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This commit added support for using with_platform_config with KubeflowV2DagRunner for running on Vertex, but because the logic only runs in _build_container_spec in step_builder.py, it is not run for Importer/FileBasedExampleGen nodes, so adding with_platform_config to e.g. ImportExampleGen is not reflected in the output json.
The text was updated successfully, but these errors were encountered:
@xivarri, Can you try using below code on ImportExampleGen or FileBasedExampleGen components to specify CPU and RAM on Vertex as shown in similar issue.
Thank you!
from kfp.pipeline_spec import pipeline_spec_pb2 as pipeline_pb2
my_component = MyComponent().with_platform_config(
pipeline_pb2.PipelineDeploymentConfig.PipelineContainerSpec
.ResourceSpec(cpu_limit=2.0, memory_limit=4.0))
Yeah that's what I did - but this does not get reflected in the output json, I had to do this hack from that issue to manually modify the json:
for component_executor_spec in data["pipelineSpec"]["deploymentSpec"][
"executors"
].values():
if "resources" not in component_executor_spec["container"]:
component_executor_spec["container"]["resources"] = {
"cpuLimit": 32.0,
"memoryLimit": 128.0,
}
(I also could not limit this to only the importexamplegen's executor - if I did that vertex would still use e2-standard-4 for it - so set it for all of them)
This commit added support for using
with_platform_config
withKubeflowV2DagRunner
for running on Vertex, but because the logic only runs in_build_container_spec
instep_builder.py
, it is not run forImporter
/FileBasedExampleGen
nodes, so addingwith_platform_config
to e.g.ImportExampleGen
is not reflected in the output json.The text was updated successfully, but these errors were encountered: