tutorials/ray/notebooks/ray_basic_1.ipynb

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   "source": [
    "# %%bash\n",
    "# pip install \"ray[client]\"==2.9.0"
   ]
  },
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<td style=\"text-align: left\"><b>Python version:</b></td>\n        <td style=\"text-align: left\"><b>3.8.13</b></td>\n    </tr>\n    <tr>\n        <td style=\"text-align: left\"><b>Ray version:</b></td>\n        <td style=\"text-align: left\"><b>2.7.0</b></td>\n    </tr>\n    <tr>\n    <td style=\"text-align: left\"><b>Dashboard:</b></td>\n    <td style=\"text-align: left\"><b><a href=\"http://10.244.0.67:8265\" target=\"_blank\">http://10.244.0.67:8265</a></b></td>\n</tr>\n\n</table>\n\n    </div>\n</div>\n"
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import ray\n",
    "\n",
    "# ray.init(address=\"ray://raycluster-kuberay-head-svc.default.svc.cluster.local:10001\")\n",
    "ray.init(address=\"ray://localhost:10001\")"
   ]
  },
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    {
     "name": "stdout",
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     "text": [
      "{'CPU': 2.0, 'memory': 3000000000.0, 'GPU': 2.0, 'node:10.244.0.67': 1.0, 'node:__internal_head__': 1.0, 'accelerator_type:G': 2.0, 'object_store_memory': 652052889.0, 'node:10.244.0.66': 1.0}\n"
     ]
    }
   ],
   "source": [
    "print(ray.cluster_resources())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5bd9efcd-caac-436a-94ca-20ea9a7b8b1c",
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 1, 4, 9]\n"
     ]
    }
   ],
   "source": [
    "# Try Ray task\n",
    "@ray.remote(num_cpus=1)\n",
    "def f(x):\n",
    "    return x * x\n",
    "\n",
    "futures = [f.remote(i) for i in range(4)]\n",
    "print(ray.get(futures)) # [0, 1, 4, 9]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9102cde5-c9db-46d2-a961-f19c1d1e6871",
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    "ExecuteTime": {
     "end_time": "2024-01-12T05:59:04.698268355Z",
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   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 1, 1, 1]\n"
     ]
    }
   ],
   "source": [
    "# Try Ray actor\n",
    "@ray.remote(num_cpus=1)\n",
    "class Counter(object):\n",
    "    def __init__(self):\n",
    "        self.n = 0\n",
    "\n",
    "    def increment(self):\n",
    "        self.n += 1\n",
    "\n",
    "    def read(self):\n",
    "        return self.n\n",
    "\n",
    "counters = [Counter.remote() for i in range(4)]\n",
    "[c.increment.remote() for c in counters]\n",
    "futures = [c.read.remote() for c in counters]\n",
    "print(ray.get(futures)) # [1, 1, 1, 1]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e065366-9b19-44a3-bd8e-db36f91d6fb1",
   "metadata": {},
   "source": [
    "### Access Ray dashboard\n",
    "\n",
    "Run a port-forward from your local computer to the ray dashboard:\n",
    "\n",
    "`kubectl port-forward svc/raycluster-kuberay-head-svc 8265:8265 -n default`\n",
    "\n",
    "Go to http://localhost:8265/ and you should see the Ray dashboard."
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Connect to Ray cluster from local machine\n",
    "\n",
    "> The version of the Ray client must match the version of the Ray cluster (2.9.0).\n",
    "\n",
    "```bash\n",
    "conda create -n ray-env python=3.8.10\n",
    "conda activate ray-env\n",
    "pip install \"ray[client]\"==2.9.0\n",
    "```\n",
    "\n",
    "Run a port forwarding to the Ray head service:\n",
    "\n",
    "```bash\n",
    "kubectl port-forward svc/raycluster-kuberay-head-svc 10001:10001 -n default\n",
    "```\n",
    "\n",
    "```python\n",
    "import ray\n",
    "\n",
    "ray.init(address=\"ray://localhost:10001\")\n",
    "print(ray.cluster_resources())\n",
    "```"
   ],
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