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1.132-3.368.397-.406.89-.717 1.474-.952 1.399-1.136 3.392-2.093 6.122-2.093 2.731 0 4.767.957 6.166 2.093.584.235 1.077.546 1.474.952.85.869 1.132 2.037 1.132 3.368 0 .368-.014.733-.052 1.086.23.462.477 1.088.644 1.517 1.258.364 2.233 1.721 2.605 2.656a.832.832 0 0 1 .053.22v2.869a.641.641 0 0 1-.078.256ZM12.172 11h-.344a4.323 4.323 0 0 1-.355.508C10.703 12.455 9.555 13 7.965 13c-1.725 0-2.989-.359-3.782-1.259a2.005 2.005 0 0 1-.085-.104L4 11.741v6.585c1.435.779 4.514 2.179 8 2.179 3.486 0 6.565-1.4 8-2.179v-6.585l-.098-.104s-.033.045-.085.104c-.793.9-2.057 1.259-3.782 1.259-1.59 0-2.738-.545-3.508-1.492a4.323 4.323 0 0 1-.355-.508h-.016.016Zm.641-2.935c.136 1.057.403 1.913.878 2.497.442.544 1.134.938 2.344.938 1.573 0 2.292-.337 2.657-.751.384-.435.558-1.15.558-2.361 0-1.14-.243-1.847-.705-2.319-.477-.488-1.319-.862-2.824-1.025-1.487-.161-2.192.138-2.533.529-.269.307-.437.808-.438 1.578v.021c0 .265.021.562.063.893Zm-1.626 0c.042-.331.063-.628.063-.894v-.02c-.001-.77-.169-1.271-.438-1.578-.341-.391-1.046-.69-2.533-.529-1.505.163-2.347.537-2.824 1.025-.462.472-.705 1.179-.705 2.319 0 1.211.175 1.926.558 2.361.365.414 1.084.751 2.657.751 1.21 0 1.902-.394 2.344-.938.475-.584.742-1.44.878-2.497Z"></path><path d="M14.5 14.25a1 1 0 0 1 1 1v2a1 1 0 0 1-2 0v-2a1 1 0 0 1 1-1Zm-5 0a1 1 0 0 1 1 1v2a1 1 0 0 1-2 0v-2a1 1 0 0 1 1-1Z"></path> </svg> <div> <div class="color-fg-default h4">GitHub Copilot</div> Write better code with AI </div> </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary d-flex flex-items-center Link--has-description pb-lg-3" data-analytics-event="{"location":"navbar","action":"security","context":"product","tag":"link","label":"security_link_product_navbar"}" href="https://github.com/features/security"> <svg aria-hidden="true" height="24" viewBox="0 0 24 24" version="1.1" width="24" data-view-component="true" class="octicon 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star to support the project! 🌟\u003c/code\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003chr\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eClearML\u003c/h3\u003e\u003ca id=\"user-content-clearml\" class=\"anchor\" aria-label=\"Permalink: ClearML\" href=\"#clearml\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eClearML is a ML/DL development and production suite. It contains FIVE main modules:\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003e\u003ca href=\"#clearml-experiment-manager\"\u003eExperiment Manager\u003c/a\u003e - Automagical experiment tracking, environments and results\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/clearml/clearml-agent\"\u003eMLOps / LLMOps\u003c/a\u003e - Orchestration, Automation \u0026amp; Pipelines solution for ML/DL/GenAI jobs (Kubernetes / Cloud / bare-metal)\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/clearml/clearml/blob/master/docs/datasets.md\"\u003eData-Management\u003c/a\u003e - Fully differentiable data management \u0026amp; version control solution on top of object-storage\n(S3 / GS / Azure / NAS)\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/clearml/clearml-serving\"\u003eModel-Serving\u003c/a\u003e - \u003cem\u003ecloud-ready\u003c/em\u003e Scalable model serving solution!\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003e\u003cstrong\u003eDeploy new model endpoints in under 5 minutes\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003eIncludes optimized GPU serving support backed by Nvidia-Triton\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003ewith out-of-the-box Model Monitoring\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://clear.ml/docs/latest/docs/webapp/webapp_reports\" rel=\"nofollow\"\u003eReports\u003c/a\u003e - Create and share rich MarkDown documents supporting embeddable online content\u003c/li\u003e\n\u003cli\u003e🔥 \u003ca href=\"https://clear.ml/docs/latest/docs/webapp/webapp_orchestration_dash/\" rel=\"nofollow\"\u003eOrchestration Dashboard\u003c/a\u003e - Live rich dashboard for your entire compute cluster (Cloud / Kubernetes / On-Prem)\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eNEW\u003c/strong\u003e 💥 \u003ca href=\"https://github.com/clearml/clearml-fractional-gpu\"\u003eFractional GPUs\u003c/a\u003e - Container based, driver level GPU memory limitation 🙀 !!!\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp dir=\"auto\"\u003eInstrumenting these components is the \u003cstrong\u003eClearML-server\u003c/strong\u003e, see \u003ca href=\"https://clear.ml/docs/latest/docs/deploying_clearml/clearml_server\" rel=\"nofollow\"\u003eSelf-Hosting\u003c/a\u003e \u0026amp; \u003ca href=\"https://app.clear.ml\" rel=\"nofollow\"\u003eFree tier Hosting\u003c/a\u003e\u003c/p\u003e\n\u003chr\u003e\n\u003cdiv align=\"center\" dir=\"auto\"\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003e\u003ca href=\"https://app.clear.ml\" rel=\"nofollow\"\u003eSign up\u003c/a\u003e \u0026amp; \u003ca href=\"https://clear.ml/docs/\" rel=\"nofollow\"\u003eStart using\u003c/a\u003e in under 2 minutes\u003c/strong\u003e\u003c/p\u003e\n\u003chr\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003eFriendly tutorials to get you started\u003c/strong\u003e\u003c/p\u003e\n\u003cmarkdown-accessiblity-table\u003e\u003ctable\u003e\n\u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://github.com/clearml/clearml/blob/master/docs/tutorials/Getting_Started_1_Experiment_Management.ipynb\"\u003e\u003cb\u003eStep 1\u003c/b\u003e\u003c/a\u003e - Experiment Management\u003c/td\u003e\n \u003ctd\u003e\u003ca href=\"https://colab.research.google.com/github/clearml/clearml/blob/master/docs/tutorials/Getting_Started_1_Experiment_Management.ipynb\" rel=\"nofollow\"\u003e\n \u003cimg src=\"https://camo.githubusercontent.com/96889048f8a9014fdeba2a891f97150c6aac6e723f5190236b10215a97ed41f3/68747470733a2f2f636f6c61622e72657365617263682e676f6f676c652e636f6d2f6173736574732f636f6c61622d62616467652e737667\" alt=\"Open In Colab\" data-canonical-src=\"https://colab.research.google.com/assets/colab-badge.svg\" style=\"max-width: 100%;\"\u003e\n\u003c/a\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://github.com/clearml/clearml/blob/master/docs/tutorials/Getting_Started_2_Setting_Up_Agent.ipynb\"\u003e\u003cb\u003eStep 2\u003c/b\u003e\u003c/a\u003e - Remote Execution Agent Setup\u003c/td\u003e\n \u003ctd\u003e\u003ca href=\"https://colab.research.google.com/github/clearml/clearml/blob/master/docs/tutorials/Getting_Started_2_Setting_Up_Agent.ipynb\" rel=\"nofollow\"\u003e\n \u003cimg src=\"https://camo.githubusercontent.com/96889048f8a9014fdeba2a891f97150c6aac6e723f5190236b10215a97ed41f3/68747470733a2f2f636f6c61622e72657365617263682e676f6f676c652e636f6d2f6173736574732f636f6c61622d62616467652e737667\" alt=\"Open In Colab\" data-canonical-src=\"https://colab.research.google.com/assets/colab-badge.svg\" style=\"max-width: 100%;\"\u003e\n\u003c/a\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://github.com/clearml/clearml/blob/master/docs/tutorials/Getting_Started_3_Remote_Execution.ipynb\"\u003e\u003cb\u003eStep 3\u003c/b\u003e\u003c/a\u003e - Remotely Execute Tasks\u003c/td\u003e\n \u003ctd\u003e\u003ca href=\"https://colab.research.google.com/github/clearml/clearml/blob/master/docs/tutorials/Getting_Started_3_Remote_Execution.ipynb\" rel=\"nofollow\"\u003e\n \u003cimg src=\"https://camo.githubusercontent.com/96889048f8a9014fdeba2a891f97150c6aac6e723f5190236b10215a97ed41f3/68747470733a2f2f636f6c61622e72657365617263682e676f6f676c652e636f6d2f6173736574732f636f6c61622d62616467652e737667\" alt=\"Open In Colab\" data-canonical-src=\"https://colab.research.google.com/assets/colab-badge.svg\" style=\"max-width: 100%;\"\u003e\n\u003c/a\u003e\u003c/td\u003e\n \u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/markdown-accessiblity-table\u003e\n\u003c/div\u003e\n\u003chr\u003e\n\u003cmarkdown-accessiblity-table\u003e\u003ctable\u003e\n\u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003eExperiment Management\u003c/td\u003e\n \u003ctd\u003eDatasets\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://app.clear.ml\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/clearml/clearml/raw/master/docs/experiment_manager.gif?raw=true\" width=\"100%\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e\u003ca href=\"https://app.clear.ml/datasets\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/clearml/clearml/raw/master/docs/datasets.gif?raw=true\" width=\"100%\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" height=\"24px\"\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eOrchestration\u003c/td\u003e\n \u003ctd\u003ePipelines\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://app.clear.ml/workers-and-queues/autoscalers\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/clearml/clearml/raw/master/docs/orchestration.gif?raw=true\" width=\"100%\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e\u003ca href=\"https://app.clear.ml/pipelines\" rel=\"nofollow\"\u003e\u003cimg src=\"https://github.com/clearml/clearml/raw/master/docs/pipelines.gif?raw=true\" width=\"100%\" data-animated-image=\"\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/td\u003e\n \u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/markdown-accessiblity-table\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eClearML Experiment Manager\u003c/h2\u003e\u003ca id=\"user-content-clearml-experiment-manager\" class=\"anchor\" aria-label=\"Permalink: ClearML Experiment Manager\" href=\"#clearml-experiment-manager\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003eAdding only 2 lines to your code gets you the following\u003c/strong\u003e\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003eComplete experiment setup log\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003eFull source control info, including non-committed local changes\u003c/li\u003e\n\u003cli\u003eExecution environment (including specific packages \u0026amp; versions)\u003c/li\u003e\n\u003cli\u003eHyper-parameters\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003e\u003ca href=\"https://docs.python.org/3/library/argparse.html\" rel=\"nofollow\"\u003e\u003ccode\u003eargparse\u003c/code\u003e\u003c/a\u003e/\u003ca href=\"https://github.com/pallets/click/\"\u003eClick\u003c/a\u003e/\u003ca href=\"https://github.com/google/python-fire\"\u003ePythonFire\u003c/a\u003e for command line parameters with currently used values\u003c/li\u003e\n\u003cli\u003eExplicit parameters dictionary\u003c/li\u003e\n\u003cli\u003eTensorflow Defines (absl-py)\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/facebookresearch/hydra\"\u003eHydra\u003c/a\u003e configuration and overrides\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003eInitial model weights file\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003eFull experiment output automatic capture\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003estdout and stderr\u003c/li\u003e\n\u003cli\u003eResource Monitoring (CPU/GPU utilization, temperature, IO, network, etc.)\u003c/li\u003e\n\u003cli\u003eModel snapshots (With optional automatic upload to central storage: Shared folder, S3, GS, Azure, Http)\u003c/li\u003e\n\u003cli\u003eArtifacts log \u0026amp; store (Shared folder, S3, GS, Azure, Http)\u003c/li\u003e\n\u003cli\u003eTensorboard/\u003ca href=\"https://github.com/clearml/clearml/tree/master/examples/frameworks/tensorboardx\"\u003eTensorboardX\u003c/a\u003e scalars, metrics, histograms, \u003cstrong\u003eimages, audio and video samples\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/clearml/clearml/tree/master/examples/frameworks/matplotlib\"\u003eMatplotlib \u0026amp; Seaborn\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://clear.ml/docs/latest/docs/fundamentals/logger\" rel=\"nofollow\"\u003eClearML Logger\u003c/a\u003e interface for complete flexibility.\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003eExtensive platform support and integrations\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003eSupported ML/DL frameworks: \u003ca href=\"https://github.com/clearml/clearml/tree/master/examples/frameworks/pytorch\"\u003ePyTorch\u003c/a\u003e (incl' \u003ca href=\"https://github.com/clearml/clearml/tree/master/examples/frameworks/ignite\"\u003eignite\u003c/a\u003e / \u003ca href=\"https://github.com/clearml/clearml/tree/master/examples/frameworks/pytorch-lightning\"\u003elightning\u003c/a\u003e), \u003ca href=\"https://github.com/clearml/clearml/tree/master/examples/frameworks/tensorflow\"\u003eTensorflow\u003c/a\u003e, \u003ca href=\"https://github.com/clearml/clearml/tree/master/examples/frameworks/keras\"\u003eKeras\u003c/a\u003e, \u003ca href=\"https://github.com/clearml/clearml/tree/master/examples/frameworks/autokeras\"\u003eAutoKeras\u003c/a\u003e, \u003ca href=\"https://github.com/clearml/clearml/tree/master/examples/frameworks/fastai\"\u003eFastAI\u003c/a\u003e, \u003ca href=\"https://github.com/clearml/clearml/tree/master/examples/frameworks/xgboost\"\u003eXGBoost\u003c/a\u003e, \u003ca href=\"https://github.com/clearml/clearml/tree/master/examples/frameworks/lightgbm\"\u003eLightGBM\u003c/a\u003e, \u003ca href=\"https://github.com/clearml/clearml/tree/master/examples/frameworks/megengine\"\u003eMegEngine\u003c/a\u003e and \u003ca href=\"https://github.com/clearml/clearml/tree/master/examples/frameworks/scikit-learn\"\u003eScikit-Learn\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003eSeamless integration (including version control) with \u003ca href=\"https://jupyter.org/\" rel=\"nofollow\"\u003e\u003cstrong\u003eJupyter Notebook\u003c/strong\u003e\u003c/a\u003e\nand \u003ca href=\"https://github.com/clearml/trains-pycharm-plugin\"\u003e\u003cem\u003ePyCharm\u003c/em\u003e remote debugging\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch4 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003e\u003ca href=\"https://clear.ml/docs/latest/docs/getting_started/ds/ds_first_steps\" rel=\"nofollow\"\u003eStart using ClearML\u003c/a\u003e\u003c/h4\u003e\u003ca id=\"user-content-start-using-clearml\" class=\"anchor\" aria-label=\"Permalink: Start using ClearML\" href=\"#start-using-clearml\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003col dir=\"auto\"\u003e\n\u003cli\u003e\n\u003cp dir=\"auto\"\u003eSign up for free to the \u003ca href=\"https://app.clear.ml\" rel=\"nofollow\"\u003eClearML Hosted Service\u003c/a\u003e (alternatively, you can set up your own server, see \u003ca href=\"https://clear.ml/docs/latest/docs/deploying_clearml/clearml_server\" rel=\"nofollow\"\u003ehere\u003c/a\u003e).\u003c/p\u003e\n\u003cblockquote\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003e\u003cem\u003eClearML Demo Server:\u003c/em\u003e\u003c/strong\u003e ClearML no longer uses the demo server by default. To enable the demo server, set the \u003ccode\u003eCLEARML_NO_DEFAULT_SERVER=0\u003c/code\u003e\nenvironment variable. Credentials aren't needed, but experiments launched to the demo server are public, so make sure not\nto launch sensitive experiments if using the demo server.\u003c/p\u003e\n\u003c/blockquote\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp dir=\"auto\"\u003eInstall the \u003ccode\u003eclearml\u003c/code\u003e python package:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"pip install clearml\"\u003e\u003cpre\u003epip install clearml\u003c/pre\u003e\u003c/div\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp dir=\"auto\"\u003eConnect the ClearML SDK to the server by \u003ca href=\"https://app.clear.ml/settings/workspace-configuration\" rel=\"nofollow\"\u003ecreating credentials\u003c/a\u003e, then execute the command\nbelow and follow the instructions:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"clearml-init\"\u003e\u003cpre\u003eclearml-init\u003c/pre\u003e\u003c/div\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp dir=\"auto\"\u003eAdd two lines to your code:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-python notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"from clearml import Task\ntask = Task.init(project_name='examples', task_name='hello world')\"\u003e\u003cpre\u003e\u003cspan class=\"pl-k\"\u003efrom\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003eclearml\u003c/span\u003e \u003cspan class=\"pl-k\"\u003eimport\u003c/span\u003e \u003cspan class=\"pl-v\"\u003eTask\u003c/span\u003e\n\u003cspan class=\"pl-s1\"\u003etask\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-v\"\u003eTask\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003einit\u003c/span\u003e(\u003cspan class=\"pl-s1\"\u003eproject_name\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e\u003cspan class=\"pl-s\"\u003e'examples'\u003c/span\u003e, \u003cspan class=\"pl-s1\"\u003etask_name\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e\u003cspan class=\"pl-s\"\u003e'hello world'\u003c/span\u003e)\u003c/pre\u003e\u003c/div\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp dir=\"auto\"\u003eAnd you are done! Everything your process outputs is now automagically logged into ClearML.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eNext step, automation! \u003cstrong\u003eLearn more about ClearML's two-click automation \u003ca href=\"https://clear.ml/docs/latest/docs/getting_started/mlops/mlops_first_steps\" rel=\"nofollow\"\u003ehere\u003c/a\u003e\u003c/strong\u003e.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eClearML Architecture\u003c/h2\u003e\u003ca id=\"user-content-clearml-architecture\" class=\"anchor\" aria-label=\"Permalink: ClearML Architecture\" href=\"#clearml-architecture\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eThe ClearML run-time components:\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003eThe ClearML Python Package - for integrating ClearML into your existing scripts by adding just two lines of code, and optionally extending your experiments and other workflows with ClearML's powerful and versatile set of classes and methods.\u003c/li\u003e\n\u003cli\u003eThe ClearML Server - for storing experiment, model, and workflow data; supporting the Web UI experiment manager and MLOps automation for reproducibility and tuning. It is available as a hosted service and open source for you to deploy your own ClearML Server.\u003c/li\u003e\n\u003cli\u003eThe ClearML Agent - for MLOps orchestration, experiment and workflow reproducibility, and scalability.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp dir=\"auto\"\u003e\u003ca target=\"_blank\" rel=\"noopener noreferrer nofollow\" href=\"https://raw.githubusercontent.com/clearml/clearml-docs/main/docs/img/clearml_architecture.png\"\u003e\u003cimg src=\"https://raw.githubusercontent.com/clearml/clearml-docs/main/docs/img/clearml_architecture.png\" width=\"100%\" alt=\"clearml-architecture\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eAdditional Modules\u003c/h2\u003e\u003ca id=\"user-content-additional-modules\" class=\"anchor\" aria-label=\"Permalink: Additional Modules\" href=\"#additional-modules\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/clearml/clearml-session\"\u003eclearml-session\u003c/a\u003e - \u003cstrong\u003eLaunch remote JupyterLab / VSCode-server inside any docker, on Cloud/On-Prem machines\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/clearml/clearml/blob/master/docs/clearml-task.md\"\u003eclearml-task\u003c/a\u003e - Run any codebase on remote machines with full remote logging of Tensorboard, Matplotlib \u0026amp; Console outputs\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://github.com/clearml/clearml/blob/master/docs/datasets.md\"\u003eclearml-data\u003c/a\u003e - \u003cstrong\u003eCLI for managing and versioning your datasets, including creating / uploading / downloading of data from S3/GS/Azure/NAS\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://clear.ml/docs/latest/docs/guides/services/aws_autoscaler\" rel=\"nofollow\"\u003eAWS Auto-Scaler\u003c/a\u003e - Automatically spin EC2 instances based on your workloads with preconfigured budget! No need for AKE!\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://clear.ml/docs/latest/docs/guides/optimization/hyper-parameter-optimization/examples_hyperparam_opt\" rel=\"nofollow\"\u003eHyper-Parameter Optimization\u003c/a\u003e - Optimize any code with black-box approach and state-of-the-art Bayesian optimization algorithms\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://clear.ml/docs/latest/docs/guides/pipeline/pipeline_controller\" rel=\"nofollow\"\u003eAutomation Pipeline\u003c/a\u003e - Build pipelines based on existing experiments / jobs, supports building pipelines of pipelines!\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://clear.ml/docs/latest/docs/guides/services/slack_alerts\" rel=\"nofollow\"\u003eSlack Integration\u003c/a\u003e - Report experiments progress / failure directly to Slack (fully customizable!)\u003c/li\u003e\n\u003c/ul\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eWhy ClearML?\u003c/h2\u003e\u003ca id=\"user-content-why-clearml\" class=\"anchor\" aria-label=\"Permalink: Why ClearML?\" href=\"#why-clearml\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eClearML is our solution to a problem we share with countless other researchers and developers in the machine\nlearning/deep learning universe: Training production-grade deep learning models is a glorious but messy process.\nClearML tracks and controls the process by associating code version control, research projects,\nperformance metrics, and model provenance.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eWe designed ClearML specifically to require effortless integration so that teams can preserve their existing methods\nand practices.\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003eUse it on a daily basis to boost collaboration and visibility in your team\u003c/li\u003e\n\u003cli\u003eCreate a remote job from any experiment with a click of a button\u003c/li\u003e\n\u003cli\u003eAutomate processes and create pipelines to collect your experimentation logs, outputs, and data\u003c/li\u003e\n\u003cli\u003eStore all your data on any object-storage solution, with the most straightforward interface possible\u003c/li\u003e\n\u003cli\u003eMake your data transparent by cataloging it all on the ClearML platform\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp dir=\"auto\"\u003eWe believe ClearML is ground-breaking. We wish to establish new standards of true seamless integration between\nexperiment management, MLOps, and data management.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eWho We Are\u003c/h2\u003e\u003ca id=\"user-content-who-we-are\" class=\"anchor\" aria-label=\"Permalink: Who We Are\" href=\"#who-we-are\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eClearML is supported by you and the \u003ca href=\"https://clear.ml\" rel=\"nofollow\"\u003eclear.ml\u003c/a\u003e team, which helps enterprise companies build scalable MLOps.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eWe built ClearML to track and control the glorious but messy process of training production-grade deep learning models.\nWe are committed to vigorously supporting and expanding the capabilities of ClearML.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eWe promise to always be backwardly compatible, making sure all your logs, data, and pipelines will always upgrade with you.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eLicense\u003c/h2\u003e\u003ca id=\"user-content-license\" class=\"anchor\" aria-label=\"Permalink: License\" href=\"#license\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eApache License, Version 2.0 (see the \u003ca href=\"https://www.apache.org/licenses/LICENSE-2.0.html\" rel=\"nofollow\"\u003eLICENSE\u003c/a\u003e for more information)\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eIf ClearML is part of your development process / project / publication, please cite us ❤️ :\u003c/p\u003e\n\u003cdiv class=\"snippet-clipboard-content notranslate position-relative overflow-auto\" data-snippet-clipboard-copy-content=\"@misc{clearml,\ntitle = {ClearML - Your entire MLOps stack in one open-source tool},\nyear = {2024},\nnote = {Software available from http://github.com/clearml/clearml},\nurl={https://clear.ml/},\nauthor = {ClearML},\n}\"\u003e\u003cpre class=\"notranslate\"\u003e\u003ccode\u003e@misc{clearml,\ntitle = {ClearML - Your entire MLOps stack in one open-source tool},\nyear = {2024},\nnote = {Software available from http://github.com/clearml/clearml},\nurl={https://clear.ml/},\nauthor = {ClearML},\n}\n\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eDocumentation, Community \u0026amp; Support\u003c/h2\u003e\u003ca id=\"user-content-documentation-community--support\" class=\"anchor\" aria-label=\"Permalink: Documentation, Community \u0026amp; Support\" href=\"#documentation-community--support\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eFor more information, see the \u003ca href=\"https://clear.ml/docs\" rel=\"nofollow\"\u003eofficial documentation\u003c/a\u003e and \u003ca href=\"https://www.youtube.com/c/ClearML\" rel=\"nofollow\"\u003eon YouTube\u003c/a\u003e.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eFor examples and use cases, check the \u003ca href=\"https://github.com/clearml/clearml/tree/master/examples\"\u003eexamples folder\u003c/a\u003e and \u003ca href=\"https://clear.ml/docs/latest/docs/guides\" rel=\"nofollow\"\u003ecorresponding documentation\u003c/a\u003e.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eIf you have any questions: post on our \u003ca href=\"https://joinslack.clear.ml\" rel=\"nofollow\"\u003eSlack Channel\u003c/a\u003e, or tag your questions on \u003ca href=\"https://stackoverflow.com/questions/tagged/clearml\" rel=\"nofollow\"\u003estackoverflow\u003c/a\u003e with '\u003cstrong\u003e\u003ca href=\"https://stackoverflow.com/questions/tagged/clearml\" rel=\"nofollow\"\u003eclearml\u003c/a\u003e\u003c/strong\u003e' tag (\u003cem\u003epreviously \u003ca href=\"https://stackoverflow.com/questions/tagged/trains\" rel=\"nofollow\"\u003etrains\u003c/a\u003e tag\u003c/em\u003e).\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eFor feature requests or bug reports, please use \u003ca href=\"https://github.com/clearml/clearml/issues\"\u003eGitHub issues\u003c/a\u003e.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eAdditionally, you can always find us at \u003cem\u003e\u003ca href=\"mailto:info@clear.ml\"\u003einfo@clear.ml\u003c/a\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eContributing\u003c/h2\u003e\u003ca id=\"user-content-contributing\" class=\"anchor\" aria-label=\"Permalink: Contributing\" href=\"#contributing\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003ePRs are always welcome\u003c/strong\u003e ❤️ See more details in the ClearML \u003ca href=\"https://github.com/clearml/clearml/blob/master/docs/contributing.md\"\u003eGuidelines for Contributing\u003c/a\u003e.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cem\u003eMay the force (and the goddess of learning rates) be with 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dir="auto"><code>🌟 ClearML is open-source - Leave a star to support the project! 🌟</code></p> </div> <hr> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">ClearML</h3><a id="user-content-clearml" class="anchor" aria-label="Permalink: ClearML" href="#clearml"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">ClearML is a ML/DL development and production suite. It contains FIVE main modules:</p> <ul dir="auto"> <li><a href="#clearml-experiment-manager">Experiment Manager</a> - Automagical experiment tracking, environments and results</li> <li><a href="https://github.com/clearml/clearml-agent">MLOps / LLMOps</a> - Orchestration, Automation & Pipelines solution for ML/DL/GenAI jobs (Kubernetes / Cloud / bare-metal)</li> <li><a href="https://github.com/clearml/clearml/blob/master/docs/datasets.md">Data-Management</a> - Fully differentiable data management & version control solution on top of object-storage (S3 / GS / Azure / NAS)</li> <li><a href="https://github.com/clearml/clearml-serving">Model-Serving</a> - <em>cloud-ready</em> Scalable model serving solution! <ul dir="auto"> <li><strong>Deploy new model endpoints in under 5 minutes</strong></li> <li>Includes optimized GPU serving support backed by Nvidia-Triton</li> <li><strong>with out-of-the-box Model Monitoring</strong></li> </ul> </li> <li><a href="https://clear.ml/docs/latest/docs/webapp/webapp_reports" rel="nofollow">Reports</a> - Create and share rich MarkDown documents supporting embeddable online content</li> <li>🔥 <a href="https://clear.ml/docs/latest/docs/webapp/webapp_orchestration_dash/" rel="nofollow">Orchestration Dashboard</a> - Live rich dashboard for your entire compute cluster (Cloud / Kubernetes / On-Prem)</li> <li><strong>NEW</strong> 💥 <a href="https://github.com/clearml/clearml-fractional-gpu">Fractional GPUs</a> - Container based, driver level GPU memory limitation 🙀 !!!</li> </ul> <p dir="auto">Instrumenting these components is the <strong>ClearML-server</strong>, see <a href="https://clear.ml/docs/latest/docs/deploying_clearml/clearml_server" rel="nofollow">Self-Hosting</a> & <a href="https://app.clear.ml" rel="nofollow">Free tier Hosting</a></p> <hr> <div align="center" dir="auto"> <p dir="auto"><strong><a href="https://app.clear.ml" rel="nofollow">Sign up</a> & <a href="https://clear.ml/docs/" rel="nofollow">Start using</a> in under 2 minutes</strong></p> <hr> <p dir="auto"><strong>Friendly tutorials to get you started</strong></p> <markdown-accessiblity-table><table> <tbody> <tr> <td><a href="https://github.com/clearml/clearml/blob/master/docs/tutorials/Getting_Started_1_Experiment_Management.ipynb"><b>Step 1</b></a> - Experiment Management</td> <td><a href="https://colab.research.google.com/github/clearml/clearml/blob/master/docs/tutorials/Getting_Started_1_Experiment_Management.ipynb" rel="nofollow"> <img src="https://camo.githubusercontent.com/96889048f8a9014fdeba2a891f97150c6aac6e723f5190236b10215a97ed41f3/68747470733a2f2f636f6c61622e72657365617263682e676f6f676c652e636f6d2f6173736574732f636f6c61622d62616467652e737667" alt="Open In Colab" data-canonical-src="https://colab.research.google.com/assets/colab-badge.svg" style="max-width: 100%;"> </a></td> </tr> <tr> <td><a href="https://github.com/clearml/clearml/blob/master/docs/tutorials/Getting_Started_2_Setting_Up_Agent.ipynb"><b>Step 2</b></a> - Remote Execution Agent Setup</td> <td><a href="https://colab.research.google.com/github/clearml/clearml/blob/master/docs/tutorials/Getting_Started_2_Setting_Up_Agent.ipynb" rel="nofollow"> <img src="https://camo.githubusercontent.com/96889048f8a9014fdeba2a891f97150c6aac6e723f5190236b10215a97ed41f3/68747470733a2f2f636f6c61622e72657365617263682e676f6f676c652e636f6d2f6173736574732f636f6c61622d62616467652e737667" alt="Open In Colab" data-canonical-src="https://colab.research.google.com/assets/colab-badge.svg" style="max-width: 100%;"> </a></td> </tr> <tr> <td><a href="https://github.com/clearml/clearml/blob/master/docs/tutorials/Getting_Started_3_Remote_Execution.ipynb"><b>Step 3</b></a> - Remotely Execute Tasks</td> <td><a href="https://colab.research.google.com/github/clearml/clearml/blob/master/docs/tutorials/Getting_Started_3_Remote_Execution.ipynb" rel="nofollow"> <img src="https://camo.githubusercontent.com/96889048f8a9014fdeba2a891f97150c6aac6e723f5190236b10215a97ed41f3/68747470733a2f2f636f6c61622e72657365617263682e676f6f676c652e636f6d2f6173736574732f636f6c61622d62616467652e737667" alt="Open In Colab" data-canonical-src="https://colab.research.google.com/assets/colab-badge.svg" style="max-width: 100%;"> </a></td> </tr> </tbody> </table></markdown-accessiblity-table> </div> <hr> <markdown-accessiblity-table><table> <tbody> <tr> <td>Experiment Management</td> <td>Datasets</td> </tr> <tr> <td><a href="https://app.clear.ml" rel="nofollow"><img src="https://github.com/clearml/clearml/raw/master/docs/experiment_manager.gif?raw=true" width="100%" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://app.clear.ml/datasets" rel="nofollow"><img src="https://github.com/clearml/clearml/raw/master/docs/datasets.gif?raw=true" width="100%" data-animated-image="" style="max-width: 100%;"></a></td> </tr> <tr> <td colspan="2" height="24px"></td> </tr> <tr> <td>Orchestration</td> <td>Pipelines</td> </tr> <tr> <td><a href="https://app.clear.ml/workers-and-queues/autoscalers" rel="nofollow"><img src="https://github.com/clearml/clearml/raw/master/docs/orchestration.gif?raw=true" width="100%" data-animated-image="" style="max-width: 100%;"></a></td> <td><a href="https://app.clear.ml/pipelines" rel="nofollow"><img src="https://github.com/clearml/clearml/raw/master/docs/pipelines.gif?raw=true" width="100%" data-animated-image="" style="max-width: 100%;"></a></td> </tr> </tbody> </table></markdown-accessiblity-table> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">ClearML Experiment Manager</h2><a id="user-content-clearml-experiment-manager" class="anchor" aria-label="Permalink: ClearML Experiment Manager" href="#clearml-experiment-manager"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto"><strong>Adding only 2 lines to your code gets you the following</strong></p> <ul dir="auto"> <li>Complete experiment setup log <ul dir="auto"> <li>Full source control info, including non-committed local changes</li> <li>Execution environment (including specific packages & versions)</li> <li>Hyper-parameters <ul dir="auto"> <li><a href="https://docs.python.org/3/library/argparse.html" rel="nofollow"><code>argparse</code></a>/<a href="https://github.com/pallets/click/">Click</a>/<a href="https://github.com/google/python-fire">PythonFire</a> for command line parameters with currently used values</li> <li>Explicit parameters dictionary</li> <li>Tensorflow Defines (absl-py)</li> <li><a href="https://github.com/facebookresearch/hydra">Hydra</a> configuration and overrides</li> </ul> </li> <li>Initial model weights file</li> </ul> </li> <li>Full experiment output automatic capture <ul dir="auto"> <li>stdout and stderr</li> <li>Resource Monitoring (CPU/GPU utilization, temperature, IO, network, etc.)</li> <li>Model snapshots (With optional automatic upload to central storage: Shared folder, S3, GS, Azure, Http)</li> <li>Artifacts log & store (Shared folder, S3, GS, Azure, Http)</li> <li>Tensorboard/<a href="https://github.com/clearml/clearml/tree/master/examples/frameworks/tensorboardx">TensorboardX</a> scalars, metrics, histograms, <strong>images, audio and video samples</strong></li> <li><a href="https://github.com/clearml/clearml/tree/master/examples/frameworks/matplotlib">Matplotlib & Seaborn</a></li> <li><a href="https://clear.ml/docs/latest/docs/fundamentals/logger" rel="nofollow">ClearML Logger</a> interface for complete flexibility.</li> </ul> </li> <li>Extensive platform support and integrations <ul dir="auto"> <li>Supported ML/DL frameworks: <a href="https://github.com/clearml/clearml/tree/master/examples/frameworks/pytorch">PyTorch</a> (incl' <a href="https://github.com/clearml/clearml/tree/master/examples/frameworks/ignite">ignite</a> / <a href="https://github.com/clearml/clearml/tree/master/examples/frameworks/pytorch-lightning">lightning</a>), <a href="https://github.com/clearml/clearml/tree/master/examples/frameworks/tensorflow">Tensorflow</a>, <a href="https://github.com/clearml/clearml/tree/master/examples/frameworks/keras">Keras</a>, <a href="https://github.com/clearml/clearml/tree/master/examples/frameworks/autokeras">AutoKeras</a>, <a href="https://github.com/clearml/clearml/tree/master/examples/frameworks/fastai">FastAI</a>, <a href="https://github.com/clearml/clearml/tree/master/examples/frameworks/xgboost">XGBoost</a>, <a href="https://github.com/clearml/clearml/tree/master/examples/frameworks/lightgbm">LightGBM</a>, <a href="https://github.com/clearml/clearml/tree/master/examples/frameworks/megengine">MegEngine</a> and <a href="https://github.com/clearml/clearml/tree/master/examples/frameworks/scikit-learn">Scikit-Learn</a></li> <li>Seamless integration (including version control) with <a href="https://jupyter.org/" rel="nofollow"><strong>Jupyter Notebook</strong></a> and <a href="https://github.com/clearml/trains-pycharm-plugin"><em>PyCharm</em> remote debugging</a></li> </ul> </li> </ul> <div class="markdown-heading" dir="auto"><h4 tabindex="-1" class="heading-element" dir="auto"><a href="https://clear.ml/docs/latest/docs/getting_started/ds/ds_first_steps" rel="nofollow">Start using ClearML</a></h4><a id="user-content-start-using-clearml" class="anchor" aria-label="Permalink: Start using ClearML" href="#start-using-clearml"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <ol dir="auto"> <li> <p dir="auto">Sign up for free to the <a href="https://app.clear.ml" rel="nofollow">ClearML Hosted Service</a> (alternatively, you can set up your own server, see <a href="https://clear.ml/docs/latest/docs/deploying_clearml/clearml_server" rel="nofollow">here</a>).</p> <blockquote> <p dir="auto"><strong><em>ClearML Demo Server:</em></strong> ClearML no longer uses the demo server by default. To enable the demo server, set the <code>CLEARML_NO_DEFAULT_SERVER=0</code> environment variable. Credentials aren't needed, but experiments launched to the demo server are public, so make sure not to launch sensitive experiments if using the demo server.</p> </blockquote> </li> <li> <p dir="auto">Install the <code>clearml</code> python package:</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="pip install clearml"><pre>pip install clearml</pre></div> </li> <li> <p dir="auto">Connect the ClearML SDK to the server by <a href="https://app.clear.ml/settings/workspace-configuration" rel="nofollow">creating credentials</a>, then execute the command below and follow the instructions:</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="clearml-init"><pre>clearml-init</pre></div> </li> <li> <p dir="auto">Add two lines to your code:</p> <div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="from clearml import Task task = Task.init(project_name='examples', task_name='hello world')"><pre><span class="pl-k">from</span> <span class="pl-s1">clearml</span> <span class="pl-k">import</span> <span class="pl-v">Task</span> <span class="pl-s1">task</span> <span class="pl-c1">=</span> <span class="pl-v">Task</span>.<span class="pl-c1">init</span>(<span class="pl-s1">project_name</span><span class="pl-c1">=</span><span class="pl-s">'examples'</span>, <span class="pl-s1">task_name</span><span class="pl-c1">=</span><span class="pl-s">'hello world'</span>)</pre></div> </li> </ol> <p dir="auto">And you are done! Everything your process outputs is now automagically logged into ClearML.</p> <p dir="auto">Next step, automation! <strong>Learn more about ClearML's two-click automation <a href="https://clear.ml/docs/latest/docs/getting_started/mlops/mlops_first_steps" rel="nofollow">here</a></strong>.</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">ClearML Architecture</h2><a id="user-content-clearml-architecture" class="anchor" aria-label="Permalink: ClearML Architecture" href="#clearml-architecture"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">The ClearML run-time components:</p> <ul dir="auto"> <li>The ClearML Python Package - for integrating ClearML into your existing scripts by adding just two lines of code, and optionally extending your experiments and other workflows with ClearML's powerful and versatile set of classes and methods.</li> <li>The ClearML Server - for storing experiment, model, and workflow data; supporting the Web UI experiment manager and MLOps automation for reproducibility and tuning. It is available as a hosted service and open source for you to deploy your own ClearML Server.</li> <li>The ClearML Agent - for MLOps orchestration, experiment and workflow reproducibility, and scalability.</li> </ul> <p dir="auto"><a target="_blank" rel="noopener noreferrer nofollow" href="https://raw.githubusercontent.com/clearml/clearml-docs/main/docs/img/clearml_architecture.png"><img src="https://raw.githubusercontent.com/clearml/clearml-docs/main/docs/img/clearml_architecture.png" width="100%" alt="clearml-architecture" style="max-width: 100%;"></a></p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Additional Modules</h2><a id="user-content-additional-modules" class="anchor" aria-label="Permalink: Additional Modules" href="#additional-modules"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <ul dir="auto"> <li><a href="https://github.com/clearml/clearml-session">clearml-session</a> - <strong>Launch remote JupyterLab / VSCode-server inside any docker, on Cloud/On-Prem machines</strong></li> <li><a href="https://github.com/clearml/clearml/blob/master/docs/clearml-task.md">clearml-task</a> - Run any codebase on remote machines with full remote logging of Tensorboard, Matplotlib & Console outputs</li> <li><a href="https://github.com/clearml/clearml/blob/master/docs/datasets.md">clearml-data</a> - <strong>CLI for managing and versioning your datasets, including creating / uploading / downloading of data from S3/GS/Azure/NAS</strong></li> <li><a href="https://clear.ml/docs/latest/docs/guides/services/aws_autoscaler" rel="nofollow">AWS Auto-Scaler</a> - Automatically spin EC2 instances based on your workloads with preconfigured budget! No need for AKE!</li> <li><a href="https://clear.ml/docs/latest/docs/guides/optimization/hyper-parameter-optimization/examples_hyperparam_opt" rel="nofollow">Hyper-Parameter Optimization</a> - Optimize any code with black-box approach and state-of-the-art Bayesian optimization algorithms</li> <li><a href="https://clear.ml/docs/latest/docs/guides/pipeline/pipeline_controller" rel="nofollow">Automation Pipeline</a> - Build pipelines based on existing experiments / jobs, supports building pipelines of pipelines!</li> <li><a href="https://clear.ml/docs/latest/docs/guides/services/slack_alerts" rel="nofollow">Slack Integration</a> - Report experiments progress / failure directly to Slack (fully customizable!)</li> </ul> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Why ClearML?</h2><a id="user-content-why-clearml" class="anchor" aria-label="Permalink: Why ClearML?" href="#why-clearml"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">ClearML is our solution to a problem we share with countless other researchers and developers in the machine learning/deep learning universe: Training production-grade deep learning models is a glorious but messy process. ClearML tracks and controls the process by associating code version control, research projects, performance metrics, and model provenance.</p> <p dir="auto">We designed ClearML specifically to require effortless integration so that teams can preserve their existing methods and practices.</p> <ul dir="auto"> <li>Use it on a daily basis to boost collaboration and visibility in your team</li> <li>Create a remote job from any experiment with a click of a button</li> <li>Automate processes and create pipelines to collect your experimentation logs, outputs, and data</li> <li>Store all your data on any object-storage solution, with the most straightforward interface possible</li> <li>Make your data transparent by cataloging it all on the ClearML platform</li> </ul> <p dir="auto">We believe ClearML is ground-breaking. We wish to establish new standards of true seamless integration between experiment management, MLOps, and data management.</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Who We Are</h2><a id="user-content-who-we-are" class="anchor" aria-label="Permalink: Who We Are" href="#who-we-are"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">ClearML is supported by you and the <a href="https://clear.ml" rel="nofollow">clear.ml</a> team, which helps enterprise companies build scalable MLOps.</p> <p dir="auto">We built ClearML to track and control the glorious but messy process of training production-grade deep learning models. We are committed to vigorously supporting and expanding the capabilities of ClearML.</p> <p dir="auto">We promise to always be backwardly compatible, making sure all your logs, data, and pipelines will always upgrade with you.</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">License</h2><a id="user-content-license" class="anchor" aria-label="Permalink: License" href="#license"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Apache License, Version 2.0 (see the <a href="https://www.apache.org/licenses/LICENSE-2.0.html" rel="nofollow">LICENSE</a> for more information)</p> <p dir="auto">If ClearML is part of your development process / project / publication, please cite us ❤️ :</p> <div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="@misc{clearml, title = {ClearML - Your entire MLOps stack in one open-source tool}, year = {2024}, note = {Software available from http://github.com/clearml/clearml}, url={https://clear.ml/}, author = {ClearML}, }"><pre class="notranslate"><code>@misc{clearml, title = {ClearML - Your entire MLOps stack in one open-source tool}, year = {2024}, note = {Software available from http://github.com/clearml/clearml}, url={https://clear.ml/}, author = {ClearML}, } </code></pre></div> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Documentation, Community & Support</h2><a id="user-content-documentation-community--support" class="anchor" aria-label="Permalink: Documentation, Community & Support" href="#documentation-community--support"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">For more information, see the <a href="https://clear.ml/docs" rel="nofollow">official documentation</a> and <a href="https://www.youtube.com/c/ClearML" rel="nofollow">on YouTube</a>.</p> <p dir="auto">For examples and use cases, check the <a href="https://github.com/clearml/clearml/tree/master/examples">examples folder</a> and <a href="https://clear.ml/docs/latest/docs/guides" rel="nofollow">corresponding documentation</a>.</p> <p dir="auto">If you have any questions: post on our <a href="https://joinslack.clear.ml" rel="nofollow">Slack Channel</a>, or tag your questions on <a href="https://stackoverflow.com/questions/tagged/clearml" rel="nofollow">stackoverflow</a> with '<strong><a href="https://stackoverflow.com/questions/tagged/clearml" rel="nofollow">clearml</a></strong>' tag (<em>previously <a href="https://stackoverflow.com/questions/tagged/trains" rel="nofollow">trains</a> tag</em>).</p> <p dir="auto">For feature requests or bug reports, please use <a href="https://github.com/clearml/clearml/issues">GitHub issues</a>.</p> <p dir="auto">Additionally, you can always find us at <em><a href="mailto:info@clear.ml">info@clear.ml</a></em></p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Contributing</h2><a id="user-content-contributing" class="anchor" aria-label="Permalink: Contributing" href="#contributing"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto"><strong>PRs are always welcome</strong> ❤️ See more details in the ClearML <a href="https://github.com/clearml/clearml/blob/master/docs/contributing.md">Guidelines for Contributing</a>.</p> <p dir="auto"><em>May the force (and the goddess of learning rates) be with you!</em></p> </article></div></div></div></div></div>   <script type="application/json" id="__PRIMER_DATA_:R0:__">{"resolvedServerColorMode":"day"}</script></div> </react-partial> <input type="hidden" data-csrf="true" value="qkk3/qg2Tg/i042wNeMGHACoIVuP8HZiNESd86r6p4/tkQr7Tk/jkXrFnpQ9VnfBGvbOVqt5vTu+wLIbbp4HZA==" /> </div> <div data-view-component="true" class="Layout-sidebar"> <div class="BorderGrid about-margin" data-pjax> <div class="BorderGrid-row"> <div class="BorderGrid-cell"> <div class="hide-sm hide-md"> <h2 class="mb-3 h4">About</h2> <p class="f4 my-3"> ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution </p> <div class="my-3 d-flex flex-items-center"> <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-link flex-shrink-0 mr-2"> <path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path> </svg> <span class="flex-auto min-width-0 css-truncate css-truncate-target width-fit"> <a title="https://clear.ml/docs" role="link" target="_blank" rel="noopener noreferrer nofollow" class="text-bold" href="https://clear.ml/docs">clear.ml/docs</a> </span> </div> <h3 class="sr-only">Topics</h3> <div class="my-3"> <div class="f6"> <a href="/topics/experiment" title="Topic: experiment" data-view-component="true" class="topic-tag topic-tag-link"> experiment </a> <a href="/topics/devops" title="Topic: devops" data-view-component="true" class="topic-tag topic-tag-link"> devops </a> <a href="/topics/machine-learning" title="Topic: machine-learning" data-view-component="true" class="topic-tag topic-tag-link"> machine-learning </a> <a href="/topics/control" title="Topic: control" data-view-component="true" class="topic-tag topic-tag-link"> control </a> <a href="/topics/ai" title="Topic: ai" data-view-component="true" class="topic-tag topic-tag-link"> ai </a> <a href="/topics/deep-learning" title="Topic: deep-learning" data-view-component="true" class="topic-tag topic-tag-link"> deep-learning </a> <a 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1.124-.967 1.954-2.096 2.366-2.717a.12.12 0 0 0 0-.136c-.412-.621-1.242-1.75-2.366-2.717C10.824 4.242 9.473 3.5 8 3.5c-1.473 0-2.825.742-3.955 1.715-1.124.967-1.954 2.096-2.366 2.717ZM8 10a2 2 0 1 1-.001-3.999A2 2 0 0 1 8 10Z"></path> </svg> <strong>95</strong> watching</a> </div> <h3 class="sr-only">Forks</h3> <div class="mt-2"> <a href="/clearml/clearml/forks" data-view-component="true" class="Link Link--muted"><svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-repo-forked mr-2"> <path d="M5 5.372v.878c0 .414.336.75.75.75h4.5a.75.75 0 0 0 .75-.75v-.878a2.25 2.25 0 1 1 1.5 0v.878a2.25 2.25 0 0 1-2.25 2.25h-1.5v2.128a2.251 2.251 0 1 1-1.5 0V8.5h-1.5A2.25 2.25 0 0 1 3.5 6.25v-.878a2.25 2.25 0 1 1 1.5 0ZM5 3.25a.75.75 0 1 0-1.5 0 .75.75 0 0 0 1.5 0Zm6.75.75a.75.75 0 1 0 0-1.5.75.75 0 0 0 0 1.5Zm-3 8.75a.75.75 0 1 0-1.5 0 .75.75 0 0 0 1.5 0Z"></path> </svg> <strong>671</strong> forks</a> </div> <div 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