New RunLLM response generated: >>>*# Question* Hey Flyters, I have a workflow that should return a dataclass with the following fields: • model(sklearn/tf/pt) • dataset (another dataclass that is json serializable) • other artifacts from model training How can i turn an arbitrary type like an sklearn model into a dataclass field? I'm looking for a solution that is similar to structured datasets for dataframes and numpys. Should I use pickled files? # Answer To handle arbitrary types like an sklearn model in a Flyte workflow, you can use Flyte's custom type transformers. Flyte defaults to using

PickleFile

for unsupported types, but you can define a custom type transformer to serialize and deserialize your model. This approach is similar to how structured datasets are handled for dataframes and numpy arrays. For your dataset, if it is JSON serializable, you can directly use it as a field in your dataclass. For other artifacts, consider using Flyte's supported types or custom transformers if they are complex objects. Would you like more detail on creating a custom type transformer for your model? Sources: - Flyte Custom Types - Flyte PickleFile Slack Link https://.slack.com/archives/CP2HDHKE1/p1731835560.866489 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.