sticky-angle-28419
03/13/2023, 11:48 PM@dynamic
is a workflow whose DAG is created during runtime (unlike @workflow
whose DAG is created during compile time), which makes it more flexible. So my question is, what are the downsides of @dynamic
compared to a static @workflow
? Why aren’t all flyte workflows @dynamic
(kind of like how all PyTorch computational graphs are by default dynamic)? Are there meaningful performance penalties to using @dynamic
?rich-garden-69988
03/14/2023, 12:20 AM@workflow
(compiled before registration). Dynamics being compiled at runtime means you can run into runtime issues that would've been caught by compiling the workflow (from my experience)sticky-angle-28419
03/14/2023, 12:21 AMrich-garden-69988
03/14/2023, 12:31 AMsticky-angle-28419
03/14/2023, 1:53 AMsticky-angle-28419
03/14/2023, 1:53 AMsticky-angle-28419
03/14/2023, 1:53 AMrich-garden-69988
03/14/2023, 2:43 AMfreezing-airport-6809
freezing-airport-6809
freezing-airport-6809
sticky-angle-28419
03/14/2023, 2:16 PMfreezing-airport-6809
freezing-airport-6809
sticky-angle-28419
03/14/2023, 2:22 PMrich-garden-69988
03/14/2023, 2:52 PMYou can generate a task, how can Flyte know if the generated task is similar to previousCan you comment on how this is done at the workflow level compared to dynamics? I thought caching was just interface/inputs/cache_version, which you'd have for both workflows and dynamics