Hey, if I separated a

pandas_image_spec

and a

sklearn_image_spec

, and a task has requires both image_specs - is it possible to give a list of image_specs in

container_image

or how to reconcile? e.g. in `pima_diabetes`:

sklearn_image_spec = ImageSpec(
    base_image="<http://ghcr.io/flyteorg/flytekit:py3.8-1.8.2|ghcr.io/flyteorg/flytekit:py3.8-1.8.2>",
    registry="localhost:30000",
    packages=["scikit-learn", "xgboost"]
)

pandas_image_spec = ImageSpec(
    base_image="<http://ghcr.io/flyteorg/flytekit:py3.8-1.8.2|ghcr.io/flyteorg/flytekit:py3.8-1.8.2>",
    registry="localhost:30000",
    packages=["pandas", "numpy"]
)

@task(container_image=sklearn_image_spec, cache_version="1.0", cache=True, limits=Resources(mem="200Mi"))
def split_traintest_dataset(
    dataset: FlyteFile[typing.TypeVar("csv")], seed: int, test_split_ratio: float
) -> Tuple[StructuredDataset, StructuredDataset, StructuredDataset, StructuredDataset]:
    
    column_names = [k for k in DATASET_COLUMNS.keys()]
    df = pd.read_csv(dataset, names=column_names) 

    x = df[column_names[:8]]
    y = df[[column_names[-1]]]

    return train_test_split(x, y, test_size=test_split_ratio, random_state=seed)

one task can only use on image, so you can just combine those two image spec

ok not sure if I should start a new thread, but with the unreleased

flytectl demo start --image=<http://ghcr.io/flyteorg/flyte-sandbox-bundled:sha-713f3f86a4d74d555e1a55b52065119df39117e3|ghcr.io/flyteorg/flyte-sandbox-bundled:sha-713f3f86a4d74d555e1a55b52065119df39117e3>

, I am getting this

❯ pyflyte run --remote pima_diabetes/diabetes.py diabetes_xgboost_model
Failed with Unknown Exception <class 'Exception'> Reason: Builder envd is not registered.
Builder envd is not registered.

pip install flytekitplugins-envd

ah - I'll remember to add all this in every requirements.txt