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Nic-MaNic-Ma
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[DLMED] update transforms and AMP notebooks
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4 files changed

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‎3d_image_transforms.ipynb

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‎automatic_mixed_precision.ipynb

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"This tutorial shows how to apply the automatic mixed precision (AMP) feature of PyTorch to training and validation programs. \n",
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"It's modified from the Spleen 3D segmentation tutorial notebook, and compares the training speed and memory usage with/without AMP.\n",
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"\n",
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"The Spleen dataset can be downloaded from http://medicaldecathlon.com/."
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"The Spleen dataset can be downloaded from http://medicaldecathlon.com/.\n",
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"\n",
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"[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Project-MONAI/MONAI/blob/master/examples/notebooks/automatic_mixed_precision.ipynb)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Set MSD Spleen dataset path"
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"## Setup environment"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Note: you may need to restart the kernel to use updated packages.\n"
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]
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}
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],
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"source": [
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"%pip install -qU \"monai[gdown, nibabel]\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Note: you may need to restart the kernel to use updated packages.\n"
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]
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}
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],
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"source": [
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"%pip install -qU matplotlib\n",
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"%matplotlib inline"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Setup data directory\n",
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"\n",
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"You can specify a directory with the `MONAI_DATA_DIRECTORY` environment variable. \n",
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"This allows you to save results and reuse downloads. \n",
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"If not specified a temporary directory will be used."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"root dir is: /workspace/data/medical\n"
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]
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}
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],
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"source": [
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"directory = os.environ.get(\"MONAI_DATA_DIRECTORY\")\n",
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"root_dir = tempfile.mkdtemp() if directory is None else directory\n",
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"print(f\"root dir is: {root_dir}\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Download dataset\n",
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"\n",
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"Downloads and extracts the Decathlon Spleen dataset."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"resource = \"https://drive.google.com/uc?id=1jzeNU1EKnK81PyTsrx0ujfNl-t0Jo8uE\"\n",
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"md5 = \"410d4a301da4e5b2f6f86ec3ddba524e\"\n",
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"\n",
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"compressed_file = os.path.join(root_dir, \"Task09_Spleen.tar\")\n",
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"data_root = os.path.join(root_dir, \"Task09_Spleen\")\n",
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"if not os.path.exists(data_root):\n",
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" download_and_extract(resource, compressed_file, root_dir, md5)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Set MSD Spleen dataset path"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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"data_root = '/workspace/data/medical/Task09_Spleen'\n",
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"train_images = sorted(glob.glob(os.path.join(data_root, 'imagesTr', '*.nii.gz')))\n",
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"train_labels = sorted(glob.glob(os.path.join(data_root, 'labelsTr', '*.nii.gz')))\n",
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"data_dicts = [{'image': image_name, 'label': label_name}\n",
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 7,
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"metadata": {},
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"outputs": [],
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"source": [
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 8,
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"metadata": {
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"scrolled": true
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},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Expected memory usage during training with AMP"
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"## Check the memory usage during training with AMP"
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]
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},
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{
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"cell_type": "markdown",
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"cell_type": "code",
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"execution_count": 14,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Tue Aug 11 05:17:40 2020 \r\n",
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"+-----------------------------------------------------------------------------+\r\n",
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"| NVIDIA-SMI 440.44 Driver Version: 440.44 CUDA Version: 10.2 |\r\n",
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"|-------------------------------+----------------------+----------------------+\r\n",
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"| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\r\n",
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"| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\r\n",
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"|===============================+======================+======================|\r\n",
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"| 0 Tesla V100-PCIE... Off | 00000000:02:00.0 Off | 0 |\r\n",
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"| N/A 38C P0 36W / 250W | 3329MiB / 32510MiB | 0% Default |\r\n",
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"+-------------------------------+----------------------+----------------------+\r\n",
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"| 1 Tesla V100-PCIE... Off | 00000000:03:00.0 Off | 0 |\r\n",
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"| N/A 40C P0 38W / 250W | 4722MiB / 32510MiB | 0% Default |\r\n",
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"+-------------------------------+----------------------+----------------------+\r\n",
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" \r\n",
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"+-----------------------------------------------------------------------------+\r\n",
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"| Processes: GPU Memory |\r\n",
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"| GPU PID Type Process name Usage |\r\n",
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"|=============================================================================|\r\n",
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"+-----------------------------------------------------------------------------+\r\n"
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]
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}
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],
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"source": [
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"![image](./images/mem_amp_on.png)"
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"! nvidia-smi"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Expected memory usage during training without AMP"
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"## Check the memory usage during training without AMP"
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]
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},
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{
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"cell_type": "markdown",
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"cell_type": "code",
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"execution_count": 16,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Tue Aug 11 05:20:12 2020 \r\n",
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"+-----------------------------------------------------------------------------+\r\n",
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"| NVIDIA-SMI 440.44 Driver Version: 440.44 CUDA Version: 10.2 |\r\n",
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"|-------------------------------+----------------------+----------------------+\r\n",
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"| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\r\n",
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"| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\r\n",
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"|===============================+======================+======================|\r\n",
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"| 0 Tesla V100-PCIE... Off | 00000000:02:00.0 Off | 0 |\r\n",
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"| N/A 41C P0 37W / 250W | 4579MiB / 32510MiB | 0% Default |\r\n",
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"+-------------------------------+----------------------+----------------------+\r\n",
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"| 1 Tesla V100-PCIE... Off | 00000000:03:00.0 Off | 0 |\r\n",
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"| N/A 40C P0 38W / 250W | 4722MiB / 32510MiB | 0% Default |\r\n",
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"+-------------------------------+----------------------+----------------------+\r\n",
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" \r\n",
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"+-----------------------------------------------------------------------------+\r\n",
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"| Processes: GPU Memory |\r\n",
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"| GPU PID Type Process name Usage |\r\n",
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"|=============================================================================|\r\n",
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"+-----------------------------------------------------------------------------+\r\n"
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]
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}
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],
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"source": [
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"![image](./images/mem_amp_off.png)"
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"! nvidia-smi"
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]
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},
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{

‎images/mem_amp_off.png

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‎images/mem_amp_on.png

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