MemVerge Memory Machine Cloud (MMC) agent example

This example shows how to use the MMCloud agent to execute tasks on MemVerge Memory Machine Cloud.

from flytekit import Resources, task, workflow
from flytekitplugins.mmcloud import MMCloudConfig

# MMCloudConfig configures MMCloudTask. Tasks specified with MMCloudConfig
# will be executed using MMCloud. Tasks will be executed with requests cpu="1"
# and mem="1Gi" by default.
@task(task_config=MMCloudConfig())
def to_str(i: int) -> str:
    return str(i)


@task(task_config=MMCloudConfig())
def to_int(s: str) -> int:
    return int(s)

# [Resource](https://docs.flyte.org/en/latest/user_guide/productionizing/customizing_task_resources.html) (cpu and mem) requests and limits, [container](https://docs.flyte.org/en/latest/user_guide/customizing_dependencies/multiple_images_in_a_workflow.html) images, and [environment](https://docs.flyte.org/en/latest/api/flytekit/generated/flytekit.task.html) variable specifications are supported.
@task(
    task_config=MMCloudConfig(submit_extra="--migratePolicy [enable=true]"),
    requests=Resources(cpu="1", mem="1Gi"),
    limits=Resources(cpu="2", mem="4Gi"),
    environment={"KEY": "value"},
)
def concatenate_str(s1: str, s2: str) -> str:
    return s1 + s2


@workflow
def concatenate_int_wf(i1: int, i2: int) -> int:
    i1_str = to_str(i=i1)
    i2_str = to_str(i=i2)
    return to_int(s=concatenate_str(s1=i1_str, s2=i2_str))