mlflow + pytorch lightning not able to log custom models

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Components

• area/artifacts: Artifact stores and artifact logging
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• area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
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I am using a custom pytorch lightning trainer with mlflow logger MLFlowLogger(experiment_name=“Experiment”, tracking_uri=tracking_uri)

I use both mlflow.pytorch.autolog()

and the logger - which saves the parameters in default run and metrics in the run in “Experiment”. However it does not log the model which i want to use for serving, it gives the following error:

Is it that pltrainer models are not supported? My model has single inputs and multiple outputs.

[piseabhijeet]

Yes, i want to make tensorflow-pytorch compatible training pipeline.

[jwyyy]

Can you provide more code? I am not able to identity the problem based on this screenshot. You can find some posts related to the error: link1 and link2.