compute = 'local' doesn't work in command() or pipeline job

[trancenoid]

• Package Name: azure-ai-ml
• Package Version: 1.21.0
• Operating System: Windows 10
• Python Version: 3.10

Describe the bug
Using local compute throws error The value provided is not a valid enum value. Field: queueSettings.jobTier. Allowed values: Spot,Basic,Standard,Premium.
To Reproduce
Steps to reproduce the behavior:

from azure.identity import DefaultAzureCredential

from azure.ai.ml import MLClient
from azure.ai.ml import command
from azure.ai.ml import Input, Output


ml_client = MLClient.from_config(DefaultAzureCredential(), path="config.json")

compute = 'local'
env = ml_client.environments.get('some-registered-env', version="6")

load_data = command(
    name="Download-Data-local1",
    display_name="Create Iris Dataset",
    description="Download and Register Data",
    is_deterministic=False, # to force rerun the step
    inputs={

        "url": Input(
            path='https://gist.github.com/netj/8836201/raw/6f9306ad21398ea43cba4f7d537619d0e07d5ae3/iris.csv',
            type="uri_file"),
    },
    outputs={
        "output_path": Output(type="uri_file", mode='rw_mount'), # a directory will be attached to the compute
    },
    # The source folder of the component
    code="tmp",
    command="""python data_prep.py \
            --url ${{inputs.url}} \
            --output_path ${{outputs.output_path}}
            """,
    environment=f"{env.name}:{env.version}",
    compute=compute
)

returned_job = ml_client.jobs.create_or_update(load_data, compute='local')
returned_job

tmp/data_prep.py :

import argparse

__all__ = ['df', 'load_data']

# %% ../nbs/experiments/data_prep_azmlish.ipynb 1
import pandas as pd
import numpy as np

# %% ../nbs/experiments/data_prep_azmlish.ipynb 3
def load_data(url):
    return pd.read_csv(url)

# Parse command-line arguments
parser = argparse.ArgumentParser(description='Data preparation script')
parser.add_argument('--url', type=str, required=True, help='URL of the CSV file to load')
parser.add_argument('--output_path', type=str, required=True, help='Path to save the output CSV file')
args = parser.parse_args()

# %% ../nbs/experiments/data_prep_azmlish.ipynb 4
df = load_data(args.url)

# %% ../nbs/experiments/data_prep_azmlish.ipynb 8
df.to_csv(args.output_path, index=False)

Expected behavior
The command should run as when using compute = 'cpu-cluster'

Screenshots
If applicable, add screenshots to help explain your problem.

Additional context
The exact code snippet works on Azure ML Compute.

[github-actions]

Thanks for the feedback! We are routing this to the appropriate team for follow-up. cc @Azure/azure-ml-sdk @azureml-github.

[trancenoid]

I tested version 1.16.1 and it works, however I would keep the issue open since the default version is 1.21.0