ZenML is an extensible, open-source MLOps framework designed to create reproducible, production-ready machine learning pipelines. It provides a structured approach to building and deploying machine learning models, ensuring that each step in the pipeline is well-defined and consistent. ZenML helps data scientists and engineers focus on their core tasks by abstracting away the complexities of pipeline orchestration and deployment.
When working with ZenML, you might encounter the STEP_OUTPUT_TYPE_ERROR. This error typically manifests when the output type of a step in your pipeline does not match the expected type defined in the pipeline configuration. This mismatch can lead to pipeline execution failures, as subsequent steps may not be able to process the output correctly.
The STEP_OUTPUT_TYPE_ERROR occurs when there is a discrepancy between the actual output type of a step and the type expected by the pipeline. This can happen due to:
Consider a step designed to output a Pandas DataFrame, but due to a recent change, it now outputs a NumPy array. If the pipeline is configured to expect a DataFrame, this will trigger the STEP_OUTPUT_TYPE_ERROR.
To resolve this error, follow these actionable steps:
Check the step function to ensure that the output type is correctly annotated. For example, if your step is supposed to return a DataFrame, make sure the function signature reflects this:
def my_step() -> pd.DataFrame:
# Your processing logic
return dataframe
Ensure that the pipeline configuration matches the expected output type. Review the pipeline definition to confirm that the expected type aligns with the step's output:
from zenml.pipelines import pipeline
@pipeline
def my_pipeline(step_1, step_2):
df = step_1()
step_2(df)
Run the step independently to verify its output type. This can help isolate the issue and confirm that the step produces the expected output:
output = my_step()
print(type(output)) # Should print <class 'pandas.core.frame.DataFrame'>
For more information on ZenML and troubleshooting, consider visiting the following resources:
By following these steps, you can effectively resolve the STEP_OUTPUT_TYPE_ERROR and ensure your ZenML pipelines run smoothly.
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