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unit_test.py
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# Copyright 2022 IBM, Red Hat
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from pathlib import Path
import sys
import filecmp
import os
import re
parent = Path(__file__).resolve().parents[1]
sys.path.append(str(parent) + "/src")
from kubernetes import client
from codeflare_sdk.cluster.awload import AWManager
from codeflare_sdk.cluster.cluster import (
Cluster,
ClusterConfiguration,
list_all_clusters,
list_all_queued,
_copy_to_ray,
get_cluster,
_app_wrapper_status,
_ray_cluster_status,
)
from codeflare_sdk.cluster.auth import (
TokenAuthentication,
PasswordUserAuthentication,
Authentication,
)
from codeflare_sdk.utils.pretty_print import (
print_no_resources_found,
print_app_wrappers_status,
print_cluster_status,
print_clusters,
)
from codeflare_sdk.cluster.model import (
AppWrapper,
RayCluster,
AppWrapperStatus,
RayClusterStatus,
CodeFlareClusterStatus,
)
from codeflare_sdk.job.jobs import (
JobDefinition,
Job,
DDPJobDefinition,
DDPJob,
torchx_runner,
)
from codeflare_sdk.utils.generate_cert import (
generate_ca_cert,
generate_tls_cert,
export_env,
)
import openshift
from openshift import OpenShiftPythonException
from openshift.selector import Selector
import ray
from torchx.specs import AppDryRunInfo, AppDef
from torchx.runner import get_runner, Runner
from torchx.schedulers.ray_scheduler import RayJob
from torchx.schedulers.kubernetes_mcad_scheduler import KubernetesMCADJob
import pytest
import yaml
# For mocking openshift client results
fake_res = openshift.Result("fake")
def arg_side_effect(*args):
fake_res.high_level_operation = args
return fake_res
def att_side_effect(self):
return self.high_level_operation
def att_side_effect_tls(self):
if "--insecure-skip-tls-verify" in self.high_level_operation[1]:
return self.high_level_operation
else:
raise OpenShiftPythonException(
"The server uses a certificate signed by unknown authority"
)
def test_token_auth_creation():
try:
token_auth = TokenAuthentication()
assert token_auth.token == None
assert token_auth.server == None
assert token_auth.skip_tls == False
token_auth = TokenAuthentication("token")
assert token_auth.token == "token"
assert token_auth.server == None
assert token_auth.skip_tls == False
token_auth = TokenAuthentication("token", "server")
assert token_auth.token == "token"
assert token_auth.server == "server"
assert token_auth.skip_tls == False
token_auth = TokenAuthentication("token", server="server")
assert token_auth.token == "token"
assert token_auth.server == "server"
assert token_auth.skip_tls == False
token_auth = TokenAuthentication(token="token", server="server")
assert token_auth.token == "token"
assert token_auth.server == "server"
assert token_auth.skip_tls == False
token_auth = TokenAuthentication(token="token", server="server", skip_tls=True)
assert token_auth.token == "token"
assert token_auth.server == "server"
assert token_auth.skip_tls == True
except Exception:
assert 0 == 1
def test_token_auth_login_logout(mocker):
mocker.patch("openshift.invoke", side_effect=arg_side_effect)
mock_res = mocker.patch.object(openshift.Result, "out")
mock_res.side_effect = lambda: att_side_effect(fake_res)
token_auth = TokenAuthentication(token="testtoken", server="testserver:6443")
assert token_auth.login() == (
"login",
["--token=testtoken", "--server=testserver:6443"],
)
assert token_auth.logout() == (
"logout",
["--token=testtoken", "--server=testserver:6443"],
)
def test_token_auth_login_tls(mocker):
mocker.patch("openshift.invoke", side_effect=arg_side_effect)
mock_res = mocker.patch.object(openshift.Result, "out")
mock_res.side_effect = lambda: att_side_effect_tls(fake_res)
# FIXME - Pytest mocker not allowing caught exception
# token_auth = TokenAuthentication(token="testtoken", server="testserver")
# assert token_auth.login() == "Error: certificate auth failure, please set `skip_tls=True` in TokenAuthentication"
token_auth = TokenAuthentication(
token="testtoken", server="testserver:6443", skip_tls=True
)
assert token_auth.login() == (
"login",
["--token=testtoken", "--server=testserver:6443", "--insecure-skip-tls-verify"],
)
def test_passwd_auth_creation():
try:
passwd_auth = PasswordUserAuthentication()
assert passwd_auth.username == None
assert passwd_auth.password == None
passwd_auth = PasswordUserAuthentication("user")
assert passwd_auth.username == "user"
assert passwd_auth.password == None
passwd_auth = PasswordUserAuthentication("user", "passwd")
assert passwd_auth.username == "user"
assert passwd_auth.password == "passwd"
passwd_auth = PasswordUserAuthentication("user", password="passwd")
assert passwd_auth.username == "user"
assert passwd_auth.password == "passwd"
passwd_auth = PasswordUserAuthentication(username="user", password="passwd")
assert passwd_auth.username == "user"
assert passwd_auth.password == "passwd"
except Exception:
assert 0 == 1
def test_passwd_auth_login_logout(mocker):
mocker.patch("openshift.invoke", side_effect=arg_side_effect)
mocker.patch("openshift.login", side_effect=arg_side_effect)
mock_res = mocker.patch.object(openshift.Result, "out")
mock_res.side_effect = lambda: att_side_effect(fake_res)
token_auth = PasswordUserAuthentication(username="user", password="passwd")
assert token_auth.login() == ("user", "passwd")
assert token_auth.logout() == ("logout",)
def test_auth_coverage():
abstract = Authentication()
abstract.login()
abstract.logout()
def test_config_creation():
config = ClusterConfiguration(
name="unit-test-cluster",
namespace="ns",
min_worker=1,
max_worker=2,
min_cpus=3,
max_cpus=4,
min_memory=5,
max_memory=6,
gpu=7,
instascale=True,
machine_types=["cpu.small", "gpu.large"],
)
assert config.name == "unit-test-cluster" and config.namespace == "ns"
assert config.min_worker == 1 and config.max_worker == 2
assert config.min_cpus == 3 and config.max_cpus == 4
assert config.min_memory == 5 and config.max_memory == 6
assert config.gpu == 7
assert (
config.image
== "ghcr.io/foundation-model-stack/base:ray2.1.0-py38-gpu-pytorch1.12.0cu116-20221213-193103"
)
assert config.template == f"{parent}/src/codeflare_sdk/templates/base-template.yaml"
assert config.instascale
assert config.machine_types == ["cpu.small", "gpu.large"]
return config
def test_cluster_creation():
cluster = Cluster(test_config_creation())
assert cluster.app_wrapper_yaml == "unit-test-cluster.yaml"
assert cluster.app_wrapper_name == "unit-test-cluster"
assert filecmp.cmp(
"unit-test-cluster.yaml", f"{parent}/tests/test-case.yaml", shallow=True
)
return cluster
def test_default_cluster_creation(mocker):
mocker.patch(
"codeflare_sdk.cluster.cluster.get_current_namespace",
return_value="opendatahub",
)
default_config = ClusterConfiguration(
name="unit-test-default-cluster",
)
cluster = Cluster(default_config)
assert cluster.app_wrapper_yaml == "unit-test-default-cluster.yaml"
assert cluster.app_wrapper_name == "unit-test-default-cluster"
assert cluster.config.namespace == "opendatahub"
return cluster
def arg_check_apply_effect(group, version, namespace, plural, body, *args):
assert group == "mcad.ibm.com"
assert version == "v1beta1"
assert namespace == "ns"
assert plural == "appwrappers"
with open("unit-test-cluster.yaml") as f:
aw = yaml.load(f, Loader=yaml.FullLoader)
assert body == aw
assert args == tuple()
def arg_check_del_effect(group, version, namespace, plural, name, *args):
assert group == "mcad.ibm.com"
assert version == "v1beta1"
assert namespace == "ns"
assert plural == "appwrappers"
assert name == "unit-test-cluster"
assert args == tuple()
def test_cluster_up_down(mocker):
mocker.patch("kubernetes.config.load_kube_config", return_value="ignore")
mocker.patch(
"kubernetes.client.CustomObjectsApi.create_namespaced_custom_object",
side_effect=arg_check_apply_effect,
)
mocker.patch(
"kubernetes.client.CustomObjectsApi.delete_namespaced_custom_object",
side_effect=arg_check_del_effect,
)
cluster = test_cluster_creation()
cluster.up()
cluster.down()
def aw_status_fields(group, version, namespace, plural, *args):
assert group == "mcad.ibm.com"
assert version == "v1beta1"
assert namespace == "test-ns"
assert plural == "appwrappers"
assert args == tuple()
return {"items": []}
def test_aw_status(mocker):
mocker.patch("kubernetes.config.load_kube_config", return_value="ignore")
mocker.patch(
"kubernetes.client.CustomObjectsApi.list_namespaced_custom_object",
side_effect=aw_status_fields,
)
aw = _app_wrapper_status("test-aw", "test-ns")
assert aw == None
def rc_status_fields(group, version, namespace, plural, *args):
assert group == "ray.io"
assert version == "v1alpha1"
assert namespace == "test-ns"
assert plural == "rayclusters"
assert args == tuple()
return {"items": []}
def test_rc_status(mocker):
mocker.patch("kubernetes.config.load_kube_config", return_value="ignore")
mocker.patch(
"kubernetes.client.CustomObjectsApi.list_namespaced_custom_object",
side_effect=rc_status_fields,
)
rc = _ray_cluster_status("test-rc", "test-ns")
assert rc == None
def uri_retreival(group, version, namespace, plural, *args):
assert group == "route.openshift.io"
assert version == "v1"
assert namespace == "ns"
assert plural == "routes"
assert args == tuple()
return {
"items": [
{
"metadata": {"name": "ray-dashboard-unit-test-cluster"},
"spec": {
"host": "ray-dashboard-unit-test-cluster-ns.apps.cluster.awsroute.org"
},
}
]
}
def test_cluster_uris(mocker):
mocker.patch("kubernetes.config.load_kube_config", return_value="ignore")
mocker.patch(
"kubernetes.client.CustomObjectsApi.list_namespaced_custom_object",
side_effect=uri_retreival,
)
cluster = test_cluster_creation()
assert cluster.cluster_uri() == "ray://unit-test-cluster-head-svc.ns.svc:10001"
assert (
cluster.cluster_dashboard_uri()
== "http://ray-dashboard-unit-test-cluster-ns.apps.cluster.awsroute.org"
)
cluster.config.name = "fake"
assert (
cluster.cluster_dashboard_uri()
== "Dashboard route not available yet, have you run cluster.up()?"
)
def test_local_client_url(mocker):
mocker.patch(
"kubernetes.client.CustomObjectsApi.get_cluster_custom_object",
return_value={"spec": {"domain": ""}},
)
mocker.patch(
"codeflare_sdk.cluster.cluster._get_ingress_domain",
return_value="apps.cluster.awsroute.org",
)
mocker.patch(
"codeflare_sdk.cluster.cluster.Cluster.create_app_wrapper",
return_value="unit-test-cluster-localinter.yaml",
)
cluster_config = ClusterConfiguration(
name="unit-test-cluster-localinter", namespace="ns", local_interactive=True
)
cluster = Cluster(cluster_config)
assert (
cluster.local_client_url()
== "ray://rayclient-unit-test-cluster-localinter-ns.apps.cluster.awsroute.org"
)
def ray_addr(self, *args):
return self._address
def test_ray_job_wrapping(mocker):
mocker.patch("kubernetes.config.load_kube_config", return_value="ignore")
mocker.patch(
"kubernetes.client.CustomObjectsApi.list_namespaced_custom_object",
side_effect=uri_retreival,
)
cluster = test_cluster_creation()
mocker.patch(
"ray.job_submission.JobSubmissionClient._check_connection_and_version_with_url",
return_value="None",
)
mock_res = mocker.patch.object(
ray.job_submission.JobSubmissionClient, "list_jobs", autospec=True
)
mock_res.side_effect = ray_addr
assert cluster.list_jobs() == cluster.cluster_dashboard_uri()
mock_res = mocker.patch.object(
ray.job_submission.JobSubmissionClient, "get_job_status", autospec=True
)
mock_res.side_effect = ray_addr
assert cluster.job_status("fake_id") == cluster.cluster_dashboard_uri()
mock_res = mocker.patch.object(
ray.job_submission.JobSubmissionClient, "get_job_logs", autospec=True
)
mock_res.side_effect = ray_addr
assert cluster.job_logs("fake_id") == cluster.cluster_dashboard_uri()
def test_print_no_resources(capsys):
try:
print_no_resources_found()
except:
assert 1 == 0
captured = capsys.readouterr()
assert captured.out == (
"╭──────────────────────────────────────────────────────────────────────────────╮\n"
"│ No resources found, have you run cluster.up() yet? │\n"
"╰──────────────────────────────────────────────────────────────────────────────╯\n"
)
def test_print_no_cluster(capsys):
try:
print_cluster_status(None)
except:
assert 1 == 0
captured = capsys.readouterr()
assert captured.out == (
"╭──────────────────────────────────────────────────────────────────────────────╮\n"
"│ No resources found, have you run cluster.up() yet? │\n"
"╰──────────────────────────────────────────────────────────────────────────────╯\n"
)
def test_print_appwrappers(capsys):
aw1 = AppWrapper(
name="awtest1",
status=AppWrapperStatus.PENDING,
can_run=False,
job_state="queue-state",
)
aw2 = AppWrapper(
name="awtest2",
status=AppWrapperStatus.RUNNING,
can_run=False,
job_state="queue-state",
)
try:
print_app_wrappers_status([aw1, aw2])
except:
assert 1 == 0
captured = capsys.readouterr()
assert captured.out == (
"╭───────────────────────╮\n"
"│ 🚀 Cluster Queue │\n"
"│ Status 🚀 │\n"
"│ +---------+---------+ │\n"
"│ | Name | Status | │\n"
"│ +=========+=========+ │\n"
"│ | awtest1 | pending | │\n"
"│ | | | │\n"
"│ | awtest2 | running | │\n"
"│ | | | │\n"
"│ +---------+---------+ │\n"
"╰───────────────────────╯\n"
)
def test_ray_details(mocker, capsys):
ray1 = RayCluster(
name="raytest1",
status=RayClusterStatus.READY,
min_workers=1,
max_workers=1,
worker_mem_min=2,
worker_mem_max=2,
worker_cpu=1,
worker_gpu=0,
namespace="ns",
dashboard="fake-uri",
)
mocker.patch(
"codeflare_sdk.cluster.cluster.Cluster.status",
return_value=(False, CodeFlareClusterStatus.UNKNOWN),
)
mocker.patch(
"codeflare_sdk.cluster.cluster.Cluster.cluster_dashboard_uri",
return_value="",
)
cf = Cluster(ClusterConfiguration(name="raytest2", namespace="ns"))
captured = capsys.readouterr()
ray2 = _copy_to_ray(cf)
details = cf.details()
assert details == ray2
assert ray2.name == "raytest2"
assert ray1.namespace == ray2.namespace
assert ray1.min_workers == ray2.min_workers
assert ray1.max_workers == ray2.max_workers
assert ray1.worker_mem_min == ray2.worker_mem_min
assert ray1.worker_mem_max == ray2.worker_mem_max
assert ray1.worker_cpu == ray2.worker_cpu
assert ray1.worker_gpu == ray2.worker_gpu
try:
print_clusters([ray1, ray2])
print_cluster_status(ray1)
print_cluster_status(ray2)
except:
assert 0 == 1
captured = capsys.readouterr()
assert captured.out == (
" 🚀 CodeFlare Cluster Details 🚀 \n"
" \n"
" ╭──────────────────────────────────────────────────────────────╮ \n"
" │ Name │ \n"
" │ raytest2 Inactive ❌ │ \n"
" │ │ \n"
" │ URI: ray://raytest2-head-svc.ns.svc:10001 │ \n"
" │ │ \n"
" │ Dashboard🔗 │ \n"
" │ │ \n"
" │ Cluster Resources │ \n"
" │ ╭─ Workers ──╮ ╭───────── Worker specs(each) ─────────╮ │ \n"
" │ │ Min Max │ │ Memory CPU GPU │ │ \n"
" │ │ │ │ │ │ \n"
" │ │ 1 1 │ │ 2~2 1 0 │ │ \n"
" │ │ │ │ │ │ \n"
" │ ╰────────────╯ ╰──────────────────────────────────────╯ │ \n"
" ╰──────────────────────────────────────────────────────────────╯ \n"
" 🚀 CodeFlare Cluster Details 🚀 \n"
" \n"
" ╭──────────────────────────────────────────────────────────────╮ \n"
" │ Name │ \n"
" │ raytest1 Active ✅ │ \n"
" │ │ \n"
" │ URI: ray://raytest1-head-svc.ns.svc:10001 │ \n"
" │ │ \n"
" │ Dashboard🔗 │ \n"
" │ │ \n"
" │ Cluster Resources │ \n"
" │ ╭─ Workers ──╮ ╭───────── Worker specs(each) ─────────╮ │ \n"
" │ │ Min Max │ │ Memory CPU GPU │ │ \n"
" │ │ │ │ │ │ \n"
" │ │ 1 1 │ │ 2~2 1 0 │ │ \n"
" │ │ │ │ │ │ \n"
" │ ╰────────────╯ ╰──────────────────────────────────────╯ │ \n"
" ╰──────────────────────────────────────────────────────────────╯ \n"
"╭──────────────────────────────────────────────────────────────╮\n"
"│ Name │\n"
"│ raytest2 Inactive ❌ │\n"
"│ │\n"
"│ URI: ray://raytest2-head-svc.ns.svc:10001 │\n"
"│ │\n"
"│ Dashboard🔗 │\n"
"│ │\n"
"│ Cluster Resources │\n"
"│ ╭─ Workers ──╮ ╭───────── Worker specs(each) ─────────╮ │\n"
"│ │ Min Max │ │ Memory CPU GPU │ │\n"
"│ │ │ │ │ │\n"
"│ │ 1 1 │ │ 2~2 1 0 │ │\n"
"│ │ │ │ │ │\n"
"│ ╰────────────╯ ╰──────────────────────────────────────╯ │\n"
"╰──────────────────────────────────────────────────────────────╯\n"
" 🚀 CodeFlare Cluster Status 🚀 \n"
" \n"
" ╭──────────────────────────────────────────────────────────╮ \n"
" │ Name │ \n"
" │ raytest1 Active ✅ │ \n"
" │ │ \n"
" │ URI: ray://raytest1-head-svc.ns.svc:10001 │ \n"
" │ │ \n"
" │ Dashboard🔗 │ \n"
" │ │ \n"
" ╰──────────────────────────────────────────────────────────╯ \n"
" 🚀 CodeFlare Cluster Status 🚀 \n"
" \n"
" ╭────────────────────────────────────────────────────────────╮ \n"
" │ Name │ \n"
" │ raytest2 Inactive ❌ │ \n"
" │ │ \n"
" │ URI: ray://raytest2-head-svc.ns.svc:10001 │ \n"
" │ │ \n"
" │ Dashboard🔗 │ \n"
" │ │ \n"
" ╰────────────────────────────────────────────────────────────╯ \n"
)
def act_side_effect_list(self):
print([self])
self.out = str(self.high_level_operation)
return [self]
def get_obj_none(group, version, namespace, plural):
return {"items": []}
def get_ray_obj(group, version, namespace, plural, cls=None):
api_obj = {
"items": [
{
"apiVersion": "ray.io/v1alpha1",
"kind": "RayCluster",
"metadata": {
"creationTimestamp": "2023-02-22T16:26:07Z",
"generation": 1,
"labels": {
"appwrapper.mcad.ibm.com": "quicktest",
"controller-tools.k8s.io": "1.0",
"resourceName": "quicktest",
"orderedinstance": "m4.xlarge_g4dn.xlarge",
},
"managedFields": [
{
"apiVersion": "ray.io/v1alpha1",
"fieldsType": "FieldsV1",
"fieldsV1": {
"f:metadata": {
"f:labels": {
".": {},
"f:appwrapper.mcad.ibm.com": {},
"f:controller-tools.k8s.io": {},
"f:resourceName": {},
},
"f:ownerReferences": {
".": {},
'k:{"uid":"6334fc1b-471e-4876-8e7b-0b2277679235"}': {},
},
},
"f:spec": {
".": {},
"f:autoscalerOptions": {
".": {},
"f:idleTimeoutSeconds": {},
"f:imagePullPolicy": {},
"f:resources": {
".": {},
"f:limits": {
".": {},
"f:cpu": {},
"f:memory": {},
},
"f:requests": {
".": {},
"f:cpu": {},
"f:memory": {},
},
},
"f:upscalingMode": {},
},
"f:enableInTreeAutoscaling": {},
"f:headGroupSpec": {
".": {},
"f:rayStartParams": {
".": {},
"f:block": {},
"f:dashboard-host": {},
"f:num-gpus": {},
},
"f:serviceType": {},
"f:template": {
".": {},
"f:spec": {".": {}, "f:containers": {}},
},
},
"f:rayVersion": {},
"f:workerGroupSpecs": {},
},
},
"manager": "mcad-controller",
"operation": "Update",
"time": "2023-02-22T16:26:07Z",
},
{
"apiVersion": "ray.io/v1alpha1",
"fieldsType": "FieldsV1",
"fieldsV1": {
"f:status": {
".": {},
"f:availableWorkerReplicas": {},
"f:desiredWorkerReplicas": {},
"f:endpoints": {
".": {},
"f:client": {},
"f:dashboard": {},
"f:gcs": {},
},
"f:lastUpdateTime": {},
"f:maxWorkerReplicas": {},
"f:minWorkerReplicas": {},
"f:state": {},
}
},
"manager": "manager",
"operation": "Update",
"subresource": "status",
"time": "2023-02-22T16:26:16Z",
},
],
"name": "quicktest",
"namespace": "ns",
"ownerReferences": [
{
"apiVersion": "mcad.ibm.com/v1beta1",
"blockOwnerDeletion": True,
"controller": True,
"kind": "AppWrapper",
"name": "quicktest",
"uid": "6334fc1b-471e-4876-8e7b-0b2277679235",
}
],
"resourceVersion": "9482407",
"uid": "44d45d1f-26c8-43e7-841f-831dbd8c1285",
},
"spec": {
"autoscalerOptions": {
"idleTimeoutSeconds": 60,
"imagePullPolicy": "Always",
"resources": {
"limits": {"cpu": "500m", "memory": "512Mi"},
"requests": {"cpu": "500m", "memory": "512Mi"},
},
"upscalingMode": "Default",
},
"enableInTreeAutoscaling": False,
"headGroupSpec": {
"rayStartParams": {
"block": "true",
"dashboard-host": "0.0.0.0",
"num-gpus": "0",
},
"serviceType": "ClusterIP",
"template": {
"spec": {
"containers": [
{
"image": "ghcr.io/foundation-model-stack/base:ray2.1.0-py38-gpu-pytorch1.12.0cu116-20221213-193103",
"imagePullPolicy": "Always",
"lifecycle": {
"preStop": {
"exec": {
"command": [
"/bin/sh",
"-c",
"ray stop",
]
}
}
},
"name": "ray-head",
"ports": [
{
"containerPort": 6379,
"name": "gcs",
"protocol": "TCP",
},
{
"containerPort": 8265,
"name": "dashboard",
"protocol": "TCP",
},
{
"containerPort": 10001,
"name": "client",
"protocol": "TCP",
},
],
"resources": {
"limits": {
"cpu": 2,
"memory": "8G",
"nvidia.com/gpu": 0,
},
"requests": {
"cpu": 2,
"memory": "8G",
"nvidia.com/gpu": 0,
},
},
}
]
}
},
},
"rayVersion": "1.12.0",
"workerGroupSpecs": [
{
"groupName": "small-group-quicktest",
"maxReplicas": 1,
"minReplicas": 1,
"rayStartParams": {"block": "true", "num-gpus": "0"},
"replicas": 1,
"template": {
"metadata": {
"annotations": {"key": "value"},
"labels": {"key": "value"},
},
"spec": {
"containers": [
{
"env": [
{
"name": "MY_POD_IP",
"valueFrom": {
"fieldRef": {
"fieldPath": "status.podIP"
}
},
}
],
"image": "ghcr.io/foundation-model-stack/base:ray2.1.0-py38-gpu-pytorch1.12.0cu116-20221213-193103",
"lifecycle": {
"preStop": {
"exec": {
"command": [
"/bin/sh",
"-c",
"ray stop",
]
}
}
},
"name": "machine-learning",
"resources": {
"limits": {
"cpu": 1,
"memory": "2G",
"nvidia.com/gpu": 0,
},
"requests": {
"cpu": 1,
"memory": "2G",
"nvidia.com/gpu": 0,
},
},
}
],
"initContainers": [
{
"command": [
"sh",
"-c",
"until nslookup $RAY_IP.$(cat /var/run/secrets/kubernetes.io/serviceaccount/namespace).svc.cluster.local; do echo waiting for myservice; sleep 2; done",
],
"image": "busybox:1.28",
"name": "init-myservice",
}
],
},
},
}
],
},
"status": {
"availableWorkerReplicas": 2,
"desiredWorkerReplicas": 1,
"endpoints": {
"client": "10001",
"dashboard": "8265",
"gcs": "6379",
},
"lastUpdateTime": "2023-02-22T16:26:16Z",
"maxWorkerReplicas": 1,
"minWorkerReplicas": 1,
"state": "ready",
},
}
]
}
return api_obj
def get_aw_obj(group, version, namespace, plural):
api_obj1 = {
"items": [
{
"apiVersion": "mcad.ibm.com/v1beta1",
"kind": "AppWrapper",
"metadata": {
"annotations": {
"kubectl.kubernetes.io/last-applied-configuration": '{"apiVersion":"mcad.ibm.com/v1beta1","kind":"AppWrapper","metadata":{"annotations":{},"name":"quicktest1","namespace":"ns"},"spec":{"priority":9,"resources":{"GenericItems":[{"custompodresources":[{"limits":{"cpu":2,"memory":"8G","nvidia.com/gpu":0},"replicas":1,"requests":{"cpu":2,"memory":"8G","nvidia.com/gpu":0}},{"limits":{"cpu":1,"memory":"2G","nvidia.com/gpu":0},"replicas":1,"requests":{"cpu":1,"memory":"2G","nvidia.com/gpu":0}}],"generictemplate":{"apiVersion":"ray.io/v1alpha1","kind":"RayCluster","metadata":{"labels":{"appwrapper.mcad.ibm.com":"quicktest1","controller-tools.k8s.io":"1.0"},"name":"quicktest1","namespace":"ns"},"spec":{"autoscalerOptions":{"idleTimeoutSeconds":60,"imagePullPolicy":"Always","resources":{"limits":{"cpu":"500m","memory":"512Mi"},"requests":{"cpu":"500m","memory":"512Mi"}},"upscalingMode":"Default"},"enableInTreeAutoscaling":false,"headGroupSpec":{"rayStartParams":{"block":"true","dashboard-host":"0.0.0.0","num-gpus":"0"},"serviceType":"ClusterIP","template":{"spec":{"containers":[{"image":"ghcr.io/foundation-model-stack/base:ray2.1.0-py38-gpu-pytorch1.12.0cu116-20221213-193103","imagePullPolicy":"Always","lifecycle":{"preStop":{"exec":{"command":["/bin/sh","-c","ray stop"]}}},"name":"ray-head","ports":[{"containerPort":6379,"name":"gcs"},{"containerPort":8265,"name":"dashboard"},{"containerPort":10001,"name":"client"}],"resources":{"limits":{"cpu":2,"memory":"8G","nvidia.com/gpu":0},"requests":{"cpu":2,"memory":"8G","nvidia.com/gpu":0}}}]}}},"rayVersion":"1.12.0","workerGroupSpecs":[{"groupName":"small-group-quicktest","maxReplicas":1,"minReplicas":1,"rayStartParams":{"block":"true","num-gpus":"0"},"replicas":1,"template":{"metadata":{"annotations":{"key":"value"},"labels":{"key":"value"}},"spec":{"containers":[{"env":[{"name":"MY_POD_IP","valueFrom":{"fieldRef":{"fieldPath":"status.podIP"}}}],"image":"ghcr.io/foundation-model-stack/base:ray2.1.0-py38-gpu-pytorch1.12.0cu116-20221213-193103","lifecycle":{"preStop":{"exec":{"command":["/bin/sh","-c","ray stop"]}}},"name":"machine-learning","resources":{"limits":{"cpu":1,"memory":"2G","nvidia.com/gpu":0},"requests":{"cpu":1,"memory":"2G","nvidia.com/gpu":0}}}],"initContainers":[{"command":["sh","-c","until nslookup $RAY_IP.$(cat /var/run/secrets/kubernetes.io/serviceaccount/namespace).svc.cluster.local; do echo waiting for myservice; sleep 2; done"],"image":"busybox:1.28","name":"init-myservice"}]}}}]}},"replicas":1},{"generictemplate":{"apiVersion":"route.openshift.io/v1","kind":"Route","metadata":{"labels":{"odh-ray-cluster-service":"quicktest-head-svc"},"name":"ray-dashboard-quicktest","namespace":"default"},"spec":{"port":{"targetPort":"dashboard"},"to":{"kind":"Service","name":"quicktest-head-svc"}}},"replica":1}],"Items":[]}}}\n'
},
"creationTimestamp": "2023-02-22T16:26:07Z",
"generation": 4,
"managedFields": [
{
"apiVersion": "mcad.ibm.com/v1beta1",
"fieldsType": "FieldsV1",
"fieldsV1": {
"f:spec": {
"f:resources": {
"f:GenericItems": {},
"f:metadata": {},
},
"f:schedulingSpec": {},
"f:service": {".": {}, "f:spec": {}},
},
"f:status": {
".": {},
"f:canrun": {},
"f:conditions": {},
"f:controllerfirsttimestamp": {},
"f:filterignore": {},
"f:queuejobstate": {},
"f:sender": {},
"f:state": {},
"f:systempriority": {},
},
},
"manager": "Go-http-client",
"operation": "Update",
"time": "2023-02-22T16:26:07Z",
},
{
"apiVersion": "mcad.ibm.com/v1beta1",
"fieldsType": "FieldsV1",
"fieldsV1": {
"f:metadata": {
"f:annotations": {
".": {},
"f:kubectl.kubernetes.io/last-applied-configuration": {},
}
},
"f:spec": {
".": {},
"f:priority": {},
"f:resources": {".": {}, "f:Items": {}},
},
},
"manager": "kubectl-client-side-apply",
"operation": "Update",
"time": "2023-02-22T16:26:07Z",
},
],
"name": "quicktest1",
"namespace": "ns",
"resourceVersion": "9482384",
"uid": "6334fc1b-471e-4876-8e7b-0b2277679235",
},
"spec": {
"priority": 9,
"resources": {
"GenericItems": [
{
"allocated": 0,
"custompodresources": [
{
"limits": {
"cpu": "2",
"memory": "8G",
"nvidia.com/gpu": "0",
},
"replicas": 1,
"requests": {
"cpu": "2",
"memory": "8G",
"nvidia.com/gpu": "0",
},
},
{
"limits": {
"cpu": "1",
"memory": "2G",
"nvidia.com/gpu": "0",
},
"replicas": 1,
"requests": {
"cpu": "1",