Bases: BaseTracker
Tracker object for generic models. Requires a dataset name and model inputs
Source code in sientia_tracker/simple_tracker.py
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36 | class SimpleTracker(BaseTracker):
"""
Tracker object for generic models. Requires a dataset name and model inputs
"""
def __init__(self, tracking_uri, username: str = None, password: str = None):
super().__init__(tracking_uri, username, password)
def save_experiment(self, dataset_name: str = "data", inputs: str | List[str] = "inputs") -> mlflow.ActiveRun:
"""
Start a run in MLflow.
Parameters:
dataset_name: Name of the dataset
inputs: Name of the model inputs
Returns:
active_run: Active run in MLflow
"""
mlflow.end_run()
print("Saving experiment", self.project_name)
runs = mlflow.search_runs(experiment_names=[
self.project_name], order_by=["start_time desc"])
next_run_number = len(runs) + 1
active_run = mlflow.start_run(run_name=f"{self.project_name}-{next_run_number}")
mlflow.log_params({
"Dataset": dataset_name,
"Inputs": inputs,
})
return active_run
|
save_experiment(dataset_name='data', inputs='inputs')
Start a run in MLflow.
| Parameters: |
-
dataset_name
(str, default:
'data'
)
–
-
inputs
(str | List[str], default:
'inputs'
)
–
|
| Returns: |
-
active_run( ActiveRun
) –
|
Source code in sientia_tracker/simple_tracker.py
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36 | def save_experiment(self, dataset_name: str = "data", inputs: str | List[str] = "inputs") -> mlflow.ActiveRun:
"""
Start a run in MLflow.
Parameters:
dataset_name: Name of the dataset
inputs: Name of the model inputs
Returns:
active_run: Active run in MLflow
"""
mlflow.end_run()
print("Saving experiment", self.project_name)
runs = mlflow.search_runs(experiment_names=[
self.project_name], order_by=["start_time desc"])
next_run_number = len(runs) + 1
active_run = mlflow.start_run(run_name=f"{self.project_name}-{next_run_number}")
mlflow.log_params({
"Dataset": dataset_name,
"Inputs": inputs,
})
return active_run
|