name: Bug Report (Use "UI Bug Report" for UI bugs) description: Create a report to help us reproduce and correct the bug labels: "bug" title: "[BUG]" body: - type: markdown attributes: value: | > [!WARNING] > Before submitting a PR, please make sure that: > - A maintainer has triaged this issue and applied the `ready` label > - This issue has no assignee > - No duplicate PR exists > > PRs not meeting these requirements may be automatically closed. - type: markdown attributes: value: | Thank you for submitting an issue. Please refer to our [issue policy](https://www.github.com/mlflow/mlflow/blob/master/ISSUE_POLICY.md) for additional information about bug reports. For help with debugging your code, please refer to [Stack Overflow](https://stackoverflow.com/questions/tagged/mlflow). #### Please fill in this bug report template to ensure a timely and thorough response. - type: checkboxes attributes: label: Issues Policy acknowledgement description: | I understand that failure to adhere to the issues guidance may result in my issue being closed without warning or response. options: - label: I have read and agree to submit bug reports in accordance with the [issues policy](https://www.github.com/mlflow/mlflow/blob/master/ISSUE_POLICY.md) required: true - type: dropdown attributes: label: Where did you encounter this bug? options: - Local machine - Databricks - Azure Machine Learning - Other validations: required: true - type: textarea validations: required: true attributes: label: MLflow version description: MLflow version (run `mlflow --version`) or commit SHA if you have MLflow installed from source (run `pip freeze | grep mlflow`). The tracking server version is required if `mlflow server` is used. value: | - Client: 1.x.y - Tracking server: 1.x.y - type: textarea attributes: label: System information description: | Describe the system where you encountered the bug. value: | - **OS Platform and Distribution (e.g., Linux Ubuntu 16.04)**: - **Python version**: validations: required: true - type: textarea attributes: label: Describe the problem description: | Describe the problem clearly here. Include descriptions of the expected behavior and the actual behavior. validations: required: true - type: textarea attributes: label: Tracking information description: | For bugs related to the tracking features (e.g. mlflow should log a run in my database but it doesn't), please insert the following code in your python script / notebook where you encountered the bug and run it: ```python # MLflow < 2.0 print("MLflow version:", mlflow.__version__) print("Tracking URI:", mlflow.get_tracking_uri()) print("Artifact URI:", mlflow.get_artifact_uri()) # MLflow >= 2.0 mlflow.doctor() ``` Then, make sure the printed out information matches what you expect and paste it (with sensitive information masked) in the box below. If you know the command that was used to launch your tracking server (e.g. `mlflow server -h 0.0.0.0 -p 5000`), please provide it. value: | ```shell REPLACE_ME ``` validations: required: false - type: textarea attributes: label: Code to reproduce issue description: | Provide a reproducible test case that is the bare minimum necessary to generate the problem. ### Bad Requires modifications (e.g., adding missing import statements) to run. ```python with mlflow.start_run(): # `mlflow` is not imported mlflow.sklearn.log_model(model, "model") # `model` is undefined ``` ### Good Does not require any modifications to run. ```python from sklearn.datasets import load_iris from sklearn.linear_model import LogisticRegression import mlflow X, y = load_iris(return_X_y=True) model = LogisticRegression().fit(X, y) with mlflow.start_run(): mlflow.sklearn.log_model(model, "model") ``` value: | ``` REPLACE_ME ``` validations: required: true - type: textarea attributes: label: Stack trace description: | Provide a **full** stack trace. ### Bad ```python TypeError: expected string or bytes-like object ``` ### Good ```python Traceback (most recent call last): File "a.py", line 3, in mlflow.log_param(1, 2) File "/home/user/mlflow/mlflow/tracking/fluent.py", line 541, in log_param return MlflowClient().log_param(run_id, key, value) File "/home/user/mlflow/mlflow/tracking/client.py", line 742, in log_param self._tracking_client.log_param(run_id, key, value) File "/home/user/mlflow/mlflow/tracking/_tracking_service/client.py", line 295, in log_param self.store.log_param(run_id, param) File "/home/user/mlflow/mlflow/store/tracking/file_store.py", line 917, in log_param _validate_param(param.key, param.value) File "/home/user/mlflow/mlflow/utils/validation.py", line 150, in _validate_param _validate_param_name(key) File "/home/user/mlflow/mlflow/utils/validation.py", line 217, in _validate_param_name if not _VALID_PARAM_AND_METRIC_NAMES.match(name): TypeError: expected string or bytes-like object ``` value: | ``` REPLACE_ME ``` validations: required: true - type: textarea attributes: label: Other info / logs description: | Include any logs or source code that would be helpful to diagnose the problem. Large logs and files should be attached. ### Example ``` # Tracking server logs [2022-08-01 16:03:02 +0900] [222636] [INFO] Starting gunicorn 20.1.0 [2022-08-01 16:03:02 +0900] [222636] [INFO] Listening at: http://127.0.0.1:5000 (222636) [2022-08-01 16:03:02 +0900] [222636] [INFO] Using worker: sync [2022-08-01 16:03:02 +0900] [222639] [INFO] Booting worker with pid: 222639 ``` value: | ``` REPLACE_ME ``` validations: required: false - type: checkboxes id: component attributes: label: What component(s) does this bug affect? description: Please choose one or more components below. options: - label: "`area/tracking`: Tracking Service, tracking client APIs, autologging" required: false - label: "`area/model-registry`: Model Registry service, APIs, and the fluent client calls for Model Registry" required: false - label: "`area/scoring`: MLflow model serving, deployment tools, Spark UDFs" required: false - label: "`area/evaluation`: MLflow model evaluation features, evaluation metrics, and evaluation workflows" required: false - label: "`area/prompt`: MLflow prompt engineering features, prompt templates, and prompt management" required: false - label: "`area/tracing`: MLflow Tracing features, tracing APIs, and LLM tracing functionality" required: false - label: "`area/gateway`: MLflow AI Gateway client APIs, server, and third-party integrations" required: false - label: "`area/projects`: MLproject format, project running backends" required: false - label: "`area/uiux`: Front-end, user experience, plotting" required: false - label: "`area/docs`: MLflow documentation pages" required: false