New RunLLM response generated:
>>>*# Question*
HI...
# runllm-flyte-triala
ancient-wolf-19325
08/22/2024, 6:04 PMNew RunLLM response generated:
>>>*# Question*
HI everyone. What is the best way to allow a failed task to still produce some output for the user. Here is a real use case: Let's say we have a task for training a model. If training fails, I prefer that the user sees this as a failed task. But I still want to return some information to the user (e.g., the location of all the checkpoints created so far). I know that there is intratask checkpointing but that is useful for passing info to the next run that is triggered by recover button. In my case, I want to pass richer info to the user so that they can decide on their next step (whether to retry using a previous checkpoint or run from scratch, see all the checkpoints and decide which ones to use, etc).
# Answer
To allow a failed task to still produce some output for the user, you can use Flyte's failure handling capabilities. Specifically, you can define a failure handler task that will be executed when the main task fails. This handler can collect and return the necessary information, such as the location of all checkpoints created so far.
Here's an example of how you can achieve this:
1. Define the main task and the failure handler task:
Copy code
from flytekit import task, workflow, WorkflowFailurePolicy
@task
def train_model() -> str:
# Simulate a failure
raise Exception("Training failed")
@task
def handle_failure(error: Exception) -> str:
# Collect and return checkpoint information
return "Checkpoint information"
@workflow(on_failure=handle_failure)
def training_workflow() -> str:
return train_model() Copy code
if __name__ == "__main__":
print(training_workflow())train_modelhandle_failure