diff --git a/redhat/ocp4/4.16/files/ray.notebook/2.5_run.llama.factory.ipynb b/redhat/ocp4/4.16/files/ray.notebook/2.5_run.llama.factory.ipynb
index 136ce14e..4aa1f45c 100644
--- a/redhat/ocp4/4.16/files/ray.notebook/2.5_run.llama.factory.ipynb
+++ b/redhat/ocp4/4.16/files/ray.notebook/2.5_run.llama.factory.ipynb
@@ -10,31 +10,64 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 17,
"id": "b55bc3ea-4ce3-49bf-bb1f-e209de8ca47a",
"metadata": {},
"outputs": [],
"source": [
"# Import pieces from codeflare-sdk\n",
- "from codeflare_sdk import Cluster, ClusterConfiguration, TokenAuthentication\n",
- "\n",
- "# import os\n",
- "\n",
- "# %env RAY_TLS_VERIFY=0"
+ "from codeflare_sdk import Cluster, ClusterConfiguration, TokenAuthentication"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 18,
+ "id": "abe0a3d8-1c53-4714-9c48-19a9158f4bd0",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "0.23.1\n"
+ ]
+ }
+ ],
+ "source": [
+ "import codeflare_sdk\n",
+ "print(codeflare_sdk.__version__)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
"id": "614daa0c",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Insecure request warnings have been disabled\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "'Logged into https://api.demo-01-rhsys.wzhlab.top:6443'"
+ ]
+ },
+ "execution_count": 19,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
"source": [
"# Create authentication object for user permissions\n",
"# IF unused, SDK will automatically check for default kubeconfig, then in-cluster config\n",
"# KubeConfigFileAuthentication can also be used to specify kubeconfig path manually\n",
"auth = TokenAuthentication(\n",
- " token = \"sha256~DVnZ1tbr11kPu9ltluH0M_Xa3O_6dEKFZScmvHuio1Y\",\n",
+ " token = \"sha256~oMdcvXQ6WV5ZxlRwCniQXn9_VzyIGbrs05b8ccrDvbQ\",\n",
" server = \"https://api.demo-01-rhsys.wzhlab.top:6443\",\n",
" skip_tls= True\n",
")\n",
@@ -58,10 +91,47 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 20,
"id": "0f4bc870-091f-4e11-9642-cba145710159",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Warning: TLS verification has been disabled - Endpoint checks will be bypassed\n",
+ "Yaml resources loaded for llama-factory-test\n"
+ ]
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "fde461846e9d47ef9b85453c043506d8",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "VBox(children=(HBox(children=(Button(description='Cluster Up', icon='play', style=ButtonStyle(), tooltip='Creaโฆ"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "46990e1ca6c44602a3fe011552af88f5",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "Output()"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"# Create and configure our cluster object\n",
"# The SDK will try to find the name of your default local queue based on the annotation \"kueue.x-k8s.io/default-queue\": \"true\" unless you specify the local queue manually below\n",
@@ -75,8 +145,8 @@
" head_extended_resource_requests={'nvidia.com/gpu':0}, # For GPU enabled workloads set the head_extended_resource_requests and worker_extended_resource_requests\n",
" worker_extended_resource_requests={'nvidia.com/gpu':0},\n",
" num_workers=2,\n",
- " worker_cpu_requests='250m',\n",
- " worker_cpu_limits=1,\n",
+ " worker_cpu_requests='2',\n",
+ " worker_cpu_limits=8,\n",
" worker_memory_requests=4,\n",
" worker_memory_limits=6,\n",
" image=\"quay.io/wangzheng422/qimgs:llama-factory-ray-20250106-v06\", # Optional Field \n",
@@ -88,10 +158,21 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 21,
"id": "f0884bbc-c224-4ca0-98a0-02dfa09c2200",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Ray Cluster: 'llama-factory-test' has successfully been created\n",
+ "Waiting for requested resources to be set up...\n",
+ "Requested cluster is up and running!\n",
+ "Dashboard is ready!\n"
+ ]
+ }
+ ],
"source": [
"# Bring up the cluster\n",
"cluster.up()\n",
@@ -100,10 +181,68 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 22,
"id": "df71c1ed",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ " ๐ CodeFlare Cluster Details ๐ \n",
+ " \n",
+ " โญโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฎ \n",
+ " โ Name โ \n",
+ " โ llama-factory-test Active โ
โ \n",
+ " โ โ \n",
+ " โ URI: ray://llama-factory-test-head-svc.rhods-notebooks.svc:10001 โ \n",
+ " โ โ \n",
+ " โ Dashboard๐ โ \n",
+ " โ โ \n",
+ " โ Cluster Resources โ \n",
+ " โ โญโโ Workers โโโฎ โญโโโโโโโโโ Worker specs(each) โโโโโโโโโโฎ โ \n",
+ " โ โ # Workers โ โ Memory CPU GPU โ โ \n",
+ " โ โ โ โ โ โ \n",
+ " โ โ 2 โ โ 4G~6G 2~8 0 โ โ \n",
+ " โ โ โ โ โ โ \n",
+ " โ โฐโโโโโโโโโโโโโโฏ โฐโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฏ โ \n",
+ " โฐโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฏ \n",
+ "
\n"
+ ],
+ "text/plain": [
+ "\u001b[3m \u001b[0m\u001b[1;3m ๐ CodeFlare Cluster Details ๐\u001b[0m\u001b[3m \u001b[0m\n",
+ "\u001b[1m \u001b[0m\u001b[1m \u001b[0m\u001b[1m \u001b[0m\n",
+ " โญโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฎ \n",
+ " โ \u001b[1;37;42mName\u001b[0m โ \n",
+ " โ \u001b[1;4mllama-factory-test\u001b[0m Active โ
โ \n",
+ " โ โ \n",
+ " โ \u001b[1mURI:\u001b[0m ray://llama-factory-test-head-svc.rhods-notebooks.svc:10001 โ \n",
+ " โ โ \n",
+ " โ \u001b]8;id=948038;https://ray-dashboard-llama-factory-test-rhods-notebooks.apps.demo-01-rhsys.wzhlab.top\u001b\\\u001b[4;34mDashboard๐\u001b[0m\u001b]8;;\u001b\\ โ \n",
+ " โ โ \n",
+ " โ \u001b[3m Cluster Resources \u001b[0m โ \n",
+ " โ โญโโ Workers โโโฎ โญโโโโโโโโโ Worker specs(each) โโโโโโโโโโฎ โ \n",
+ " โ โ \u001b[1m \u001b[0m\u001b[1m# Workers\u001b[0m\u001b[1m \u001b[0m โ โ \u001b[1m \u001b[0m\u001b[1mMemory \u001b[0m\u001b[1m \u001b[0m\u001b[1m \u001b[0m\u001b[1mCPU \u001b[0m\u001b[1m \u001b[0m\u001b[1m \u001b[0m\u001b[1mGPU \u001b[0m\u001b[1m \u001b[0m โ โ \n",
+ " โ โ \u001b[35m \u001b[0m\u001b[35m \u001b[0m\u001b[35m \u001b[0m โ โ \u001b[36m \u001b[0m\u001b[36m \u001b[0m\u001b[36m \u001b[0m\u001b[35m \u001b[0m\u001b[35m \u001b[0m\u001b[35m \u001b[0m\u001b[35m \u001b[0m\u001b[35m \u001b[0m\u001b[35m \u001b[0m โ โ \n",
+ " โ โ \u001b[35m \u001b[0m\u001b[35m2 \u001b[0m\u001b[35m \u001b[0m โ โ \u001b[36m \u001b[0m\u001b[36m4G~6G \u001b[0m\u001b[36m \u001b[0m\u001b[35m \u001b[0m\u001b[35m2~8 \u001b[0m\u001b[35m \u001b[0m\u001b[35m \u001b[0m\u001b[35m0 \u001b[0m\u001b[35m \u001b[0m โ โ \n",
+ " โ โ \u001b[35m \u001b[0m\u001b[35m \u001b[0m\u001b[35m \u001b[0m โ โ \u001b[36m \u001b[0m\u001b[36m \u001b[0m\u001b[36m \u001b[0m\u001b[35m \u001b[0m\u001b[35m \u001b[0m\u001b[35m \u001b[0m\u001b[35m \u001b[0m\u001b[35m \u001b[0m\u001b[35m \u001b[0m โ โ \n",
+ " โ โฐโโโโโโโโโโโโโโฏ โฐโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฏ โ \n",
+ " โฐโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฏ \n"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "text/plain": [
+ "RayCluster(name='llama-factory-test', status=, head_cpu_requests=1, head_cpu_limits=1, head_mem_requests='6G', head_mem_limits='6G', num_workers=2, worker_mem_requests='4G', worker_mem_limits='6G', worker_cpu_requests='2', worker_cpu_limits=8, namespace='rhods-notebooks', dashboard='https://ray-dashboard-llama-factory-test-rhods-notebooks.apps.demo-01-rhsys.wzhlab.top', worker_extended_resources={'nvidia.com/gpu': 0}, head_extended_resources={'nvidia.com/gpu': 0})"
+ ]
+ },
+ "execution_count": 22,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
"source": [
"cluster.details()"
]
@@ -120,10 +259,19 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 23,
"id": "c1719bca",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "https://ray-dashboard-llama-factory-test-rhods-notebooks.apps.demo-01-rhsys.wzhlab.top\n",
+ "ray://llama-factory-test-head-svc.rhods-notebooks.svc:10001\n"
+ ]
+ }
+ ],
"source": [
"ray_dashboard_uri = cluster.cluster_dashboard_uri()\n",
"ray_cluster_uri = cluster.cluster_uri()\n",
@@ -141,7 +289,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 24,
"id": "c9436436",
"metadata": {},
"outputs": [],
@@ -154,18 +302,31 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 25,
"id": "300146dc",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "2025-01-07 16:29:14,056\tINFO client_builder.py:244 -- Passing the following kwargs to ray.init() on the server: ignore_reinit_error\n",
+ "SIGTERM handler is not set because current thread is not the main thread.\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Ray cluster is up and running: True\n"
+ ]
+ }
+ ],
"source": [
"# before proceeding make sure the cluster exists and the uri is not empty\n",
"assert ray_cluster_uri, \"Ray cluster needs to be started and set before proceeding\"\n",
"\n",
"import ray\n",
- "import os\n",
- "\n",
- "%env RAY_TLS_VERIFY=0\n",
"\n",
"# reset the ray context in case there's already one. \n",
"ray.shutdown()\n",
@@ -176,7 +337,7 @@
"runtime_env = {}\n",
"# NOTE: This will work for in-cluster notebook servers (RHODS/ODH), but not for local machines\n",
"# To see how to connect from your laptop, go to demo-notebooks/additional-demos/local_interactive.ipynb\n",
- "ray.init(address=ray_cluster_uri, runtime_env=runtime_env, ignore_reinit_error=True, _ssl_verify=False)\n",
+ "ray.init(address=ray_cluster_uri, runtime_env=runtime_env, ignore_reinit_error=True)\n",
"\n",
"print(\"Ray cluster is up and running: \", ray.is_initialized())"
]
@@ -191,7 +352,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 26,
"id": "1b36e0d9",
"metadata": {},
"outputs": [],
@@ -218,11 +379,7 @@
"\n",
" def execute_command(self, ip_address, nnodes, node_rank):\n",
" command = f'source /opt/py_env/bin/activate; cd /app; FORCE_TORCHRUN=1 NNODES={nnodes} NODE_RANK={node_rank} MASTER_ADDR={ip_address} MASTER_PORT=29500 NPROC_PER_NODE=1 llamafactory-cli train wzh/tinyllama_lora_sft.yaml'\n",
- " try:\n",
- " os.system(command)\n",
- " return \"Command executed successfully\"\n",
- " except Exception as e:\n",
- " return f\"Error executing command: {e}\"\n",
+ " return self._run_command_in_host_env(command)\n",
"\n",
" def _run_command_in_host_env(self, command):\n",
" try:\n",
@@ -246,10 +403,86 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 27,
"id": "5901d958",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Actor 1 IP: 10.132.0.152\n",
+ "Actor 2 IP: 10.132.0.153\n",
+ "Actor 1 command result: [2025-01-07 16:29:35,112] [WARNING] [real_accelerator.py:162:get_accelerator] Setting accelerator to CPU. If you have GPU or other accelerator, we were unable to detect it.\n",
+ "[2025-01-07 16:29:35,124] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cpu (auto detect)\n",
+ "[INFO|2025-01-07 16:29:39] llamafactory.cli:157 >> Initializing distributed tasks at: 10.132.0.152:29500\n",
+ "[2025-01-07 16:29:50,342] [WARNING] [real_accelerator.py:162:get_accelerator] Setting accelerator to CPU. If you have GPU or other accelerator, we were unable to detect it.\n",
+ "[2025-01-07 16:29:50,354] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cpu (auto detect)\n",
+ "[INFO|2025-01-07 16:29:52] llamafactory.hparams.parser:355 >> Process rank: 0, device: cpu:0, n_gpu: 1, distributed training: True, compute dtype: torch.bfloat16\n",
+ "[INFO|2025-01-07 16:29:52] llamafactory.data.template:157 >> Add pad token: \n",
+ "[INFO|2025-01-07 16:29:52] llamafactory.data.loader:157 >> Loading dataset identity.json...\n",
+ "[INFO|2025-01-07 16:29:53] llamafactory.data.loader:157 >> Loading dataset alpaca_en_demo.json...\n",
+ "training example:\n",
+ "input_ids:\n",
+ "[1, 836, 1389, 2313, 31908, 23980, 836, 31873, 1389, 2313, 31908, 16644, 31905, 312, 705, 16717, 3227, 28035, 363, 7421, 8825, 3321, 417, 16717, 10935, 2338, 31843, 1035, 473, 312, 2803, 365, 31822, 31824, 16346, 31902, 2]\n",
+ "inputs:\n",
+ " [INST] hi [/INST] Hello! I am {{name}}, an AI assistant developed by {{author}}. How can I assist you today?\n",
+ "label_ids:\n",
+ "[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 16644, 31905, 312, 705, 16717, 3227, 28035, 363, 7421, 8825, 3321, 417, 16717, 10935, 2338, 31843, 1035, 473, 312, 2803, 365, 31822, 31824, 16346, 31902, 2]\n",
+ "labels:\n",
+ "Hello! I am {{name}}, an AI assistant developed by {{author}}. How can I assist you today?\n",
+ "[INFO|2025-01-07 16:30:01] llamafactory.model.model_utils.checkpointing:157 >> Gradient checkpointing enabled.\n",
+ "[INFO|2025-01-07 16:30:01] llamafactory.model.model_utils.attention:157 >> Using torch SDPA for faster training and inference.\n",
+ "[INFO|2025-01-07 16:30:01] llamafactory.model.adapter:157 >> Upcasting trainable params to float32.\n",
+ "[INFO|2025-01-07 16:30:01] llamafactory.model.adapter:157 >> Fine-tuning method: LoRA\n",
+ "[INFO|2025-01-07 16:30:01] llamafactory.model.model_utils.misc:157 >> Found linear modules: down_proj,v_proj,k_proj,gate_proj,q_proj,up_proj,o_proj\n",
+ "[INFO|2025-01-07 16:30:01] llamafactory.model.loader:157 >> trainable params: 94,208 || all params: 4,715,584 || trainable%: 1.9978\n",
+ "{'train_runtime': 11.9649, 'train_samples_per_second': 4.513, 'train_steps_per_second': 0.251, 'train_loss': 12.782352447509766, 'epoch': 2.67}\n",
+ "***** train metrics *****\n",
+ " epoch = 2.6667\n",
+ " total_flos = 93GF\n",
+ " train_loss = 12.7824\n",
+ " train_runtime = 0:00:11.96\n",
+ " train_samples_per_second = 4.513\n",
+ " train_steps_per_second = 0.251\n",
+ "[WARNING|2025-01-07 16:30:14] llamafactory.extras.ploting:162 >> No metric loss to plot.\n",
+ "[WARNING|2025-01-07 16:30:14] llamafactory.extras.ploting:162 >> No metric eval_loss to plot.\n",
+ "[WARNING|2025-01-07 16:30:14] llamafactory.extras.ploting:162 >> No metric eval_accuracy to plot.\n",
+ "***** eval metrics *****\n",
+ " epoch = 2.6667\n",
+ " eval_loss = 7.5598\n",
+ " eval_runtime = 0:00:00.17\n",
+ " eval_samples_per_second = 11.622\n",
+ " eval_steps_per_second = 5.811\n",
+ "\n",
+ "Actor 2 command result: [2025-01-07 16:29:34,217] [WARNING] [real_accelerator.py:162:get_accelerator] Setting accelerator to CPU. If you have GPU or other accelerator, we were unable to detect it.\n",
+ "[2025-01-07 16:29:34,228] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cpu (auto detect)\n",
+ "[INFO|2025-01-07 16:29:37] llamafactory.cli:157 >> Initializing distributed tasks at: 10.132.0.152:29500\n",
+ "[2025-01-07 16:29:48,299] [WARNING] [real_accelerator.py:162:get_accelerator] Setting accelerator to CPU. If you have GPU or other accelerator, we were unable to detect it.\n",
+ "[2025-01-07 16:29:48,310] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cpu (auto detect)\n",
+ "[INFO|2025-01-07 16:29:52] llamafactory.hparams.parser:355 >> Process rank: 0, device: cpu:0, n_gpu: 1, distributed training: True, compute dtype: torch.bfloat16\n",
+ "[INFO|2025-01-07 16:29:52] llamafactory.data.template:157 >> Add pad token: \n",
+ "[INFO|2025-01-07 16:29:52] llamafactory.data.loader:157 >> Loading dataset identity.json...\n",
+ "[INFO|2025-01-07 16:29:52] llamafactory.data.loader:157 >> Loading dataset alpaca_en_demo.json...\n",
+ "training example:\n",
+ "input_ids:\n",
+ "[1, 836, 1389, 2313, 31908, 23980, 836, 31873, 1389, 2313, 31908, 16644, 31905, 312, 705, 16717, 3227, 28035, 363, 7421, 8825, 3321, 417, 16717, 10935, 2338, 31843, 1035, 473, 312, 2803, 365, 31822, 31824, 16346, 31902, 2]\n",
+ "inputs:\n",
+ " [INST] hi [/INST] Hello! I am {{name}}, an AI assistant developed by {{author}}. How can I assist you today?\n",
+ "label_ids:\n",
+ "[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 16644, 31905, 312, 705, 16717, 3227, 28035, 363, 7421, 8825, 3321, 417, 16717, 10935, 2338, 31843, 1035, 473, 312, 2803, 365, 31822, 31824, 16346, 31902, 2]\n",
+ "labels:\n",
+ "Hello! I am {{name}}, an AI assistant developed by {{author}}. How can I assist you today?\n",
+ "[INFO|2025-01-07 16:30:00] llamafactory.model.model_utils.checkpointing:157 >> Gradient checkpointing enabled.\n",
+ "[INFO|2025-01-07 16:30:00] llamafactory.model.model_utils.attention:157 >> Using torch SDPA for faster training and inference.\n",
+ "[INFO|2025-01-07 16:30:00] llamafactory.model.adapter:157 >> Upcasting trainable params to float32.\n",
+ "[INFO|2025-01-07 16:30:00] llamafactory.model.adapter:157 >> Fine-tuning method: LoRA\n",
+ "[INFO|2025-01-07 16:30:01] llamafactory.model.model_utils.misc:157 >> Found linear modules: o_proj,q_proj,v_proj,up_proj,down_proj,gate_proj,k_proj\n",
+ "[INFO|2025-01-07 16:30:01] llamafactory.model.loader:157 >> trainable params: 94,208 || all params: 4,715,584 || trainable%: 1.9978\n",
+ "\n"
+ ]
+ }
+ ],
"source": [
"#call the above cell as a remote ray function\n",
"actor1 = NetworkCommandActor.remote()\n",
@@ -288,23 +521,50 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 15,
"id": "5f36db0f-31f6-4373-9503-dc3c1c4c3f57",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Ray Cluster: 'llama-factory-test' has successfully been deleted\n"
+ ]
+ }
+ ],
"source": [
"cluster.down()"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 16,
"id": "0d41b90e",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'Successfully logged out of https://api.demo-01-rhsys.wzhlab.top:6443'"
+ ]
+ },
+ "execution_count": 16,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
"source": [
"auth.logout()"
]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "1029b8b8-56b9-4caf-9396-396ec54f4877",
+ "metadata": {},
+ "outputs": [],
+ "source": []
}
],
"metadata": {