... | ... | @@ -49,8 +49,6 @@ To **delete** one ore more sessions just select the sessions in the list and pre |
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This will actually **delete the directories** of the sessions with all created snapshots and log files.
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## Console
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The console is the main output of barista. There are different callers that register to the console and can display custom messages and errors that the user should know about. E.g. sessions write the caffe output here, the input manger would write errors if the data is faulty and other barista modules would complain about errors.
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The messages are not filtered at the beginning. They can be filtered by their type "Text" or "Error" and also by their caller. If there is no filter every line has a prefix to identify the line it has the format: ¸`[HH:MM:ss, Caller] Sometext`
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![console](/uploads/244e74a4c57428cbb88dcf3449e065e1/console.png)
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... | ... | @@ -60,6 +58,12 @@ The plotter is the main tool to visualize the feedback given by caffe. The caffe |
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![plotter](/uploads/909b990e46bc8806c89821d2837c8e99/plotter.png)
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In the settings panel there is a list of all training sessions or loaded log files. Every session/log has a corresponding set of plotable keys represented as check boxes contained in the right area. Each key is associated to the TRAIN or TEST phase.
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In the settings panel there is a list of all training sessions or loaded log files. Every session/log has a corresponding set of plotable keys represented as check boxes contained in the right area. Each key is associated to the TRAIN or TEST phase. If a check box is checked a plot line with the name 'logname.phase.key' is added to the plotter.
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![plotter_settings](/uploads/faf0726ebe2aaaf4c32e3204bf53212a/plotter_settings.png) |
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![plotter_settings](/uploads/faf0726ebe2aaaf4c32e3204bf53212a/plotter_settings.png)
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The list of sessions or log files can be extended by starting a new session or opening an existing log file via the open button. Because the logs, phases and keys can be chosen separately the trainings can be easily compared and analysed.
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For instance one can compare the loss-rate to the learning-rate of a training to observe how the learning-rate influences the loss-rate. This can help to optimize the choice of the learning-rate parameters.
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Furthermore the user can choose how to plot the data (linear, logarithmic) and to plot it against the time or the number of iterations. Both options can be set in the settings panel. |
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