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https://github.com/clearml/clearml
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68 lines
2.0 KiB
Python
68 lines
2.0 KiB
Python
# ClearML - Example of manual graphs and statistics reporting
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#
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import pandas as pd
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from clearml import Task, Logger
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def report_table(logger, iteration=0):
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# type: (Logger, int) -> ()
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"""
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reporting tables to the 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 tables
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# Report table - DataFrame with index
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df = pd.DataFrame(
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{
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"num_legs": [2, 4, 8, 0],
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"num_wings": [2, 0, 0, 0],
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"num_specimen_seen": [10, 2, 1, 8],
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},
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index=["falcon", "dog", "spider", "fish"],
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)
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df.index.name = "id"
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logger.report_table("table pd", "PD with index", iteration=iteration, table_plot=df)
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# Report table - CSV from path
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csv_url = "https://raw.githubusercontent.com/plotly/datasets/master/Mining-BTC-180.csv"
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logger.report_table("table - csv", "remote csv", iteration=iteration, url=csv_url)
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# Report table - Created with list of lists
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logger.report_table("table - list of lists",
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"List of lists",
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iteration=iteration,
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table_plot=[
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["Last Name", "First Name", "Age"],
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["Doe", "John", "25"],
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["Smith", "Peter", "30"],
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])
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def main():
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# Create the experiment Task
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task = Task.init(project_name="examples", task_name="table reporting")
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print('reporting pandas tables and python lists as tables into the plots section')
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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_table(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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