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the clearml experiment manager integrates with a number of libraries and Frameworks that are very popular in the machine learning field for example after adding the magic two lines of code plots made by modbot leap or Seaborn will automatically be added to the plot section in the task without you having to add any extra code in the same way any scalars reported to tensorboard will be added to the scalars tab and even command line arguments are automatically detected and parsed as hyper parameters in the task but what if the automatic logging does too much letamp;#39;s say youamp;#39;re training a model with pytorch and saving a checkpoint every iteration the automated tracking will detect this and upload every single one which might not be what you wanted foreign automated pytorch tracking by setting the autoconnect Frameworks argument when initializing the task each integration can be enabled or disabled individually and in the case of pytorch and tensorflow you can even spe
