Not Normal

not_normal.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "462ffaa0",
   "metadata": {},
   "source": [
    "### Are NN Weights Distributed Normally?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97baead2",
   "metadata": {},
   "source": [
    "Since pretrained neural network weights usually have a zero-centered normal distribution with standard deviation σ (see Appendix F), we can transform all weights to a single fixed distribution by scaling σ such that the distribution fits exactly into the range of our data type. \n",
    "\n",
    "From: https://arxiv.org/pdf/2305.14314.pdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "cf34882d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import torchvision.models as models\n",
    "import scipy.stats as stats\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import statsmodels.api as sm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "53df9a97",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/soodoku/opt/anaconda3/lib/python3.9/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.\n",
      "  warnings.warn(\n",
      "/Users/soodoku/opt/anaconda3/lib/python3.9/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=ResNet18_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet18_Weights.DEFAULT` to get the most up-to-date weights.\n",
      "  warnings.warn(msg)\n",
      "/Users/soodoku/opt/anaconda3/lib/python3.9/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=ResNet34_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet34_Weights.DEFAULT` to get the most up-to-date weights.\n",
      "  warnings.warn(msg)\n",
      "/Users/soodoku/opt/anaconda3/lib/python3.9/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=ResNet50_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet50_Weights.DEFAULT` to get the most up-to-date weights.\n",
      "  warnings.warn(msg)\n",
      "/Users/soodoku/opt/anaconda3/lib/python3.9/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=ResNet101_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet101_Weights.DEFAULT` to get the most up-to-date weights.\n",
      "  warnings.warn(msg)\n",
      "/Users/soodoku/opt/anaconda3/lib/python3.9/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=ResNet152_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet152_Weights.DEFAULT` to get the most up-to-date weights.\n",
      "  warnings.warn(msg)\n",
      "/Users/soodoku/opt/anaconda3/lib/python3.9/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=VGG11_Weights.IMAGENET1K_V1`. You can also use `weights=VGG11_Weights.DEFAULT` to get the most up-to-date weights.\n",
      "  warnings.warn(msg)\n",
      "/Users/soodoku/opt/anaconda3/lib/python3.9/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=VGG13_Weights.IMAGENET1K_V1`. You can also use `weights=VGG13_Weights.DEFAULT` to get the most up-to-date weights.\n",
      "  warnings.warn(msg)\n",
      "/Users/soodoku/opt/anaconda3/lib/python3.9/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=VGG16_Weights.IMAGENET1K_V1`. You can also use `weights=VGG16_Weights.DEFAULT` to get the most up-to-date weights.\n",
      "  warnings.warn(msg)\n",
      "/Users/soodoku/opt/anaconda3/lib/python3.9/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=VGG19_Weights.IMAGENET1K_V1`. You can also use `weights=VGG19_Weights.DEFAULT` to get the most up-to-date weights.\n",
      "  warnings.warn(msg)\n",
      "/Users/soodoku/opt/anaconda3/lib/python3.9/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=AlexNet_Weights.IMAGENET1K_V1`. You can also use `weights=AlexNet_Weights.DEFAULT` to get the most up-to-date weights.\n",
      "  warnings.warn(msg)\n",
      "/Users/soodoku/opt/anaconda3/lib/python3.9/site-packages/scipy/stats/_morestats.py:1800: UserWarning: p-value may not be accurate for N > 5000.\n",
      "  warnings.warn(\"p-value may not be accurate for N > 5000.\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       Model Distribution\n",
      "0   ResNet18   Not Normal\n",
      "1   ResNet34   Not Normal\n",
      "2   ResNet50   Not Normal\n",
      "3  ResNet101   Not Normal\n",
      "4  ResNet152   Not Normal\n",
      "5      VGG11   Not Normal\n",
      "6      VGG13   Not Normal\n",
      "7      VGG16   Not Normal\n",
      "8      VGG19   Not Normal\n",
      "9    AlexNet   Not Normal\n"
     ]
    }
   ],
   "source": [
    "# Function to load computer vision models\n",
    "def load_computer_vision_models():\n",
    "    model_resnet18 = models.resnet18(pretrained=True)\n",
    "    model_resnet34 = models.resnet34(pretrained=True)\n",
    "    model_resnet50 = models.resnet50(pretrained=True)\n",
    "    model_resnet101 = models.resnet101(pretrained=True)\n",
    "    model_resnet152 = models.resnet152(pretrained=True)\n",
    "    model_vgg11 = models.vgg11(pretrained=True)\n",
    "    model_vgg13 = models.vgg13(pretrained=True)\n",
    "    model_vgg16 = models.vgg16(pretrained=True)\n",
    "    model_vgg19 = models.vgg19(pretrained=True)\n",
    "    model_alexnet = models.alexnet(pretrained=True)\n",
    "\n",
    "    computer_vision_models = [\n",
    "        (\"ResNet18\", model_resnet18),\n",
    "        (\"ResNet34\", model_resnet34),\n",
    "        (\"ResNet50\", model_resnet50),\n",
    "        (\"ResNet101\", model_resnet101),\n",
    "        (\"ResNet152\", model_resnet152),\n",
    "        (\"VGG11\", model_vgg11),\n",
    "        (\"VGG13\", model_vgg13),\n",
    "        (\"VGG16\", model_vgg16),\n",
    "        (\"VGG19\", model_vgg19),\n",
    "        (\"AlexNet\", model_alexnet)\n",
    "    ]\n",
    "    return computer_vision_models\n",
    "\n",
    "# Function to load NLP models\n",
    "def load_nlp_models():\n",
    "    model_bert = torch.hub.load('huggingface/pytorch-transformers', 'bert-base-uncased')\n",
    "    model_gpt = torch.hub.load('huggingface/pytorch-transformers', 'gpt2')\n",
    "    model_roberta = torch.hub.load('huggingface/pytorch-transformers', 'roberta-base')\n",
    "    model_distilbert = torch.hub.load('huggingface/pytorch-transformers', 'distilbert-base-uncased')\n",
    "    model_t5 = torch.hub.load('huggingface/pytorch-transformers', 't5-small')\n",
    "    model_albert = torch.hub.load('huggingface/pytorch-transformers', 'albert-base-v2')\n",
    "    model_bart = torch.hub.load('huggingface/pytorch-transformers', 'facebook/bart-base')\n",
    "    model_xlnet = torch.hub.load('huggingface/pytorch-transformers', 'xlnet-base-cased')\n",
    "    model_electra = torch.hub.load('huggingface/pytorch-transformers', 'google/electra-small-discriminator')\n",
    "\n",
    "    nlp_models = [\n",
    "        (\"BERT\", model_bert),\n",
    "        (\"GPT2\", model_gpt),\n",
    "        (\"RoBERTa\", model_roberta),\n",
    "        (\"DistilBERT\", model_distilbert),\n",
    "        (\"T5\", model_t5),\n",
    "        (\"ALBERT\", model_albert),\n",
    "        (\"BART\", model_bart),\n",
    "        (\"XLNet\", model_xlnet),\n",
    "        (\"ELECTRA\", model_electra)\n",
    "    ]\n",
    "    return nlp_models\n",
    "\n",
    "# Function to perform the Shapiro-Wilk test\n",
    "def perform_shapiro_wilk_test(model_name, model):\n",
    "    # Extract all the parameters (weights) from the model\n",
    "    weights = []\n",
    "    for name, param in model.named_parameters():\n",
    "        if 'weight' in name:\n",
    "            weights.extend(param.cpu().detach().numpy().flatten())\n",
    "\n",
    "    # Perform the Shapiro-Wilk test\n",
    "    p_value = stats.shapiro(weights).pvalue\n",
    "\n",
    "    # Check if the p-value is less than the significance level (e.g., 0.05)\n",
    "    if p_value < 0.05:\n",
    "        return \"Not Normal\"\n",
    "    else:\n",
    "        return \"Normal\"\n",
    "\n",
    "# Load computer vision models\n",
    "computer_vision_models = load_computer_vision_models()\n",
    "\n",
    "# Load NLP models\n",
    "#nlp_models = load_nlp_models()\n",
    "\n",
    "# Perform the Shapiro-Wilk test for each model\n",
    "all_models = computer_vision_models #+ nlp_models\n",
    "results = [(model_name, perform_shapiro_wilk_test(model_name, model)) for model_name, model in all_models]\n",
    "\n",
    "# Create a summary table\n",
    "summary_table = pd.DataFrame(results, columns=[\"Model\", \"Distribution\"])\n",
    "print(summary_table)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7458c790",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: ResNet18, Distribution: 0.0\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: ResNet34, Distribution: 0.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: ResNet50, Distribution: 0.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: ResNet101, Distribution: 0.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: ResNet152, Distribution: 0.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: VGG11, Distribution: 0.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: VGG13, Distribution: 0.0\n"
     ]
    }
   ],
   "source": [
    "# Function to perform the Shapiro-Wilk test\n",
    "def perform_shapiro_wilk_test(model_name, model):\n",
    "    # Extract all the parameters (weights) from the model\n",
    "    weights = []\n",
    "    for name, param in model.named_parameters():\n",
    "        if 'weight' in name:\n",
    "            weights.extend(param.cpu().detach().numpy().flatten())\n",
    "\n",
    "    # Perform the Shapiro-Wilk test\n",
    "    stat, p = stats.shapiro(weights)\n",
    "    return p\n",
    "\n",
    "# Function to plot Q-Q plot\n",
    "def plot_qq_plot(model_name, model):\n",
    "    # Extract all the parameters (weights) from the model\n",
    "    weights = []\n",
    "    for name, param in model.named_parameters():\n",
    "        if 'weight' in name:\n",
    "            weights.extend(param.cpu().detach().numpy().flatten())\n",
    "\n",
    "    # Convert the list to a numpy array\n",
    "    weights = np.array(weights)\n",
    "\n",
    "    # Create a Q-Q plot\n",
    "    sm.qqplot(weights, line='s')\n",
    "    plt.title(f\"Q-Q Plot for {model_name}\")\n",
    "    plt.xlabel(\"Theoretical Quantiles\")\n",
    "    plt.ylabel(\"Sample Quantiles\")\n",
    "    plt.show()\n",
    "\n",
    "# Load computer vision models\n",
    "computer_vision_models = load_computer_vision_models()\n",
    "\n",
    "# Load NLP models\n",
    "#nlp_models = load_nlp_models()\n",
    "\n",
    "# Perform the Shapiro-Wilk test and plot Q-Q plots for each model\n",
    "all_models = computer_vision_models #+ nlp_models\n",
    "for model_name, model in all_models:\n",
    "    print(f\"Model: {model_name}, Distribution: {perform_shapiro_wilk_test(model_name, model)}\")\n",
    "    plot_qq_plot(model_name, model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bd71f2c9",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}