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[tune] Tune experiment analysis improvements (#10645)

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Co-authored-by: Richard Liaw <rliaw@berkeley.edu>
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Kai Fricke
2020-09-08 21:00:52 -07:00
committed by GitHub
co-authored by Richard Liaw
parent d9c68fca5c
commit d7c7aba99c
14 changed files with 247 additions and 38 deletions
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doc/source/tune/api_docs/analysis.rst
+1 -1
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@@ -18,7 +18,7 @@ Here are some example operations for obtaining a summary of your experiment:
.. code-block:: python
# Get a dataframe for the last reported results of all of the trials
df = analysis.dataframe()
df = analysis.results_df
# Get a dataframe for the max accuracy seen for each trial
df = analysis.dataframe(metric="mean_accuracy", mode="max")
doc/source/tune/key-concepts.rst
+11 -3
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@@ -219,16 +219,24 @@ Analysis
analysis = tune.run(trainable, search_alg=algo, stop={"training_iteration": 20})
# Get the best hyperparameters
best_hyperparameters = analysis.get_best_config()
best_trial = analysis.best_trial # Get best trial
best_config = analysis.best_config # Get best trial's hyperparameters
best_logdir = analysis.best_logdir # Get best trial's logdir
best_checkpoint = analysis.best_checkpoint # Get best trial's best checkpoint
best_result = analysis.best_result # Get best trial's last results
best_result_df = analysis.best_result_df # Get best result as pandas dataframe
This object can also retrieve all training runs as dataframes, allowing you to do ad-hoc data analysis over your results.
.. code-block:: python
# Get a dataframe for the max score seen for each trial
# Get a dataframe with the last results for each trial
df_results = analysis.results_df
# Get a dataframe of results for a specific score or mode
df = analysis.dataframe(metric="score", mode="max")
What's Next?
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