Add automatic library installation in after optimization test

Author: ReturnToFirst

Diff for: README.md

@@ -9,12 +9,13 @@ This code samples show unoptimized/optimized tensorflow workflow.
 
 ## Requirements
 
+### Hardware Requirements
 * x86-64 (AMD64) CPU
 * RAM >= 8GiB
 * NVIDIA [Computer Capability](https://developer.nvidia.com/cuda-gpus) 7.0+ GPUs
     * GPU memory > 12GiB for default batch size
 
-### Test Environment
+#### Test Environment
 * CPU : Intel(R) Xeon(R) Gold 5218R
 * GPU : 2x A100 80GB PCI-E
 * RAM : 255GiB
@@ -30,8 +31,8 @@ This code samples show unoptimized/optimized tensorflow workflow.
 1. Clone this repo with submodule
    ```
    git clone --recursive https://github.com/ReturnToFirst/FastTFWorkflow.git
-   ```
-2. Compare performance between unoptimized/optimized workflow
+
+3. Compare performance between unoptimized/optimized workflow
 
 ### For advanced users
 

Diff for: after_optimization.ipynb

@@ -28,13 +28,49 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import tensorflow as tf\n",
-    "from nvidia.dali import pipeline_def, fn, types\n",
-    "import nvidia.dali.plugin.tf as dali_tf\n",
-    "\n",
+    "# This package will use for install uninstalled package\n",
+    "import subprocess\n",
+    "\n",
+    "# Import TensorFlow and install if not installed\n",
+    "try:\n",
+    "    import tensorflow as tf\n",
+    "except(ModuleNotFoundError):\n",
+    "    subprocess.run([\"pip3\", \"install\", \"tensorflow\"])\n",
+    "    import tensorflow as tf\n",
+    "\n",
+    "# Import NVIDIA DALI and install if not installed\n",
+    "try:\n",
+    "    from nvidia.dali import pipeline_def, fn, types\n",
+    "except(ModuleNotFoundError):\n",
+    "    import re\n",
+    "\n",
+    "    nv_smi = subprocess.run([\"nvidia-smi\"], stdout=subprocess.PIPE).stdout\n",
+    "    cuda_version = float(re.search(r'CUDA\\sVersion:\\s+(\\d+\\.\\d+)', nv_smi.decode()).group(1))\n",
+    "    if 12 <= cuda_version:\n",
+    "        subprocess.run(['pip' 'install' '--extra-index-url' 'https://developer.download.nvidia.com/compute/redist' '--upgrade nvidia-dali-cuda120'])\n",
+    "    else:\n",
+    "        subprocess.run(['pip' 'install' '--extra-index-url' 'https://developer.download.nvidia.com/compute/redist' '--upgrade nvidia-dali-cuda110'])\n",
+    "\n",
+    "    from nvidia.dali import pipeline_def, fn, types\n",
+    "\n",
+    "# Import NVIDIA DALI TensorFlow plugin and install if not installed\n",
+    "try:\n",
+    "    import nvidia.dali.plugin.tf as dali_tf\n",
+    "    \n",
+    "except(ModuleNotFoundError):\n",
+    "    if 12 <= cuda_version:\n",
+    "        subprocess.run(['pip' 'install' '--extra-index-url' 'https://developer.download.nvidia.com/compute/redist' '--upgrade nvidia-dali-tf-plugin-cuda120'])\n",
+    "    else:\n",
+    "        subprocess.run(['pip' 'install' '--extra-index-url' 'https://developer.download.nvidia.com/compute/redist' '--upgrade nvidia-dali-tf-plugin-cuda110'])\n",
+    "    import nvidia.dali.plugin.tf as dali_tf\n",
+    "\n",
+    "\n",
+    "# Import Python internal modules\n",
     "import os\n",
     "import glob\n",
-    "import math\n"
+    "import math\n",
+    "import subprocess\n",
+    "import re"
    ]
   },
   {
@@ -296,7 +332,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.11"
+   "version": "3.8.16"
   },
   "orig_nbformat": 4
  },

Diff for: after_optimization_multi.ipynb

@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Example : Optimized Pytorch workflow\n",
+    "# Example : Optimized TensorFlow workflow\n",
     "\n",
     "## Summary\n",
     "This example is optimized pytorch training workflow.\n",