- 【CVAT】How to create multiple jobs in one task?
- How to increase accuracy of model using catboost
- How to implement a skip-connection structure between LSTM layers
- How to fix : module 'tensorflow' has no attribute 'Session'
- How to test one single image in pytorch
- Plotly: How to make an annotated confusion matrix using a heatmap?
- How to get the Weight of Evidence (WOE) and Information Value (IV) in Python/pandas?
- How to save weights of keras model for each epoch?
- How to avoid reloading ML model every time when I call python script?
- How to split data based on a column value in sklearn
- How to use sklearn ( chi-square or ANOVA) to removes redundant features
- How to graph centroids with KMeans
- How to solve ' CUDA out of memory. Tried to allocate xxx MiB' in pytorch?
- How to calculate TPR and FPR in Python without using sklearn?
- How to create a custom PreprocessingLayer in TF 2.2
- Python: How to retrive the best model from Optuna LightGBM study?
- How to predownload a transformers model
- How to reset Keras metrics?
- How to handle missing values (NaN) in categorical data when using scikit-learn OneHotEncoder?
- How to get probabilities along with classification in LogisticRegression?
How to safely shutdown mlflow ui?
Written by- Aionlinecourse3881 times views
To safely shutdown the MLflow UI, you can use the mlflow server stop
command. This command will stop the MLflow server and terminate the web
server process.
Here's the general syntax for the command:
The --server-id option allows you to specify a unique identifier for the server instance. This can be useful if you are running multiple instances of the MLflow server on the same machine.
For example, to stop the MLflow server running on the default host and port, you can run the following command:
Here's the general syntax for the command:
mlflow server stop [--host HOST] [--port PORT] [--server-id SERVER_ID]The --host and --port options allow you to specify the host and port on which the MLflow server is running. If you are running the MLflow server on the default host and port (localhost:5000), you can omit these options.
The --server-id option allows you to specify a unique identifier for the server instance. This can be useful if you are running multiple instances of the MLflow server on the same machine.
For example, to stop the MLflow server running on the default host and port, you can run the following command:
mlflow server stopThis will shut down the MLflow server and terminate the web server process.