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https://github.com/clearml/clearml
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65 lines
1.6 KiB
Python
65 lines
1.6 KiB
Python
# ClearML - Example of manual graphs and statistics reporting
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#
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import numpy as np
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from clearml import Task, Logger
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def report_plots(logger, iteration=0):
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# type: (Logger, int) -> ()
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"""
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reporting plots to plots section
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:param logger: The task.logger to use for sending the plots
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:param iteration: The iteration number of the current reports
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"""
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# report 3d surface
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surface = np.random.randint(10, size=(10, 10))
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logger.report_surface(
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"example_surface",
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"series1",
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iteration=iteration,
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matrix=surface,
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xaxis="title X",
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yaxis="title Y",
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zaxis="title Z",
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)
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# report 3d scatter plot
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scatter3d = np.random.randint(10, size=(10, 3))
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logger.report_scatter3d(
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"example_scatter_3d",
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"series_xyz",
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iteration=iteration,
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scatter=scatter3d,
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xaxis="title x",
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yaxis="title y",
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zaxis="title z",
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)
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def main():
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# Connecting ClearML with the current process,
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# from here on everything is logged automatically
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task = Task.init(project_name="examples", task_name="3D plot reporting")
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print('reporting 3D plot graphs')
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# Get the task logger,
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# You can also call Task.current_task().get_logger() from anywhere in your code.
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logger = task.get_logger()
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# report graphs
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report_plots(logger)
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# force flush reports
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# If flush is not called, reports are flushed in the background every couple of seconds,
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# and at the end of the process execution
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logger.flush()
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print('We are done reporting, have a great day :)')
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if __name__ == "__main__":
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main()
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