mirror of
https://github.com/clearml/clearml
synced 2025-01-31 17:17:00 +00:00
51 lines
1.7 KiB
Python
51 lines
1.7 KiB
Python
# ClearML - Example of manual graphs and statistics reporting
|
|
#
|
|
from clearml import Task, Logger
|
|
|
|
|
|
def report_scalars(logger):
|
|
# type: (Logger) -> ()
|
|
"""
|
|
reporting scalars to scalars section
|
|
:param logger: The task.logger to use for sending the scalars
|
|
"""
|
|
# report two scalar series on the same graph
|
|
for i in range(100):
|
|
logger.report_scalar(title="unified graph", series="series A", iteration=i, value=1. / (i + 1))
|
|
logger.report_scalar(title="unified graph", series="series B", iteration=i, value=10. / (i + 1))
|
|
|
|
# report two scalar series on two different graphs
|
|
for i in range(100):
|
|
logger.report_scalar(title="graph A", series="series A", iteration=i, value=1. / (i + 1))
|
|
logger.report_scalar(title="graph B", series="series B", iteration=i, value=10. / (i + 1))
|
|
|
|
# report single scalars
|
|
logger.report_single_value(name="metric A", value=486)
|
|
logger.report_single_value(name="metric B", value=305.95)
|
|
|
|
|
|
def main():
|
|
# Connecting ClearML with the current process,
|
|
# from here on everything is logged automatically
|
|
task = Task.init(project_name="examples", task_name="Scalar reporting")
|
|
|
|
print('reporting scalar graphs')
|
|
|
|
# Get the task logger,
|
|
# You can also call Task.current_task().get_logger() from anywhere in your code.
|
|
logger = task.get_logger()
|
|
|
|
# report scalars
|
|
report_scalars(logger)
|
|
|
|
# force flush reports
|
|
# If flush is not called, reports are flushed in the background every couple of seconds,
|
|
# and at the end of the process execution
|
|
logger.flush()
|
|
|
|
print('We are done reporting, have a great day :)')
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|