progress

.gitignore

@@ -6,5 +6,6 @@ fastbook
 *.png
 *.gif
 *.jpeg
-pytorch/**/jupyter-settings
-**/workspaces
+#**/pytorch/jupyter-settings
+**/workspaces
+**/user-settings

pytorch/.env

@@ -0,0 +1,2 @@
+ROOT_DIR=/opt/jupyter_gpu/pytorch
+JUPYTER_PORT=8888

pytorch/Dockerfile

@@ -0,0 +1,28 @@
+# -------------------------------------------------------
+# Relies on JUPYTER_PORT being set in docker-compose.yml
+# -------------------------------------------------------
+FROM pytorch/pytorch:latest
+
+# Install JupyterLab
+RUN pip install jupyterlab
+
+# Install additional packages
+RUN pip install plotly
+RUN pip install fastbook
+
+# Install additional applications
+RUN apt update
+RUN apt-get install graphviz -y
+
+# Set environment variables, etc.
+#ENV MY_ENV_VAR=myvalue
+
+# Set the working directory
+WORKDIR /workspace
+
+# Expose the port for JupyterLab
+EXPOSE ${JUPYTER_PORT}
+
+# Command to run JupyterLab
+CMD ["jupyter-lab", "--ip=0.0.0.0", "--port=8888", "--no-browser", "--allow-root", "--NotebookApp.token=''"]
+

pytorch/docker-compose.yml

@@ -0,0 +1,25 @@
+version: '3.8'
+
+#==================================================
+# Relies on the file `.env` content for varables:
+#    ROOT_DIR
+#    JUPYTER_PORT
+#==================================================
+
+services:
+  jupyter:
+    user: "oleg"
+    build: ${ROOT_DIR}
+    image: cvtt/jupyter_gpu_pt:v1.0.8
+    container_name: jupyter_gpu_pt
+    runtime: nvidia
+    environment:
+      - JUPYTER_ENABLE_LAB=yes
+    volumes:
+      - ${ROOT_DIR}/notebooks:/workspace
+      - ${ROOT_DIR}/jupyter_settings/user-settings:/root/.jupyter/lab/user-settings
+      - ${ROOT_DIR}/jupyter_settings/workspaces:/root/.jupyter/lab/workspaces
+      - ${ROOT_DIR}/.cache/torch:/root/.cache/torch
+    ports:
+      - "${JUPYTER_PORT}:${JUPYTER_PORT}"
+    shm_size: "8gb"

pytorch/notebooks/oleg/Testing GPU.ipynb

@@ -0,0 +1,126 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "6b269e64-be58-43b5-ad60-0fbd1d37861a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CUDA is available. Number of GPUs: 1\n",
+      "GPU Name: NVIDIA GeForce RTX 3060\n"
+     ]
+    }
+   ],
+   "source": [
+    "import torch\n",
+    "\n",
+    "# Check if CUDA is available\n",
+    "if torch.cuda.is_available():\n",
+    "    print(f\"CUDA is available. Number of GPUs: {torch.cuda.device_count()}\")\n",
+    "    print(f\"GPU Name: {torch.cuda.get_device_name(0)}\")\n",
+    "else:\n",
+    "    print(\"CUDA is not available. No GPU detected.\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "97906ea2-b284-4966-9c11-b8629f053815",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import plotly"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "7313a620-a0eb-4207-a12a-90aeee3cd980",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'3.10.13 (main, Sep 11 2023, 13:44:35) [GCC 11.2.0]'"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import sys\n",
+    "sys.version"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "95d9a2e6-3464-4dbe-9a97-0c2d5eb34193",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "environ{'PATH': '/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin',\n",
+       "        'HOSTNAME': '1fc69c311e22',\n",
+       "        'JUPYTER_ENABLE_LAB': 'yes',\n",
+       "        'NVIDIA_VISIBLE_DEVICES': 'all',\n",
+       "        'NVIDIA_DRIVER_CAPABILITIES': 'compute,utility',\n",
+       "        'LD_LIBRARY_PATH': '/usr/local/nvidia/lib:/usr/local/nvidia/lib64',\n",
+       "        'PYTORCH_VERSION': '2.2.1',\n",
+       "        'HOME': '/root',\n",
+       "        'LC_CTYPE': 'C.UTF-8',\n",
+       "        'JPY_SESSION_NAME': '/workspace/oleg/Testing GPU.ipynb',\n",
+       "        'JPY_PARENT_PID': '1',\n",
+       "        'PYDEVD_USE_FRAME_EVAL': 'NO',\n",
+       "        'TERM': 'xterm-color',\n",
+       "        'CLICOLOR': '1',\n",
+       "        'FORCE_COLOR': '1',\n",
+       "        'CLICOLOR_FORCE': '1',\n",
+       "        'PAGER': 'cat',\n",
+       "        'GIT_PAGER': 'cat',\n",
+       "        'MPLBACKEND': 'module://matplotlib_inline.backend_inline',\n",
+       "        'CUDA_MODULE_LOADING': 'LAZY'}"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import os\n",
+    "import pandas as pd\n",
+    "import matplotlib\n",
+    "os.environ"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}