gpu_test.ipynb

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   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "nvcc: NVIDIA (R) Cuda compiler driver\n",
      "Copyright (c) 2005-2018 NVIDIA Corporation\n",
      "Built on Sat_Aug_25_21:08:04_Central_Daylight_Time_2018\n",
      "Cuda compilation tools, release 10.0, V10.0.130\n"
     ]
    }
   ],
   "source": [
    "!nvcc --version"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#import os\n",
    "#os.environ[\"CUDA_DEVICE_ORDER\"] = \"PCI_BUS_ID\" \n",
    "# The GPU id to use, usually either \"0\" or \"1\";\n",
    "#os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"1\"  # use id from $ nvidia-smi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Keras Version 2.2.5\n",
      "Tensorflow Version 1.15.0\n"
     ]
    }
   ],
   "source": [
    "# Print version\n",
    "print(\"Keras Version\", keras.__version__)\n",
    "print(\"Tensorflow Version\", tf.__version__)\n",
    "\n",
    "# use this version\n",
    "#Keras Version 2.3.1\n",
    "#Tensorflow Version 2.0.0\n",
    "\n",
    "# conda install -c conda-forge keras\n",
    "# conda install -c anaconda tensorflow-gpu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['/device:GPU:0']\n"
     ]
    }
   ],
   "source": [
    "# GPU test\n",
    "from tensorflow.python.client import device_lib\n",
    "def get_available_gpus():\n",
    "    local_device_protos = device_lib.list_local_devices()\n",
    "    return [x.name for x in local_device_protos if x.device_type == 'GPU']\n",
    "\n",
    "print(get_available_gpus())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[name: \"/device:CPU:0\"\n",
       " device_type: \"CPU\"\n",
       " memory_limit: 268435456\n",
       " locality {\n",
       " }\n",
       " incarnation: 7058356687516318937, name: \"/device:GPU:0\"\n",
       " device_type: \"GPU\"\n",
       " memory_limit: 9108882063\n",
       " locality {\n",
       "   bus_id: 1\n",
       "   links {\n",
       "   }\n",
       " }\n",
       " incarnation: 7427185872298565116\n",
       " physical_device_desc: \"device: 0, name: GeForce RTX 2080 Ti, pci bus id: 0000:01:00.0, compute capability: 7.5\"]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get compute specs\n",
    "from tensorflow.python.client import device_lib\n",
    "device_lib.list_local_devices()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.test.is_built_with_cuda()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.test.is_gpu_available()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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