whylogs.mlflow
¶
Submodules¶
Package Contents¶
Functions¶
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Enable whylogs in |
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List all the runs from an experiment that contains whylogs |
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Retrieve all whylogs DatasetProfile for a given run and a given dataset name. |
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Retrieve all whylogs profiles for a given experiment. This only |
- whylogs.mlflow.disable_mlflow()¶
- whylogs.mlflow.enable_mlflow(session=None) bool ¶
Enable whylogs in
mlflow
module viamlflow.whylogs
.- Returns
True if MLFlow has been patched. False otherwise.
import mlflow import whylogs whylogs.enable_mlflow() import numpy as np import pandas as pd pdf = pd.DataFrame( data=[[1, 2, 3, 4, True, "x", bytes([1])]], columns=["b", "d", "a", "c", "e", "g", "f"], dtype=np.object, ) active_run = mlflow.start_run() # log a Pandas dataframe under default name mlflow.whylogs.log_pandas(pdf) # log a Pandas dataframe with custom name mlflow.whylogs.log_pandas(pdf, "another dataset") # Finish the MLFlow run mlflow.end_run()
- whylogs.mlflow.list_whylogs_runs(experiment_id: str, dataset_name: str = 'default')¶
List all the runs from an experiment that contains whylogs
- Return type
typing.List[mlflow.entities.Run]
- Parameters
experiment_id – the experiment id
dataset_name – the name of the dataset. Default to “default”
- whylogs.mlflow.get_run_profiles(run_id: str, dataset_name: str = 'default', client=None)¶
Retrieve all whylogs DatasetProfile for a given run and a given dataset name.
- Parameters
client –
mlflow.tracking.MlflowClient
run_id – the run id
dataset_name – the dataset name within a run. If not set, use the default value “default”
- Return type
typing.List[whylogs.DatasetProfile]
- whylogs.mlflow.get_experiment_profiles(experiment_id: str, dataset_name: str = 'default')¶
Retrieve all whylogs profiles for a given experiment. This only returns Active Runs at the moment.
- Return type
typing.List[whylogs.DatasetProfile]
- Parameters
experiment_id – the experiment ID string
dataset_name – the dataset name within a run. If not set, use the default value “default”