mlflow--mlflow
wehub-resource-sync
41 行
1.2 KiB
Python
41 行
1.2 KiB
Python
from pprint import pprint
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import pandas as pd
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from sklearn import datasets, svm
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from sklearn.model_selection import GridSearchCV
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from utils import fetch_logged_data
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import mlflow
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def main():
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mlflow.sklearn.autolog()
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iris = datasets.load_iris()
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parameters = {"kernel": ("linear", "rbf"), "C": [1, 10]}
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svc = svm.SVC()
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clf = GridSearchCV(svc, parameters)
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clf.fit(iris.data, iris.target)
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run_id = mlflow.last_active_run().info.run_id
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# show data logged in the parent run
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print("========== parent run ==========")
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for key, data in fetch_logged_data(run_id).items():
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print(f"\n---------- logged {key} ----------")
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pprint(data)
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# show data logged in the child runs
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filter_child_runs = f"tags.mlflow.parentRunId = '{run_id}'"
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runs = mlflow.search_runs(filter_string=filter_child_runs)
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param_cols = [f"params.{p}" for p in parameters.keys()]
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metric_cols = ["metrics.mean_test_score"]
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print("\n========== child runs ==========\n")
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pd.set_option("display.max_columns", None) # prevent truncating columns
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print(runs[["run_id", *param_cols, *metric_cols]])
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if __name__ == "__main__":
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main()
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