).