[BUG] Loading Pyfunc artifact from pre- saved model uses Windows path format instead of linux.

[threaddy]

Issues Policy acknowledgement

• I have read and agree to submit bug reports in accordance with the issues policy

Where did you encounter this bug?

Local machine

Willingness to contribute

Yes. I would be willing to contribute a fix for this bug with guidance from the MLflow community.

MLflow version

• mlflow==2.12.1

System information

• Localhost Windows 11
• Docker image python:3.11-slim
• Python 3.11

Describe the problem

I am trying to containerize a Pytorch ML model that is trained and saved locally using a custom wrapper of PythonModel to save some artifacts (scaler, hyperparameters, intermediate predictions)

However, when re-loading the model in the container, the artifact paths are clearly reloaded using a mix of Windows and Linux directory separators. This raises a FileNotFoundError exception.

What is a clean way to fix this behavior? Should I try to save the model differently during training? Or maybe a path fix should be implemented when moving across platforms

Tracking information

System information: Linux #1 SMP Thu Jan 11 04:09:03 UTC 2024
Python version: 3.11.9
MLflow version: 2.12.1
MLflow module location: /usr/local/lib/python3.11/site-packages/mlflow/init.py
Tracking URI: http://localhost:5002
Registry URI: http://localhost:5002
MLflow environment variables:
MLFLOW_HOST: 0.0.0.0
MLFLOW_PORT: 5002
MLFLOW_TRACKING_URI: http://localhost:5002
MLflow dependencies:
Flask: 3.0.3
Jinja2: 3.1.3
alembic: 1.13.1
click: 8.1.7
cloudpickle: 3.0.0
docker: 7.0.0
entrypoints: 0.4
fastapi: 0.110.2
gitpython: 3.1.43
graphene: 3.3
gunicorn: 21.2.0
importlib-metadata: 7.1.0
markdown: 3.6
matplotlib: 3.8.4
numpy: 1.26.3
packaging: 23.2
pandas: 2.2.0
protobuf: 5.26.1
pyarrow: 15.0.2
pydantic: 2.6.4
pytz: 2024.1
pyyaml: 6.0.1
querystring-parser: 1.2.4
requests: 2.31.0
scikit-learn: 1.4.0
scipy: 1.12.0
sqlalchemy: 2.0.27
sqlparse: 0.5.0
uvicorn: 0.29.0

Code to reproduce issue

import mlflow

uri = mlflow.tracking.get_tracking_uri()
client = mlflow.tracking.MlflowClient()

registered_models = client.search_model_versions("")
latest_model_name = registered_models[0].name
latest_model_version = registered_models[0].version

model_uri = f"models:/{latest_model_name}/{latest_model_version}"
model_info = mlflow.models.get_model_info(model_uri)
loaded_model = mlflow.pyfunc.load_model(model_uri)

Stack trace

Traceback (most recent call last):
  File "/app/app_main.py", line 30, in <module>
    loaded_model = mlflow.pyfunc.load_model(model_uri)
  File "/usr/local/lib/python3.11/site-packages/mlflow/pyfunc/model.py", line 468, in _load_pyfunc
    context, python_model, signature = _load_context_model_and_signature(model_path, model_config)
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/mlflow/pyfunc/model.py", line 461, in _load_context_model_and_signature
    python_model.load_context(context=context)
  File "C:\Users\fgarb\Documents\0_PARA\1_projects\prj2_anom_container_deploy\train.py", line 172, in load_context
  File "/usr/local/lib/python3.11/site-packages/joblib/numpy_pickle.py", line 650, in load
    with open(filename, 'rb') as f:
         ^^^^^^^^^^^^^^^^^^^^
FileNotFoundError: [Errno 2] No such file or directory: '/tmp/tmp8ny0hf25/artifacts\\hparams.pkl'

Other info / logs

REPLACE_ME

What component(s) does this bug affect?

• area/artifacts: Artifact stores and artifact logging
• area/build: Build and test infrastructure for MLflow
• area/deployments: MLflow Deployments client APIs, server, and third-party Deployments integrations
• area/docs: MLflow documentation pages
• area/examples: Example code
• area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
• area/models: MLmodel format, model serialization/deserialization, flavors
• area/recipes: Recipes, Recipe APIs, Recipe configs, Recipe Templates
• area/projects: MLproject format, project running backends
• area/scoring: MLflow Model server, model deployment tools, Spark UDFs
• area/server-infra: MLflow Tracking server backend
• area/tracking: Tracking Service, tracking client APIs, autologging

What interface(s) does this bug affect?

• area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev server
• area/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Models
• area/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registry
• area/windows: Windows support

What language(s) does this bug affect?

• language/r: R APIs and clients
• language/java: Java APIs and clients
• language/new: Proposals for new client languages

What integration(s) does this bug affect?

• integrations/azure: Azure and Azure ML integrations
• integrations/sagemaker: SageMaker integrations
• integrations/databricks: Databricks integrations

[WeichenXu123]

Thanks for reporting, you can use python os.sep or os.path.join or pathlib to make path separator supporting cross-platform.

[github-actions]

@mlflow/mlflow-team Please assign a maintainer and start triaging this issue.