BuildWeightWatcher.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "view-in-github"
   },
   "source": [
    "<a href=\"https://colab.research.google.com/github/CalculatedContent/WeightWatcher/blob/master/BuildWeightWatcher.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "G1fhIR2qLyqa",
    "outputId": "71f0b97f-af33-4d8c-84bd-b2d618494023"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cloning into 'WeightWatcher'...\n",
      "remote: Enumerating objects: 2968, done.\u001b[K\n",
      "remote: Counting objects: 100% (2968/2968), done.\u001b[K\n",
      "remote: Compressing objects: 100% (1008/1008), done.\u001b[K\n",
      "remote: Total 2968 (delta 1971), reused 2946 (delta 1954), pack-reused 0\u001b[K\n",
      "Receiving objects: 100% (2968/2968), 95.12 MiB | 40.52 MiB/s, done.\n",
      "Resolving deltas: 100% (1971/1971), done.\n"
     ]
    }
   ],
   "source": [
    "!git clone https://github.com/CalculatedContent/WeightWatcher.git"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "collapsed": true,
    "id": "NPMi2ScqL3nz",
    "jupyter": {
     "outputs_hidden": true
    },
    "outputId": "4c928437-4db8-47ca-e978-931bbe34b08d",
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
      "Collecting transformers\n",
      "  Downloading transformers-4.26.0-py3-none-any.whl (6.3 MB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m6.3/6.3 MB\u001b[0m \u001b[31m83.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25hRequirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.8/dist-packages (from transformers) (6.0)\n",
      "Requirement already satisfied: requests in /usr/local/lib/python3.8/dist-packages (from transformers) (2.25.1)\n",
      "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.8/dist-packages (from transformers) (1.21.6)\n",
      "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.8/dist-packages (from transformers) (23.0)\n",
      "Collecting huggingface-hub<1.0,>=0.11.0\n",
      "  Downloading huggingface_hub-0.12.0-py3-none-any.whl (190 kB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m190.3/190.3 KB\u001b[0m \u001b[31m23.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25hRequirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.8/dist-packages (from transformers) (4.64.1)\n",
      "Collecting tokenizers!=0.11.3,<0.14,>=0.11.1\n",
      "  Downloading tokenizers-0.13.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.6 MB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.6/7.6 MB\u001b[0m \u001b[31m107.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25hRequirement already satisfied: filelock in /usr/local/lib/python3.8/dist-packages (from transformers) (3.9.0)\n",
      "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.8/dist-packages (from transformers) (2022.6.2)\n",
      "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.8/dist-packages (from huggingface-hub<1.0,>=0.11.0->transformers) (4.4.0)\n",
      "Requirement already satisfied: chardet<5,>=3.0.2 in /usr/local/lib/python3.8/dist-packages (from requests->transformers) (4.0.0)\n",
      "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.8/dist-packages (from requests->transformers) (2.10)\n",
      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.8/dist-packages (from requests->transformers) (1.24.3)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.8/dist-packages (from requests->transformers) (2022.12.7)\n",
      "Installing collected packages: tokenizers, huggingface-hub, transformers\n",
      "Successfully installed huggingface-hub-0.12.0 tokenizers-0.13.2 transformers-4.26.0\n"
     ]
    }
   ],
   "source": [
    "!pip install transformers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "collapsed": true,
    "id": "qmn7e65AL94c",
    "jupyter": {
     "outputs_hidden": true
    },
    "outputId": "8a7eb63d-6ef4-40bc-9b46-1e7bf0822784",
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/content/WeightWatcher\n",
      "/usr/local/lib/python3.8/dist-packages/setuptools/dist.py:697: UserWarning: Usage of dash-separated 'description-file' will not be supported in future versions. Please use the underscore name 'description_file' instead\n",
      "  warnings.warn(\n",
      "running build\n",
      "running build_py\n",
      "creating build\n",
      "creating build/lib\n",
      "creating build/lib/weightwatcher\n",
      "copying weightwatcher/weightwatcher.py -> build/lib/weightwatcher\n",
      "copying weightwatcher/__init__.py -> build/lib/weightwatcher\n",
      "copying weightwatcher/constants.py -> build/lib/weightwatcher\n",
      "copying weightwatcher/RMT_Util.py -> build/lib/weightwatcher\n",
      "copying weightwatcher/__main__.py -> build/lib/weightwatcher\n",
      "running egg_info\n",
      "creating weightwatcher.egg-info\n",
      "writing weightwatcher.egg-info/PKG-INFO\n",
      "writing dependency_links to weightwatcher.egg-info/dependency_links.txt\n",
      "writing entry points to weightwatcher.egg-info/entry_points.txt\n",
      "writing requirements to weightwatcher.egg-info/requires.txt\n",
      "writing top-level names to weightwatcher.egg-info/top_level.txt\n",
      "writing manifest file 'weightwatcher.egg-info/SOURCES.txt'\n",
      "reading manifest file 'weightwatcher.egg-info/SOURCES.txt'\n",
      "adding license file 'LICENSE.txt'\n",
      "writing manifest file 'weightwatcher.egg-info/SOURCES.txt'\n",
      "running install\n",
      "running bdist_egg\n",
      "installing library code to build/bdist.linux-x86_64/egg\n",
      "running install_lib\n",
      "creating build/bdist.linux-x86_64\n",
      "creating build/bdist.linux-x86_64/egg\n",
      "creating build/bdist.linux-x86_64/egg/weightwatcher\n",
      "copying build/lib/weightwatcher/weightwatcher.py -> build/bdist.linux-x86_64/egg/weightwatcher\n",
      "copying build/lib/weightwatcher/__init__.py -> build/bdist.linux-x86_64/egg/weightwatcher\n",
      "copying build/lib/weightwatcher/constants.py -> build/bdist.linux-x86_64/egg/weightwatcher\n",
      "copying build/lib/weightwatcher/RMT_Util.py -> build/bdist.linux-x86_64/egg/weightwatcher\n",
      "copying build/lib/weightwatcher/__main__.py -> build/bdist.linux-x86_64/egg/weightwatcher\n",
      "byte-compiling build/bdist.linux-x86_64/egg/weightwatcher/weightwatcher.py to weightwatcher.cpython-38.pyc\n",
      "byte-compiling build/bdist.linux-x86_64/egg/weightwatcher/__init__.py to __init__.cpython-38.pyc\n",
      "byte-compiling build/bdist.linux-x86_64/egg/weightwatcher/constants.py to constants.cpython-38.pyc\n",
      "byte-compiling build/bdist.linux-x86_64/egg/weightwatcher/RMT_Util.py to RMT_Util.cpython-38.pyc\n",
      "byte-compiling build/bdist.linux-x86_64/egg/weightwatcher/__main__.py to __main__.cpython-38.pyc\n",
      "creating build/bdist.linux-x86_64/egg/EGG-INFO\n",
      "copying weightwatcher.egg-info/PKG-INFO -> build/bdist.linux-x86_64/egg/EGG-INFO\n",
      "copying weightwatcher.egg-info/SOURCES.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n",
      "copying weightwatcher.egg-info/dependency_links.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n",
      "copying weightwatcher.egg-info/entry_points.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n",
      "copying weightwatcher.egg-info/requires.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n",
      "copying weightwatcher.egg-info/top_level.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n",
      "zip_safe flag not set; analyzing archive contents...\n",
      "creating dist\n",
      "creating 'dist/weightwatcher-0.6.4.1-py3.8.egg' and adding 'build/bdist.linux-x86_64/egg' to it\n",
      "removing 'build/bdist.linux-x86_64/egg' (and everything under it)\n",
      "Processing weightwatcher-0.6.4.1-py3.8.egg\n",
      "Copying weightwatcher-0.6.4.1-py3.8.egg to /usr/local/lib/python3.8/dist-packages\n",
      "Adding weightwatcher 0.6.4.1 to easy-install.pth file\n",
      "Installing weightwatcher script to /usr/local/bin\n",
      "\n",
      "Installed /usr/local/lib/python3.8/dist-packages/weightwatcher-0.6.4.1-py3.8.egg\n",
      "Processing dependencies for weightwatcher==0.6.4.1\n",
      "Searching for powerlaw\n",
      "Reading https://pypi.org/simple/powerlaw/\n",
      "Downloading https://files.pythonhosted.org/packages/e8/26/e0daa306f83d705bc1ed4d6759b7fc945cc787530c230ee1fe299cc28093/powerlaw-1.5-py3-none-any.whl#sha256=633a669573d9fd663d2f452f121117f2d6b2f2c502eca532f9355f733abfec96\n",
      "Best match: powerlaw 1.5\n",
      "Processing powerlaw-1.5-py3-none-any.whl\n",
      "Installing powerlaw-1.5-py3-none-any.whl to /usr/local/lib/python3.8/dist-packages\n",
      "Adding powerlaw 1.5 to easy-install.pth file\n",
      "\n",
      "Installed /usr/local/lib/python3.8/dist-packages/powerlaw-1.5-py3.8.egg\n",
      "Searching for matplotlib-inline\n",
      "Reading https://pypi.org/simple/matplotlib-inline/\n",
      "Downloading https://files.pythonhosted.org/packages/f2/51/c34d7a1d528efaae3d8ddb18ef45a41f284eacf9e514523b191b7d0872cc/matplotlib_inline-0.1.6-py3-none-any.whl#sha256=f1f41aab5328aa5aaea9b16d083b128102f8712542f819fe7e6a420ff581b311\n",
      "Best match: matplotlib-inline 0.1.6\n",
      "Processing matplotlib_inline-0.1.6-py3-none-any.whl\n",
      "Installing matplotlib_inline-0.1.6-py3-none-any.whl to /usr/local/lib/python3.8/dist-packages\n",
      "Adding matplotlib-inline 0.1.6 to easy-install.pth file\n",
      "\n",
      "Installed /usr/local/lib/python3.8/dist-packages/matplotlib_inline-0.1.6-py3.8.egg\n",
      "Searching for tqdm==4.64.1\n",
      "Best match: tqdm 4.64.1\n",
      "Adding tqdm 4.64.1 to easy-install.pth file\n",
      "Installing tqdm script to /usr/local/bin\n",
      "\n",
      "Using /usr/local/lib/python3.8/dist-packages\n",
      "Searching for scikit-learn==1.0.2\n",
      "Best match: scikit-learn 1.0.2\n",
      "Adding scikit-learn 1.0.2 to easy-install.pth file\n",
      "\n",
      "Using /usr/local/lib/python3.8/dist-packages\n",
      "Searching for matplotlib==3.2.2\n",
      "Best match: matplotlib 3.2.2\n",
      "Adding matplotlib 3.2.2 to easy-install.pth file\n",
      "\n",
      "Using /usr/local/lib/python3.8/dist-packages\n",
      "Searching for pandas==1.3.5\n",
      "Best match: pandas 1.3.5\n",
      "Adding pandas 1.3.5 to easy-install.pth file\n",
      "\n",
      "Using /usr/local/lib/python3.8/dist-packages\n",
      "Searching for numpy==1.21.6\n",
      "Best match: numpy 1.21.6\n",
      "Adding numpy 1.21.6 to easy-install.pth file\n",
      "Installing f2py script to /usr/local/bin\n",
      "Installing f2py3 script to /usr/local/bin\n",
      "Installing f2py3.8 script to /usr/local/bin\n",
      "\n",
      "Using /usr/local/lib/python3.8/dist-packages\n",
      "Searching for scipy==1.7.3\n",
      "Best match: scipy 1.7.3\n",
      "Adding scipy 1.7.3 to easy-install.pth file\n",
      "\n",
      "Using /usr/local/lib/python3.8/dist-packages\n",
      "Searching for joblib==1.2.0\n",
      "Best match: joblib 1.2.0\n",
      "Adding joblib 1.2.0 to easy-install.pth file\n",
      "\n",
      "Using /usr/local/lib/python3.8/dist-packages\n",
      "Searching for threadpoolctl==3.1.0\n",
      "Best match: threadpoolctl 3.1.0\n",
      "Adding threadpoolctl 3.1.0 to easy-install.pth file\n",
      "\n",
      "Using /usr/local/lib/python3.8/dist-packages\n",
      "Searching for mpmath==1.2.1\n",
      "Best match: mpmath 1.2.1\n",
      "Adding mpmath 1.2.1 to easy-install.pth file\n",
      "\n",
      "Using /usr/local/lib/python3.8/dist-packages\n",
      "Searching for traitlets==5.7.1\n",
      "Best match: traitlets 5.7.1\n",
      "Adding traitlets 5.7.1 to easy-install.pth file\n",
      "\n",
      "Using /usr/local/lib/python3.8/dist-packages\n",
      "Searching for python-dateutil==2.8.2\n",
      "Best match: python-dateutil 2.8.2\n",
      "Adding python-dateutil 2.8.2 to easy-install.pth file\n",
      "\n",
      "Using /usr/local/lib/python3.8/dist-packages\n",
      "Searching for pyparsing==3.0.9\n",
      "Best match: pyparsing 3.0.9\n",
      "Adding pyparsing 3.0.9 to easy-install.pth file\n",
      "\n",
      "Using /usr/local/lib/python3.8/dist-packages\n",
      "Searching for kiwisolver==1.4.4\n",
      "Best match: kiwisolver 1.4.4\n",
      "Adding kiwisolver 1.4.4 to easy-install.pth file\n",
      "\n",
      "Using /usr/local/lib/python3.8/dist-packages\n",
      "Searching for cycler==0.11.0\n",
      "Best match: cycler 0.11.0\n",
      "Adding cycler 0.11.0 to easy-install.pth file\n",
      "\n",
      "Using /usr/local/lib/python3.8/dist-packages\n",
      "Searching for pytz==2022.7.1\n",
      "Best match: pytz 2022.7.1\n",
      "Adding pytz 2022.7.1 to easy-install.pth file\n",
      "\n",
      "Using /usr/local/lib/python3.8/dist-packages\n",
      "Searching for six==1.15.0\n",
      "Best match: six 1.15.0\n",
      "Adding six 1.15.0 to easy-install.pth file\n",
      "\n",
      "Using /usr/local/lib/python3.8/dist-packages\n",
      "Finished processing dependencies for weightwatcher==0.6.4.1\n"
     ]
    }
   ],
   "source": [
    "%cd WeightWatcher\n",
    "!python setup.py build install "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-------------------------------------\n",
      "In Test_ValidParams: test_invalid_PL_package_settings\n",
      "CRITICAL:weightwatcher:xmax=force not available if using pl_package=ww\n",
      "CRITICAL:weightwatcher:pl_package only supports PowerLaw fits, but fit=TPL\n",
      "CRITICAL:weightwatcher:pl_package only supports PowerLaw fits, but fit=E_TPL\n",
      "CRITICAL:weightwatcher:pl_package only supports PowerLaw fits, but fit=truncated_power_law\n",
      "CRITICAL:weightwatcher:xmax can not be 0\n",
      "WARNING:weightwatcher:Unknown how to fix fingers True, deactivating\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_ValidParams: test_valid_params\n",
      "WARNING:weightwatcher:fix_fingers ignores xmax = None\n",
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 2 tests in 0.470s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "!python -m unittest -k Test_ValidParams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-------------------------------------\n",
      "In Test_KerasLayers: test_keras_layer_constructor\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_KerasLayers: test_replace_weights_and_biases\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_KerasLayers: test_replace_weights_only\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_KerasLayers: test_ww_layer_attributes\n",
      "the longname is None\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_KerasLayers: test_ww_layer_iterator\n",
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 5 tests in 15.161s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "!python -m unittest -k Test_KerasLayers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-------------------------------------\n",
      "In Test_PyTorchLayers: test_pytorch_layer_constructor\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_PyTorchLayers: test_replace_weights_and_biases\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_PyTorchLayers: test_replace_weights_only\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_PyTorchLayers: test_ww_layer_attributes\n",
      "the longname is fc\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_PyTorchLayers: test_ww_layer_iterator\n",
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 5 tests in 1.789s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "!python -m unittest -k Test_PyTorchLayers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-------------------------------------\n",
      "In Test_PyStateDictLayers: test_pytorch_layer_constructor\n",
      "<weightwatcher.weightwatcher.PyStateDictLayer object at 0x7fe1b6831910>\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_PyStateDictLayers: test_replace_weights_and_biases\n",
      "WWLayer 1  conv1 CONV2D  skipped False\n",
      "WWLayer 3  layer1.0.conv1 CONV2D  skipped False\n",
      "WWLayer 5  layer1.0.conv2 CONV2D  skipped False\n",
      "WWLayer 7  layer1.1.conv1 CONV2D  skipped False\n",
      "WWLayer 9  layer1.1.conv2 CONV2D  skipped False\n",
      "WWLayer 11  layer2.0.conv1 CONV2D  skipped False\n",
      "WWLayer 13  layer2.0.conv2 CONV2D  skipped False\n",
      "WWLayer 15  layer2.0.downsample.0 CONV2D  skipped False\n",
      "WWLayer 17  layer2.1.conv1 CONV2D  skipped False\n",
      "WWLayer 19  layer2.1.conv2 CONV2D  skipped False\n",
      "WWLayer 21  layer3.0.conv1 CONV2D  skipped False\n",
      "WWLayer 23  layer3.0.conv2 CONV2D  skipped False\n",
      "WWLayer 25  layer3.0.downsample.0 CONV2D  skipped False\n",
      "WWLayer 27  layer3.1.conv1 CONV2D  skipped False\n",
      "WWLayer 29  layer3.1.conv2 CONV2D  skipped False\n",
      "WWLayer 31  layer4.0.conv1 CONV2D  skipped False\n",
      "WWLayer 33  layer4.0.conv2 CONV2D  skipped False\n",
      "WWLayer 35  layer4.0.downsample.0 CONV2D  skipped False\n",
      "WWLayer 37  layer4.1.conv1 CONV2D  skipped False\n",
      "WWLayer 39  layer4.1.conv2 CONV2D  skipped False\n",
      "WWLayer 41  fc DENSE  skipped False\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_PyStateDictLayers: test_replace_weights_only\n",
      "WWLayer 1  conv1 CONV2D  skipped False\n",
      "WWLayer 3  layer1.0.conv1 CONV2D  skipped False\n",
      "WWLayer 5  layer1.0.conv2 CONV2D  skipped False\n",
      "WWLayer 7  layer1.1.conv1 CONV2D  skipped False\n",
      "WWLayer 9  layer1.1.conv2 CONV2D  skipped False\n",
      "WWLayer 11  layer2.0.conv1 CONV2D  skipped False\n",
      "WWLayer 13  layer2.0.conv2 CONV2D  skipped False\n",
      "WWLayer 15  layer2.0.downsample.0 CONV2D  skipped False\n",
      "WWLayer 17  layer2.1.conv1 CONV2D  skipped False\n",
      "WWLayer 19  layer2.1.conv2 CONV2D  skipped False\n",
      "WWLayer 21  layer3.0.conv1 CONV2D  skipped False\n",
      "WWLayer 23  layer3.0.conv2 CONV2D  skipped False\n",
      "WWLayer 25  layer3.0.downsample.0 CONV2D  skipped False\n",
      "WWLayer 27  layer3.1.conv1 CONV2D  skipped False\n",
      "WWLayer 29  layer3.1.conv2 CONV2D  skipped False\n",
      "WWLayer 31  layer4.0.conv1 CONV2D  skipped False\n",
      "WWLayer 33  layer4.0.conv2 CONV2D  skipped False\n",
      "WWLayer 35  layer4.0.downsample.0 CONV2D  skipped False\n",
      "WWLayer 37  layer4.1.conv1 CONV2D  skipped False\n",
      "WWLayer 39  layer4.1.conv2 CONV2D  skipped False\n",
      "WWLayer 41  fc DENSE  skipped False\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_PyStateDictLayers: test_ww_layer_attributes\n",
      "WWLayer 1  conv1 CONV2D  skipped False\n",
      "WWLayer 3  layer1.0.conv1 CONV2D  skipped False\n",
      "WWLayer 5  layer1.0.conv2 CONV2D  skipped False\n",
      "WWLayer 7  layer1.1.conv1 CONV2D  skipped False\n",
      "WWLayer 9  layer1.1.conv2 CONV2D  skipped False\n",
      "WWLayer 11  layer2.0.conv1 CONV2D  skipped False\n",
      "WWLayer 13  layer2.0.conv2 CONV2D  skipped False\n",
      "WWLayer 15  layer2.0.downsample.0 CONV2D  skipped False\n",
      "WWLayer 17  layer2.1.conv1 CONV2D  skipped False\n",
      "WWLayer 19  layer2.1.conv2 CONV2D  skipped False\n",
      "WWLayer 21  layer3.0.conv1 CONV2D  skipped False\n",
      "WWLayer 23  layer3.0.conv2 CONV2D  skipped False\n",
      "WWLayer 25  layer3.0.downsample.0 CONV2D  skipped False\n",
      "WWLayer 27  layer3.1.conv1 CONV2D  skipped False\n",
      "WWLayer 29  layer3.1.conv2 CONV2D  skipped False\n",
      "WWLayer 31  layer4.0.conv1 CONV2D  skipped False\n",
      "WWLayer 33  layer4.0.conv2 CONV2D  skipped False\n",
      "WWLayer 35  layer4.0.downsample.0 CONV2D  skipped False\n",
      "WWLayer 37  layer4.1.conv1 CONV2D  skipped False\n",
      "WWLayer 39  layer4.1.conv2 CONV2D  skipped False\n",
      "WWLayer 41  fc DENSE  skipped False\n",
      "the longname is fc\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_PyStateDictLayers: test_ww_layer_iterator\n",
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 5 tests in 1.710s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "!python -m unittest -k Test_PyStateDictLayers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-------------------------------------\n",
      "In Test_VGG11_noModel: test_analyze_columns_no_model\n",
      "Index(['layer_id', 'name', 'D', 'Lambda', 'M', 'N', 'Q', 'alpha',\n",
      "       'alpha_weighted', 'best_fit', 'entropy', 'fit_entropy', 'has_esd',\n",
      "       'lambda_max', 'layer_type', 'log_alpha_norm', 'log_norm',\n",
      "       'log_spectral_norm', 'longname', 'matrix_rank', 'norm', 'num_evals',\n",
      "       'num_fingers', 'num_pl_spikes', 'rank_loss', 'rf', 'sigma',\n",
      "       'spectral_norm', 'stable_rank', 'sv_max', 'warning', 'weak_rank_loss',\n",
      "       'xmax', 'xmin'],\n",
      "      dtype='object')\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_noModel: test_basic_columns_no_model\n",
      "    layer_id    name     M  ...      longname  num_evals rf\n",
      "0          2  Conv2d     3  ...    features.0         27  9\n",
      "1          5  Conv2d    64  ...    features.3        576  9\n",
      "2          8  Conv2d   128  ...    features.6       1152  9\n",
      "3         10  Conv2d   256  ...    features.8       2304  9\n",
      "4         13  Conv2d   256  ...   features.11       2304  9\n",
      "5         15  Conv2d   512  ...   features.13       4608  9\n",
      "6         18  Conv2d   512  ...   features.16       4608  9\n",
      "7         20  Conv2d   512  ...   features.18       4608  9\n",
      "8         25  Linear  4096  ...  classifier.0       4096  1\n",
      "9         28  Linear  4096  ...  classifier.3       4096  1\n",
      "10        31  Linear  1000  ...  classifier.6       1000  1\n",
      "\n",
      "[11 rows x 9 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_noModel: test_getESD_no_model\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_noModel: test_get_summary_no_model\n",
      "{'log_norm': 3.2835808, 'alpha': 2.1613259185493496, 'alpha_weighted': 3.847748288422296, 'log_alpha_norm': 4.236026567250773, 'log_spectral_norm': 1.7802721, 'stable_rank': 31.86462}\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_noModel: test_intra_power_law_fit_no_model\n",
      "2.661745275849647 lognormal\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_noModel: test_permute_W_no_model\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_noModel: test_randomize_no_model\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_noModel: test_svd_sharpness_no_model\n",
      "max esd before 60.278518503997944\n",
      "max esd after 14.729313848460382\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_noModel: test_svd_smoothing_no_model\n",
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 9 tests in 116.110s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "!python -m unittest -k Test_VGG11_noModel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "background_save": true
    },
    "id": "X4_aU-mAMdh9",
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-------------------------------------\n",
      "In Test_VGG11_Distances: test_CKA_distances\n",
      "====== pool=True ========\n",
      "         method    name   delta_W  delta_b     M      N  b_shape      longname\n",
      "layer_id                                                                      \n",
      "5           cka  Conv2d  1.000000      0.0    64    128  unknown    features.3\n",
      "8           cka  Conv2d  1.000000      0.0   128    256  unknown    features.6\n",
      "10          cka  Conv2d  1.000000      0.0   256    256  unknown    features.8\n",
      "13          cka  Conv2d  1.000000      0.0   256    512  unknown   features.11\n",
      "15          cka  Conv2d  1.000000      0.0   512    512  unknown   features.13\n",
      "18          cka  Conv2d  1.000000      0.0   512    512  unknown   features.16\n",
      "20          cka  Conv2d  1.000000      0.0   512    512  unknown   features.18\n",
      "25          cka  Linear  0.988792      0.0  4096  25088  unknown  classifier.0\n",
      "28          cka  Linear  1.000003      0.0  4096   4096  unknown  classifier.3\n",
      "31          cka  Linear  0.999941      0.0  1000   4096  unknown  classifier.6\n",
      "====== pool=False ========\n",
      "         method    name   delta_W  ...  b_shape      longname  slice_id\n",
      "layer_id                           ...                                 \n",
      "5           cka  Conv2d  1.000000  ...  unknown    features.3         0\n",
      "5           cka  Conv2d  1.000000  ...  unknown    features.3         1\n",
      "5           cka  Conv2d  1.000000  ...  unknown    features.3         2\n",
      "5           cka  Conv2d  1.000000  ...  unknown    features.3         3\n",
      "5           cka  Conv2d  1.000000  ...  unknown    features.3         4\n",
      "...         ...     ...       ...  ...      ...           ...       ...\n",
      "20          cka  Conv2d  1.000000  ...  unknown   features.18         7\n",
      "20          cka  Conv2d  1.000000  ...  unknown   features.18         8\n",
      "25          cka  Linear  0.988792  ...  unknown  classifier.0         0\n",
      "28          cka  Linear  1.000003  ...  unknown  classifier.3         0\n",
      "31          cka  Linear  0.999941  ...  unknown  classifier.6         0\n",
      "\n",
      "[66 rows x 9 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Distances: test_Euclidian_distances\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Distances: test_Euclidian_distances_w_one_layer\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Distances: test_distances\n",
      "46.490322 0.6762209892272949\n",
      "         method    name     delta_W  ...      N  b_shape      longname\n",
      "layer_id                             ...                              \n",
      "5           raw  Conv2d   21.070652  ...    128  unknown    features.3\n",
      "8           raw  Conv2d   25.752670  ...    256  unknown    features.6\n",
      "10          raw  Conv2d   32.198410  ...    256  unknown    features.8\n",
      "13          raw  Conv2d   34.913013  ...    512  unknown   features.11\n",
      "15          raw  Conv2d   43.350277  ...    512  unknown   features.13\n",
      "18          raw  Conv2d   44.069283  ...    512  unknown   features.16\n",
      "20          raw  Conv2d   43.204105  ...    512  unknown   features.18\n",
      "25          raw  Linear  116.324615  ...  25088     4096  classifier.0\n",
      "28          raw  Linear   59.974529  ...   4096     4096  classifier.3\n",
      "31          raw  Linear   44.045704  ...   4096     1000  classifier.6\n",
      "\n",
      "[10 rows x 8 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Distances: test_same_distances\n",
      "         method    name  delta_W  delta_b     M      N  b_shape      longname\n",
      "layer_id                                                                     \n",
      "5           raw  Conv2d      0.0      0.0     3    128  unknown    features.3\n",
      "8           raw  Conv2d      0.0      0.0     3    256  unknown    features.6\n",
      "10          raw  Conv2d      0.0      0.0     3    256  unknown    features.8\n",
      "13          raw  Conv2d      0.0      0.0     3    512  unknown   features.11\n",
      "15          raw  Conv2d      0.0      0.0     3    512  unknown   features.13\n",
      "18          raw  Conv2d      0.0      0.0     3    512  unknown   features.16\n",
      "20          raw  Conv2d      0.0      0.0     3    512  unknown   features.18\n",
      "25          raw  Linear      0.0      0.0  4096  25088     4096  classifier.0\n",
      "28          raw  Linear      0.0      0.0  4096   4096     4096  classifier.3\n",
      "31          raw  Linear      0.0      0.0  1000   4096     1000  classifier.6\n",
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 5 tests in 58.877s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "!python -m unittest -k Test_VGG11_Distances"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-------------------------------------\n",
      "In Test_Albert: test_albert_availbla\n",
      "Some weights of the model checkpoint at albert-xxlarge-v2 were not used when initializing AlbertModel: ['predictions.dense.bias', 'predictions.dense.weight', 'predictions.LayerNorm.bias', 'predictions.bias', 'predictions.decoder.weight', 'predictions.LayerNorm.weight', 'predictions.decoder.bias']\n",
      "- This IS expected if you are initializing AlbertModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
      "- This IS NOT expected if you are initializing AlbertModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
      "   layer_id    name  ...  num_evals  rf\n",
      "0        17  Linear  ...       4096   1\n",
      "\n",
      "[1 rows x 9 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_Albert: test_fix_fingers\n",
      "Some weights of the model checkpoint at albert-xxlarge-v2 were not used when initializing AlbertModel: ['predictions.dense.bias', 'predictions.dense.weight', 'predictions.LayerNorm.bias', 'predictions.bias', 'predictions.decoder.weight', 'predictions.LayerNorm.weight', 'predictions.decoder.bias']\n",
      "- This IS expected if you are initializing AlbertModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
      "- This IS NOT expected if you are initializing AlbertModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
      "WARNING:weightwatcher:fix_fingers ignores xmax = None\n",
      "WARNING:weightwatcher:fix_fingers ignores xmax = None\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_Albert: test_fix_fingers_w_powerlaw\n",
      "Some weights of the model checkpoint at albert-xxlarge-v2 were not used when initializing AlbertModel: ['predictions.dense.bias', 'predictions.dense.weight', 'predictions.LayerNorm.bias', 'predictions.bias', 'predictions.decoder.weight', 'predictions.LayerNorm.weight', 'predictions.decoder.bias']\n",
      "- This IS expected if you are initializing AlbertModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
      "- This IS NOT expected if you are initializing AlbertModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
      "WARNING:weightwatcher:fix_fingers ignores xmax = None\n",
      "WARNING:weightwatcher:fix_fingers ignores xmax = None\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_Albert: test_layer_alpha\n",
      "Some weights of the model checkpoint at albert-xxlarge-v2 were not used when initializing AlbertModel: ['predictions.dense.bias', 'predictions.dense.weight', 'predictions.LayerNorm.bias', 'predictions.bias', 'predictions.decoder.weight', 'predictions.LayerNorm.weight', 'predictions.decoder.bias']\n",
      "- This IS expected if you are initializing AlbertModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
      "- This IS NOT expected if you are initializing AlbertModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_Albert: test_layer_alpha_w_powerlaw\n",
      "Some weights of the model checkpoint at albert-xxlarge-v2 were not used when initializing AlbertModel: ['predictions.dense.bias', 'predictions.dense.weight', 'predictions.LayerNorm.bias', 'predictions.bias', 'predictions.decoder.weight', 'predictions.LayerNorm.weight', 'predictions.decoder.bias']\n",
      "- This IS expected if you are initializing AlbertModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
      "- This IS NOT expected if you are initializing AlbertModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_Albert: test_xmax_set\n",
      "Some weights of the model checkpoint at albert-xxlarge-v2 were not used when initializing AlbertModel: ['predictions.dense.bias', 'predictions.dense.weight', 'predictions.LayerNorm.bias', 'predictions.bias', 'predictions.decoder.weight', 'predictions.LayerNorm.weight', 'predictions.decoder.bias']\n",
      "- This IS expected if you are initializing AlbertModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
      "- This IS NOT expected if you are initializing AlbertModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 6 tests in 46.710s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "!python -m unittest -k Test_Albert"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_ESD_model_set\n",
      "    layer_id    name     M  ...      longname  num_evals rf\n",
      "0          2  Conv2d     3  ...    features.0         27  9\n",
      "1          5  Conv2d    64  ...    features.3        576  9\n",
      "2          8  Conv2d   128  ...    features.6       1152  9\n",
      "3         10  Conv2d   256  ...    features.8       2304  9\n",
      "4         13  Conv2d   256  ...   features.11       2304  9\n",
      "5         15  Conv2d   512  ...   features.13       4608  9\n",
      "6         18  Conv2d   512  ...   features.16       4608  9\n",
      "7         20  Conv2d   512  ...   features.18       4608  9\n",
      "8         25  Linear  4096  ...  classifier.0       4096  1\n",
      "9         28  Linear  4096  ...  classifier.3       4096  1\n",
      "10        31  Linear  1000  ...  classifier.6       1000  1\n",
      "\n",
      "[11 rows x 9 columns]\n",
      "4096\n",
      "4096\n",
      "max esd before 60.278518503997944\n",
      "max esd after 60.278518503997944\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_N_ge_M\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_all_layer_types\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_analyze_columns\n",
      "Index(['layer_id', 'name', 'D', 'Lambda', 'M', 'N', 'Q', 'alpha',\n",
      "       'alpha_weighted', 'best_fit', 'entropy', 'fit_entropy', 'has_esd',\n",
      "       'lambda_max', 'layer_type', 'log_alpha_norm', 'log_norm',\n",
      "       'log_spectral_norm', 'longname', 'matrix_rank', 'norm', 'num_evals',\n",
      "       'num_fingers', 'num_pl_spikes', 'rank_loss', 'rf', 'sigma',\n",
      "       'spectral_norm', 'stable_rank', 'sv_max', 'warning', 'weak_rank_loss',\n",
      "       'xmax', 'xmin'],\n",
      "      dtype='object')\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_analyze_columns_with_model\n",
      "Index(['layer_id', 'name', 'D', 'Lambda', 'M', 'N', 'Q', 'alpha',\n",
      "       'alpha_weighted', 'best_fit', 'entropy', 'fit_entropy', 'has_esd',\n",
      "       'lambda_max', 'layer_type', 'log_alpha_norm', 'log_norm',\n",
      "       'log_spectral_norm', 'longname', 'matrix_rank', 'norm', 'num_evals',\n",
      "       'num_fingers', 'num_pl_spikes', 'rank_loss', 'rf', 'sigma',\n",
      "       'spectral_norm', 'stable_rank', 'sv_max', 'warning', 'weak_rank_loss',\n",
      "       'xmax', 'xmin'],\n",
      "      dtype='object')\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_bad_params\n",
      "WARNING:weightwatcher:layer filter ids must be all > 0 or < 0: [-1, 1]\n",
      "ERROR:weightwatcher:Error, params not valid: \n",
      " {'glorot_fix': False, 'normalize': False, 'conv2d_norm': True, 'randomize': True, 'savedir': 'ww-img', 'savefig': 'ww-img', 'rescale': True, 'plot': False, 'deltaEs': False, 'intra': False, 'channels': None, 'conv2d_fft': False, 'kernel_fft': False, 'ww2x': False, 'pool': True, 'vectors': True, 'smooth': None, 'stacked': False, 'svd_method': 'accurate', 'fix_fingers': None, 'fit': 'power_law', 'sparsify': True, 'detX': True, 'mp_fit': False, 'min_evals': 0, 'max_evals': None, 'max_N': 10, 'tolerance': 1e-06, 'layer_ids_start': 0, 'add_biases': False, 'pl_package': 'ww', 'xmax': None, 'glorot_fit': False, 'layers': [-1, 1]}\n",
      "WARNING:weightwatcher:KERNEL_FFT option not currently supported, may be deprecated\n",
      "ERROR:weightwatcher:Error, params not valid: \n",
      " {'glorot_fix': False, 'normalize': False, 'conv2d_norm': True, 'randomize': True, 'savedir': 'ww-img', 'savefig': 'ww-img', 'rescale': True, 'plot': False, 'deltaEs': False, 'intra': False, 'channels': None, 'conv2d_fft': False, 'kernel_fft': True, 'ww2x': False, 'pool': True, 'vectors': True, 'smooth': None, 'stacked': False, 'svd_method': 'accurate', 'fix_fingers': None, 'fit': 'power_law', 'sparsify': True, 'detX': True, 'mp_fit': False, 'min_evals': 0, 'max_evals': None, 'max_N': 10, 'tolerance': 1e-06, 'layer_ids_start': 0, 'add_biases': False, 'pl_package': 'ww', 'xmax': None, 'glorot_fit': False, 'layers': []}\n",
      "WARNING:weightwatcher:WW2X option deprecated, reverting too POOL=False\n",
      "F\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_basic_columns\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_basic_columns_with_model\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_basic_columns_with_new_watcher\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_compute_spectral_norms\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_density_fit\n",
      "num spikes 782\n",
      "sigma mp 0.6894768801797752\n",
      "I think something is wrong here\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_density_fit_on_randomized_W\n",
      "rand_num_spikes 1\n",
      "rand_sigma mp 0.9997353619629317\n",
      "F\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_describe_model\n",
      "    layer_id    name     M  ...      longname  num_evals rf\n",
      "0          2  Conv2d     3  ...    features.0         27  9\n",
      "1          5  Conv2d    64  ...    features.3        576  9\n",
      "2          8  Conv2d   128  ...    features.6       1152  9\n",
      "3         10  Conv2d   256  ...    features.8       2304  9\n",
      "4         13  Conv2d   256  ...   features.11       2304  9\n",
      "5         15  Conv2d   512  ...   features.13       4608  9\n",
      "6         18  Conv2d   512  ...   features.16       4608  9\n",
      "7         20  Conv2d   512  ...   features.18       4608  9\n",
      "8         25  Linear  4096  ...  classifier.0       4096  1\n",
      "9         28  Linear  4096  ...  classifier.3       4096  1\n",
      "10        31  Linear  1000  ...  classifier.6       1000  1\n",
      "\n",
      "[11 rows x 9 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_describe_model_ww2x\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_dimensions\n",
      "    layer_id    name     M  ...      longname  num_evals rf\n",
      "0          2  Conv2d     3  ...    features.0         27  9\n",
      "1          5  Conv2d    64  ...    features.3        576  9\n",
      "2          8  Conv2d   128  ...    features.6       1152  9\n",
      "3         10  Conv2d   256  ...    features.8       2304  9\n",
      "4         13  Conv2d   256  ...   features.11       2304  9\n",
      "5         15  Conv2d   512  ...   features.13       4608  9\n",
      "6         18  Conv2d   512  ...   features.16       4608  9\n",
      "7         20  Conv2d   512  ...   features.18       4608  9\n",
      "8         25  Linear  4096  ...  classifier.0       4096  1\n",
      "9         28  Linear  4096  ...  classifier.3       4096  1\n",
      "10        31  Linear  1000  ...  classifier.6       1000  1\n",
      "\n",
      "[11 rows x 9 columns]\n",
      "   layer_id    name  M   N  ...         layer_type    longname num_evals  rf\n",
      "0         2  Conv2d  3  64  ...  LAYER_TYPE.CONV2D  features.0        27   9\n",
      "\n",
      "[1 rows x 9 columns]\n",
      "64 3 9 27\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_filter_conv2D_layer_types\n",
      "   layer_id    name    M    N  ...         layer_type     longname num_evals  rf\n",
      "0         2  Conv2d    3   64  ...  LAYER_TYPE.CONV2D   features.0        27   9\n",
      "1         5  Conv2d   64  128  ...  LAYER_TYPE.CONV2D   features.3       576   9\n",
      "2         8  Conv2d  128  256  ...  LAYER_TYPE.CONV2D   features.6      1152   9\n",
      "3        10  Conv2d  256  256  ...  LAYER_TYPE.CONV2D   features.8      2304   9\n",
      "4        13  Conv2d  256  512  ...  LAYER_TYPE.CONV2D  features.11      2304   9\n",
      "5        15  Conv2d  512  512  ...  LAYER_TYPE.CONV2D  features.13      4608   9\n",
      "6        18  Conv2d  512  512  ...  LAYER_TYPE.CONV2D  features.16      4608   9\n",
      "7        20  Conv2d  512  512  ...  LAYER_TYPE.CONV2D  features.18      4608   9\n",
      "\n",
      "[8 rows x 9 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_filter_dense_layer_types\n",
      "test_filter_dense_layer_types\n",
      "   layer_id    name     M      N  ...        layer_type      longname num_evals  rf\n",
      "0        25  Linear  4096  25088  ...  LAYER_TYPE.DENSE  classifier.0      4096   1\n",
      "1        28  Linear  4096   4096  ...  LAYER_TYPE.DENSE  classifier.3      4096   1\n",
      "2        31  Linear  1000   4096  ...  LAYER_TYPE.DENSE  classifier.6      1000   1\n",
      "\n",
      "[3 rows x 9 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_filter_layer_ids\n",
      "    layer_id    name     M  ...      longname  num_evals rf\n",
      "0          2  Conv2d     3  ...    features.0         27  9\n",
      "1          5  Conv2d    64  ...    features.3        576  9\n",
      "2          8  Conv2d   128  ...    features.6       1152  9\n",
      "3         10  Conv2d   256  ...    features.8       2304  9\n",
      "4         13  Conv2d   256  ...   features.11       2304  9\n",
      "5         15  Conv2d   512  ...   features.13       4608  9\n",
      "6         18  Conv2d   512  ...   features.16       4608  9\n",
      "7         20  Conv2d   512  ...   features.18       4608  9\n",
      "8         25  Linear  4096  ...  classifier.0       4096  1\n",
      "9         28  Linear  4096  ...  classifier.3       4096  1\n",
      "10        31  Linear  1000  ...  classifier.6       1000  1\n",
      "\n",
      "[11 rows x 9 columns]\n",
      "   layer_id    name     M      N  ...        layer_type      longname num_evals  rf\n",
      "0        25  Linear  4096  25088  ...  LAYER_TYPE.DENSE  classifier.0      4096   1\n",
      "1        28  Linear  4096   4096  ...  LAYER_TYPE.DENSE  classifier.3      4096   1\n",
      "2        31  Linear  1000   4096  ...  LAYER_TYPE.DENSE  classifier.6      1000   1\n",
      "\n",
      "[3 rows x 9 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_fit_entropy_on_layer\n",
      "Calculating best minimal value for power law fit\n",
      ".min progress: 99%\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_getESD\n",
      "    layer_id    name     M  ...      longname  num_evals rf\n",
      "0          2  Conv2d     3  ...    features.0         27  9\n",
      "1          5  Conv2d    64  ...    features.3        576  9\n",
      "2          8  Conv2d   128  ...    features.6       1152  9\n",
      "3         10  Conv2d   256  ...    features.8       2304  9\n",
      "4         13  Conv2d   256  ...   features.11       2304  9\n",
      "5         15  Conv2d   512  ...   features.13       4608  9\n",
      "6         18  Conv2d   512  ...   features.16       4608  9\n",
      "7         20  Conv2d   512  ...   features.18       4608  9\n",
      "8         25  Linear  4096  ...  classifier.0       4096  1\n",
      "9         28  Linear  4096  ...  classifier.3       4096  1\n",
      "10        31  Linear  1000  ...  classifier.6       1000  1\n",
      "\n",
      "[11 rows x 9 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_getESD_with_model\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_get_details\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_get_framework_layer\n",
      "Linear(in_features=25088, out_features=4096, bias=True)\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_get_summary\n",
      "{'log_norm': 2.1971962, 'alpha': 1.7207916701875228, 'alpha_weighted': 1.141652879015995, 'log_alpha_norm': 2.273003564664541, 'log_spectral_norm': 0.6634463, 'stable_rank': 34.17826}\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_get_summary_with_model\n",
      "{'log_norm': 2.1971962, 'alpha': 1.7207916701875228, 'alpha_weighted': 1.141652879015995, 'log_alpha_norm': 2.273003564664541, 'log_spectral_norm': 0.6634463, 'stable_rank': 34.17826}\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_get_summary_with_new_model\n",
      "{'log_norm': 3.1718328, 'alpha': 2.7404752500854537, 'alpha_weighted': 4.83160523450143, 'log_alpha_norm': 5.178781840348228, 'log_spectral_norm': 1.7630538, 'stable_rank': 25.631802}\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_layer_ids\n",
      "<class 'torchvision.models.vgg.VGG'>\n",
      "    layer_id    name     M  ...      longname  num_evals rf\n",
      "0          2  Conv2d     3  ...    features.0         27  9\n",
      "1          5  Conv2d    64  ...    features.3        576  9\n",
      "2          8  Conv2d   128  ...    features.6       1152  9\n",
      "3         10  Conv2d   256  ...    features.8       2304  9\n",
      "4         13  Conv2d   256  ...   features.11       2304  9\n",
      "5         15  Conv2d   512  ...   features.13       4608  9\n",
      "6         18  Conv2d   512  ...   features.16       4608  9\n",
      "7         20  Conv2d   512  ...   features.18       4608  9\n",
      "8         25  Linear  4096  ...  classifier.0       4096  1\n",
      "9         28  Linear  4096  ...  classifier.3       4096  1\n",
      "10        31  Linear  1000  ...  classifier.6       1000  1\n",
      "\n",
      "[11 rows x 9 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_make_ww_iterator\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_max_matrix_shape\n",
      "   layer_id    name     M     N  ...         layer_type      longname num_evals  rf\n",
      "0         2  Conv2d     3    64  ...  LAYER_TYPE.CONV2D    features.0        27   9\n",
      "1         5  Conv2d    64   128  ...  LAYER_TYPE.CONV2D    features.3       576   9\n",
      "2        31  Linear  1000  4096  ...   LAYER_TYPE.DENSE  classifier.6      1000   1\n",
      "\n",
      "[3 rows x 9 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_min_matrix_shape\n",
      "   layer_id    name     M  ...      longname  num_evals rf\n",
      "0         5  Conv2d    64  ...    features.3        576  9\n",
      "1         8  Conv2d   128  ...    features.6       1152  9\n",
      "2        10  Conv2d   256  ...    features.8       2304  9\n",
      "3        13  Conv2d   256  ...   features.11       2304  9\n",
      "4        15  Conv2d   512  ...   features.13       4608  9\n",
      "5        18  Conv2d   512  ...   features.16       4608  9\n",
      "6        20  Conv2d   512  ...   features.18       4608  9\n",
      "7        25  Linear  4096  ...  classifier.0       4096  1\n",
      "8        28  Linear  4096  ...  classifier.3       4096  1\n",
      "9        31  Linear  1000  ...  classifier.6       1000  1\n",
      "\n",
      "[10 rows x 9 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_model_layer_types_ww2x\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_mp_fit_columns\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_negative_filter_layer_ids\n",
      "skip these layers [-25, -28, -31]\n",
      "    layer_id    name     M  ...      longname  num_evals rf\n",
      "0          2  Conv2d     3  ...    features.0         27  9\n",
      "1          5  Conv2d    64  ...    features.3        576  9\n",
      "2          8  Conv2d   128  ...    features.6       1152  9\n",
      "3         10  Conv2d   256  ...    features.8       2304  9\n",
      "4         13  Conv2d   256  ...   features.11       2304  9\n",
      "5         15  Conv2d   512  ...   features.13       4608  9\n",
      "6         18  Conv2d   512  ...   features.16       4608  9\n",
      "7         20  Conv2d   512  ...   features.18       4608  9\n",
      "8         25  Linear  4096  ...  classifier.0       4096  1\n",
      "9         28  Linear  4096  ...  classifier.3       4096  1\n",
      "10        31  Linear  1000  ...  classifier.6       1000  1\n",
      "\n",
      "[11 rows x 9 columns]\n",
      "   layer_id    name    M    N  ...         layer_type     longname num_evals  rf\n",
      "0         2  Conv2d    3   64  ...  LAYER_TYPE.CONV2D   features.0        27   9\n",
      "1         5  Conv2d   64  128  ...  LAYER_TYPE.CONV2D   features.3       576   9\n",
      "2         8  Conv2d  128  256  ...  LAYER_TYPE.CONV2D   features.6      1152   9\n",
      "3        10  Conv2d  256  256  ...  LAYER_TYPE.CONV2D   features.8      2304   9\n",
      "4        13  Conv2d  256  512  ...  LAYER_TYPE.CONV2D  features.11      2304   9\n",
      "5        15  Conv2d  512  512  ...  LAYER_TYPE.CONV2D  features.13      4608   9\n",
      "6        18  Conv2d  512  512  ...  LAYER_TYPE.CONV2D  features.16      4608   9\n",
      "7        20  Conv2d  512  512  ...  LAYER_TYPE.CONV2D  features.18      4608   9\n",
      "\n",
      "[8 rows x 9 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_num_evals\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_permute_W\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_permute_W_with_model\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_print_watcher\n",
      "\n",
      "Analysis done: False\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_rand_distance\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_random_mp_fit_columns_\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_randomize\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_randomize_mp_fits\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_rescale_eigenvalues\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_reset_params\n",
      "CRITICAL:weightwatcher:pl_package only supports PowerLaw fits, but fit=TPL\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_rf_value\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_runtime_warnings\n",
      "/darda/WeightWatcher/tests/test.py:1802: RuntimeWarning: invalid value encountered in sqrt\n",
      "  print(\"test runtime warning: sqrt(-1)=\", np.sqrt(-1.0))\n",
      "test runtime warning: sqrt(-1)= nan\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_same_models\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_start_ids_1\n",
      "    layer_id    name     M  ...      longname  num_evals rf\n",
      "0          2  Conv2d     3  ...    features.0         27  9\n",
      "1          5  Conv2d    64  ...    features.3        576  9\n",
      "2          8  Conv2d   128  ...    features.6       1152  9\n",
      "3         10  Conv2d   256  ...    features.8       2304  9\n",
      "4         13  Conv2d   256  ...   features.11       2304  9\n",
      "5         15  Conv2d   512  ...   features.13       4608  9\n",
      "6         18  Conv2d   512  ...   features.16       4608  9\n",
      "7         20  Conv2d   512  ...   features.18       4608  9\n",
      "8         25  Linear  4096  ...  classifier.0       4096  1\n",
      "9         28  Linear  4096  ...  classifier.3       4096  1\n",
      "10        31  Linear  1000  ...  classifier.6       1000  1\n",
      "\n",
      "[11 rows x 9 columns] 11\n",
      "    layer_id    name     M  ...      longname  num_evals rf\n",
      "0          3  Conv2d     3  ...    features.0         27  9\n",
      "1          6  Conv2d    64  ...    features.3        576  9\n",
      "2          9  Conv2d   128  ...    features.6       1152  9\n",
      "3         11  Conv2d   256  ...    features.8       2304  9\n",
      "4         14  Conv2d   256  ...   features.11       2304  9\n",
      "5         16  Conv2d   512  ...   features.13       4608  9\n",
      "6         19  Conv2d   512  ...   features.16       4608  9\n",
      "7         21  Conv2d   512  ...   features.18       4608  9\n",
      "8         26  Linear  4096  ...  classifier.0       4096  1\n",
      "9         29  Linear  4096  ...  classifier.3       4096  1\n",
      "10        32  Linear  1000  ...  classifier.6       1000  1\n",
      "\n",
      "[11 rows x 9 columns]\n",
      "1 3\n",
      "2 6\n",
      "3 9\n",
      "4 11\n",
      "5 14\n",
      "6 16\n",
      "7 19\n",
      "8 21\n",
      "9 26\n",
      "10 29\n",
      "11 32\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_svd_sharpness\n",
      "max esd before 60.278518503997944\n",
      "max esd after 14.729313848460382\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_svd_sharpness2\n",
      "----test_svd_sharpness-----\n",
      "max esd before 7.6678536369389905\n",
      "max esd after 4.981769575236147\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_svd_sharpness_with_model\n",
      "max esd before 60.278518503997944\n",
      "max esd after 14.729313848460382\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_svd_smoothing\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_svd_smoothing_alt\n",
      "----test_svd_smoothing_alt-----\n",
      "num comps = 3277\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_svd_smoothing_alt2\n",
      "----test_svd_smoothing_alt2-----\n",
      "num comps = 819\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_svd_smoothing_with_model\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_switch_channels\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_ww_maxdist\n",
      "   layer_id    name         D  ...  ww_softrank      xmax      xmin\n",
      "0        28  Linear  0.032453  ...     0.336142  60.29372  0.335099\n",
      "\n",
      "[1 rows x 44 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_ww_softrank\n",
      "   ww_softrank  mp_softrank  lambda_max  rand_bulk_max  max_rand_eval\n",
      "0      0.05795     0.024624   58.785088       3.432861       3.384362\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_ww_stacked_layer_details\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Base: test_ww_stacked_layer_iterator\n",
      ".\n",
      "======================================================================\n",
      "FAIL: test_bad_params (tests.test.Test_VGG11_Base)\n",
      "N/A yet\n",
      "----------------------------------------------------------------------\n",
      "Traceback (most recent call last):\n",
      "  File \"/darda/WeightWatcher/tests/test.py\", line 1242, in test_bad_params\n",
      "    self.watcher.describe(ww2x=True)\n",
      "AssertionError: Exception not raised\n",
      "\n",
      "======================================================================\n",
      "FAIL: test_density_fit_on_randomized_W (tests.test.Test_VGG11_Base)\n",
      "Test the fitted sigma from the density fit: FIX\n",
      "----------------------------------------------------------------------\n",
      "Traceback (most recent call last):\n",
      "  File \"/darda/WeightWatcher/tests/test.py\", line 1651, in test_density_fit_on_randomized_W\n",
      "    self.assertAlmostEqual(rand_sigma_mp, 1.0) #sigma_mp\n",
      "AssertionError: 0.9997353619629317 != 1.0 within 7 places (0.0002646380370683321 difference)\n",
      "\n",
      "----------------------------------------------------------------------\n",
      "Ran 59 tests in 552.439s\n",
      "\n",
      "FAILED (failures=2)\n"
     ]
    }
   ],
   "source": [
    "!python -m unittest -k Test_VGG11_Base"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_ESD_model_set\n",
      "    layer_id          name     M  ...      longname  num_evals rf\n",
      "0          1    features.0     3  ...    features.0         27  9\n",
      "1          2    features.3    64  ...    features.3        576  9\n",
      "2          3    features.6   128  ...    features.6       1152  9\n",
      "3          4    features.8   256  ...    features.8       2304  9\n",
      "4          5   features.11   256  ...   features.11       2304  9\n",
      "5          6   features.13   512  ...   features.13       4608  9\n",
      "6          7   features.16   512  ...   features.16       4608  9\n",
      "7          8   features.18   512  ...   features.18       4608  9\n",
      "8          9  classifier.0  4096  ...  classifier.0       4096  1\n",
      "9         10  classifier.3  4096  ...  classifier.3       4096  1\n",
      "10        11  classifier.6  1000  ...  classifier.6       1000  1\n",
      "\n",
      "[11 rows x 9 columns]\n",
      "4096\n",
      "4096\n",
      "max esd before 60.278518503997944\n",
      "max esd after 60.278518503997944\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_N_ge_M\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_all_layer_types\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_analyze_columns\n",
      "Index(['layer_id', 'name', 'D', 'Lambda', 'M', 'N', 'Q', 'alpha',\n",
      "       'alpha_weighted', 'best_fit', 'entropy', 'fit_entropy', 'has_esd',\n",
      "       'lambda_max', 'layer_type', 'log_alpha_norm', 'log_norm',\n",
      "       'log_spectral_norm', 'longname', 'matrix_rank', 'norm', 'num_evals',\n",
      "       'num_fingers', 'num_pl_spikes', 'rank_loss', 'rf', 'sigma',\n",
      "       'spectral_norm', 'stable_rank', 'sv_max', 'warning', 'weak_rank_loss',\n",
      "       'xmax', 'xmin'],\n",
      "      dtype='object')\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_analyze_columns_with_model\n",
      "Index(['layer_id', 'name', 'D', 'Lambda', 'M', 'N', 'Q', 'alpha',\n",
      "       'alpha_weighted', 'best_fit', 'entropy', 'fit_entropy', 'has_esd',\n",
      "       'lambda_max', 'layer_type', 'log_alpha_norm', 'log_norm',\n",
      "       'log_spectral_norm', 'longname', 'matrix_rank', 'norm', 'num_evals',\n",
      "       'num_fingers', 'num_pl_spikes', 'rank_loss', 'rf', 'sigma',\n",
      "       'spectral_norm', 'stable_rank', 'sv_max', 'warning', 'weak_rank_loss',\n",
      "       'xmax', 'xmin'],\n",
      "      dtype='object')\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_bad_params\n",
      "WARNING:weightwatcher:layer filter ids must be all > 0 or < 0: [-1, 1]\n",
      "ERROR:weightwatcher:Error, params not valid: \n",
      " {'glorot_fix': False, 'normalize': False, 'conv2d_norm': True, 'randomize': True, 'savedir': 'ww-img', 'savefig': 'ww-img', 'rescale': True, 'plot': False, 'deltaEs': False, 'intra': False, 'channels': None, 'conv2d_fft': False, 'kernel_fft': False, 'ww2x': False, 'pool': True, 'vectors': True, 'smooth': None, 'stacked': False, 'svd_method': 'accurate', 'fix_fingers': None, 'fit': 'power_law', 'sparsify': True, 'detX': True, 'mp_fit': False, 'min_evals': 0, 'max_evals': None, 'max_N': 10, 'tolerance': 1e-06, 'layer_ids_start': 0, 'add_biases': False, 'pl_package': 'ww', 'xmax': None, 'glorot_fit': False, 'layers': [-1, 1]}\n",
      "WARNING:weightwatcher:KERNEL_FFT option not currently supported, may be deprecated\n",
      "ERROR:weightwatcher:Error, params not valid: \n",
      " {'glorot_fix': False, 'normalize': False, 'conv2d_norm': True, 'randomize': True, 'savedir': 'ww-img', 'savefig': 'ww-img', 'rescale': True, 'plot': False, 'deltaEs': False, 'intra': False, 'channels': None, 'conv2d_fft': False, 'kernel_fft': True, 'ww2x': False, 'pool': True, 'vectors': True, 'smooth': None, 'stacked': False, 'svd_method': 'accurate', 'fix_fingers': None, 'fit': 'power_law', 'sparsify': True, 'detX': True, 'mp_fit': False, 'min_evals': 0, 'max_evals': None, 'max_N': 10, 'tolerance': 1e-06, 'layer_ids_start': 0, 'add_biases': False, 'pl_package': 'ww', 'xmax': None, 'glorot_fit': False, 'layers': []}\n",
      "WARNING:weightwatcher:WW2X option deprecated, reverting too POOL=False\n",
      "F\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_basic_columns\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_basic_columns_with_model\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_basic_columns_with_new_watcher\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_compute_spectral_norms\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_density_fit\n",
      "num spikes 782\n",
      "sigma mp 0.6894768801797752\n",
      "I think something is wrong here\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_density_fit_on_randomized_W\n",
      "rand_num_spikes 1\n",
      "E\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_describe_model\n",
      "    layer_id          name     M  ...      longname  num_evals rf\n",
      "0          1    features.0     3  ...    features.0         27  9\n",
      "1          2    features.3    64  ...    features.3        576  9\n",
      "2          3    features.6   128  ...    features.6       1152  9\n",
      "3          4    features.8   256  ...    features.8       2304  9\n",
      "4          5   features.11   256  ...   features.11       2304  9\n",
      "5          6   features.13   512  ...   features.13       4608  9\n",
      "6          7   features.16   512  ...   features.16       4608  9\n",
      "7          8   features.18   512  ...   features.18       4608  9\n",
      "8          9  classifier.0  4096  ...  classifier.0       4096  1\n",
      "9         10  classifier.3  4096  ...  classifier.3       4096  1\n",
      "10        11  classifier.6  1000  ...  classifier.6       1000  1\n",
      "\n",
      "[11 rows x 9 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_describe_model_ww2x\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_dimensions\n",
      "    layer_id          name     M  ...      longname  num_evals rf\n",
      "0          1    features.0     3  ...    features.0         27  9\n",
      "1          2    features.3    64  ...    features.3        576  9\n",
      "2          3    features.6   128  ...    features.6       1152  9\n",
      "3          4    features.8   256  ...    features.8       2304  9\n",
      "4          5   features.11   256  ...   features.11       2304  9\n",
      "5          6   features.13   512  ...   features.13       4608  9\n",
      "6          7   features.16   512  ...   features.16       4608  9\n",
      "7          8   features.18   512  ...   features.18       4608  9\n",
      "8          9  classifier.0  4096  ...  classifier.0       4096  1\n",
      "9         10  classifier.3  4096  ...  classifier.3       4096  1\n",
      "10        11  classifier.6  1000  ...  classifier.6       1000  1\n",
      "\n",
      "[11 rows x 9 columns]\n",
      "   layer_id        name  M   N  ...         layer_type    longname num_evals  rf\n",
      "0         1  features.0  3  64  ...  LAYER_TYPE.CONV2D  features.0        27   9\n",
      "\n",
      "[1 rows x 9 columns]\n",
      "64 3 9 27\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_filter_conv2D_layer_types\n",
      "   layer_id         name    M  ...     longname  num_evals rf\n",
      "0         1   features.0    3  ...   features.0         27  9\n",
      "1         2   features.3   64  ...   features.3        576  9\n",
      "2         3   features.6  128  ...   features.6       1152  9\n",
      "3         4   features.8  256  ...   features.8       2304  9\n",
      "4         5  features.11  256  ...  features.11       2304  9\n",
      "5         6  features.13  512  ...  features.13       4608  9\n",
      "6         7  features.16  512  ...  features.16       4608  9\n",
      "7         8  features.18  512  ...  features.18       4608  9\n",
      "\n",
      "[8 rows x 9 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_filter_dense_layer_types\n",
      "test_filter_dense_layer_types\n",
      "   layer_id          name     M  ...      longname  num_evals rf\n",
      "0         9  classifier.0  4096  ...  classifier.0       4096  1\n",
      "1        10  classifier.3  4096  ...  classifier.3       4096  1\n",
      "2        11  classifier.6  1000  ...  classifier.6       1000  1\n",
      "\n",
      "[3 rows x 9 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_filter_layer_ids\n",
      "    layer_id          name     M  ...      longname  num_evals rf\n",
      "0          1    features.0     3  ...    features.0         27  9\n",
      "1          2    features.3    64  ...    features.3        576  9\n",
      "2          3    features.6   128  ...    features.6       1152  9\n",
      "3          4    features.8   256  ...    features.8       2304  9\n",
      "4          5   features.11   256  ...   features.11       2304  9\n",
      "5          6   features.13   512  ...   features.13       4608  9\n",
      "6          7   features.16   512  ...   features.16       4608  9\n",
      "7          8   features.18   512  ...   features.18       4608  9\n",
      "8          9  classifier.0  4096  ...  classifier.0       4096  1\n",
      "9         10  classifier.3  4096  ...  classifier.3       4096  1\n",
      "10        11  classifier.6  1000  ...  classifier.6       1000  1\n",
      "\n",
      "[11 rows x 9 columns]\n",
      "   layer_id          name     M  ...      longname  num_evals rf\n",
      "0         9  classifier.0  4096  ...  classifier.0       4096  1\n",
      "1        10  classifier.3  4096  ...  classifier.3       4096  1\n",
      "2        11  classifier.6  1000  ...  classifier.6       1000  1\n",
      "\n",
      "[3 rows x 9 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_fit_entropy_on_layer\n",
      "Calculating best minimal value for power law fit\n",
      ".min progress: 99%\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_getESD\n",
      "    layer_id          name     M  ...      longname  num_evals rf\n",
      "0          1    features.0     3  ...    features.0         27  9\n",
      "1          2    features.3    64  ...    features.3        576  9\n",
      "2          3    features.6   128  ...    features.6       1152  9\n",
      "3          4    features.8   256  ...    features.8       2304  9\n",
      "4          5   features.11   256  ...   features.11       2304  9\n",
      "5          6   features.13   512  ...   features.13       4608  9\n",
      "6          7   features.16   512  ...   features.16       4608  9\n",
      "7          8   features.18   512  ...   features.18       4608  9\n",
      "8          9  classifier.0  4096  ...  classifier.0       4096  1\n",
      "9         10  classifier.3  4096  ...  classifier.3       4096  1\n",
      "10        11  classifier.6  1000  ...  classifier.6       1000  1\n",
      "\n",
      "[11 rows x 9 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_getESD_with_model\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_get_details\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_get_framework_layer\n",
      "F\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_get_summary\n",
      "{'log_norm': 2.1971962, 'alpha': 1.7207916701875228, 'alpha_weighted': 1.141652879015995, 'log_alpha_norm': 2.273003564664541, 'log_spectral_norm': 0.6634463, 'stable_rank': 34.17826}\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_get_summary_with_model\n",
      "{'log_norm': 2.1971962, 'alpha': 1.7207916701875228, 'alpha_weighted': 1.141652879015995, 'log_alpha_norm': 2.273003564664541, 'log_spectral_norm': 0.6634463, 'stable_rank': 34.17826}\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_get_summary_with_new_model\n",
      "{'log_norm': 3.1718328, 'alpha': 2.7404752500854537, 'alpha_weighted': 4.83160523450143, 'log_alpha_norm': 5.178781840348228, 'log_spectral_norm': 1.7630538, 'stable_rank': 25.631802}\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_layer_ids\n",
      "<class 'collections.OrderedDict'>\n",
      "    layer_id          name     M  ...      longname  num_evals rf\n",
      "0          1    features.0     3  ...    features.0         27  9\n",
      "1          2    features.3    64  ...    features.3        576  9\n",
      "2          3    features.6   128  ...    features.6       1152  9\n",
      "3          4    features.8   256  ...    features.8       2304  9\n",
      "4          5   features.11   256  ...   features.11       2304  9\n",
      "5          6   features.13   512  ...   features.13       4608  9\n",
      "6          7   features.16   512  ...   features.16       4608  9\n",
      "7          8   features.18   512  ...   features.18       4608  9\n",
      "8          9  classifier.0  4096  ...  classifier.0       4096  1\n",
      "9         10  classifier.3  4096  ...  classifier.3       4096  1\n",
      "10        11  classifier.6  1000  ...  classifier.6       1000  1\n",
      "\n",
      "[11 rows x 9 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_make_ww_iterator\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_max_matrix_shape\n",
      "   layer_id          name     M  ...      longname  num_evals rf\n",
      "0         1    features.0     3  ...    features.0         27  9\n",
      "1         2    features.3    64  ...    features.3        576  9\n",
      "2        11  classifier.6  1000  ...  classifier.6       1000  1\n",
      "\n",
      "[3 rows x 9 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_min_matrix_shape\n",
      "   layer_id          name     M  ...      longname  num_evals rf\n",
      "0         2    features.3    64  ...    features.3        576  9\n",
      "1         3    features.6   128  ...    features.6       1152  9\n",
      "2         4    features.8   256  ...    features.8       2304  9\n",
      "3         5   features.11   256  ...   features.11       2304  9\n",
      "4         6   features.13   512  ...   features.13       4608  9\n",
      "5         7   features.16   512  ...   features.16       4608  9\n",
      "6         8   features.18   512  ...   features.18       4608  9\n",
      "7         9  classifier.0  4096  ...  classifier.0       4096  1\n",
      "8        10  classifier.3  4096  ...  classifier.3       4096  1\n",
      "9        11  classifier.6  1000  ...  classifier.6       1000  1\n",
      "\n",
      "[10 rows x 9 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_model_layer_types_ww2x\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_mp_fit_columns\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_negative_filter_layer_ids\n",
      "skip these layers [-9, -10, -11]\n",
      "    layer_id          name     M  ...      longname  num_evals rf\n",
      "0          1    features.0     3  ...    features.0         27  9\n",
      "1          2    features.3    64  ...    features.3        576  9\n",
      "2          3    features.6   128  ...    features.6       1152  9\n",
      "3          4    features.8   256  ...    features.8       2304  9\n",
      "4          5   features.11   256  ...   features.11       2304  9\n",
      "5          6   features.13   512  ...   features.13       4608  9\n",
      "6          7   features.16   512  ...   features.16       4608  9\n",
      "7          8   features.18   512  ...   features.18       4608  9\n",
      "8          9  classifier.0  4096  ...  classifier.0       4096  1\n",
      "9         10  classifier.3  4096  ...  classifier.3       4096  1\n",
      "10        11  classifier.6  1000  ...  classifier.6       1000  1\n",
      "\n",
      "[11 rows x 9 columns]\n",
      "   layer_id         name    M  ...     longname  num_evals rf\n",
      "0         1   features.0    3  ...   features.0         27  9\n",
      "1         2   features.3   64  ...   features.3        576  9\n",
      "2         3   features.6  128  ...   features.6       1152  9\n",
      "3         4   features.8  256  ...   features.8       2304  9\n",
      "4         5  features.11  256  ...  features.11       2304  9\n",
      "5         6  features.13  512  ...  features.13       4608  9\n",
      "6         7  features.16  512  ...  features.16       4608  9\n",
      "7         8  features.18  512  ...  features.18       4608  9\n",
      "\n",
      "[8 rows x 9 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_num_evals\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_permute_W\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_permute_W_with_model\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_print_watcher\n",
      "\n",
      "Analysis done: False\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_rand_distance\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_random_mp_fit_columns_\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_randomize\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_randomize_mp_fits\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_rescale_eigenvalues\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_reset_params\n",
      "CRITICAL:weightwatcher:pl_package only supports PowerLaw fits, but fit=TPL\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_rf_value\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_runtime_warnings\n",
      "/darda/WeightWatcher/tests/test.py:1802: RuntimeWarning: invalid value encountered in sqrt\n",
      "  print(\"test runtime warning: sqrt(-1)=\", np.sqrt(-1.0))\n",
      "test runtime warning: sqrt(-1)= nan\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_same_models\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_start_ids_1\n",
      "    layer_id          name     M  ...      longname  num_evals rf\n",
      "0          1    features.0     3  ...    features.0         27  9\n",
      "1          2    features.3    64  ...    features.3        576  9\n",
      "2          3    features.6   128  ...    features.6       1152  9\n",
      "3          4    features.8   256  ...    features.8       2304  9\n",
      "4          5   features.11   256  ...   features.11       2304  9\n",
      "5          6   features.13   512  ...   features.13       4608  9\n",
      "6          7   features.16   512  ...   features.16       4608  9\n",
      "7          8   features.18   512  ...   features.18       4608  9\n",
      "8          9  classifier.0  4096  ...  classifier.0       4096  1\n",
      "9         10  classifier.3  4096  ...  classifier.3       4096  1\n",
      "10        11  classifier.6  1000  ...  classifier.6       1000  1\n",
      "\n",
      "[11 rows x 9 columns] 11\n",
      "    layer_id          name     M  ...      longname  num_evals rf\n",
      "0          1    features.0     3  ...    features.0         27  9\n",
      "1          2    features.3    64  ...    features.3        576  9\n",
      "2          3    features.6   128  ...    features.6       1152  9\n",
      "3          4    features.8   256  ...    features.8       2304  9\n",
      "4          5   features.11   256  ...   features.11       2304  9\n",
      "5          6   features.13   512  ...   features.13       4608  9\n",
      "6          7   features.16   512  ...   features.16       4608  9\n",
      "7          8   features.18   512  ...   features.18       4608  9\n",
      "8          9  classifier.0  4096  ...  classifier.0       4096  1\n",
      "9         10  classifier.3  4096  ...  classifier.3       4096  1\n",
      "10        11  classifier.6  1000  ...  classifier.6       1000  1\n",
      "\n",
      "[11 rows x 9 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_svd_sharpness\n",
      "max esd before 60.278518503997944\n",
      "max esd after 14.729313848460382\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_svd_sharpness2\n",
      "----test_svd_sharpness-----\n",
      "max esd before 7.6678536369389905\n",
      "max esd after 4.981769575236147\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_svd_sharpness_with_model\n",
      "max esd before 60.278518503997944\n",
      "max esd after 14.729313848460382\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_svd_smoothing\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_svd_smoothing_alt\n",
      "----test_svd_smoothing_alt-----\n",
      "num comps = 3277\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_svd_smoothing_alt2\n",
      "----test_svd_smoothing_alt2-----\n",
      "num comps = 819\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_svd_smoothing_with_model\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_switch_channels\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_ww_maxdist\n",
      "   layer_id          name         D  ...  ww_softrank      xmax      xmin\n",
      "0        10  classifier.3  0.032453  ...     0.336004  60.29372  0.335099\n",
      "\n",
      "[1 rows x 44 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_ww_softrank\n",
      "   ww_softrank  mp_softrank  lambda_max  rand_bulk_max  max_rand_eval\n",
      "0     0.057864     0.024624   58.785088       3.437327       3.395412\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_ww_stacked_layer_details\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict: test_ww_stacked_layer_iterator\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict_Alpha_w_WWFit: test_WWFit_available\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict_Alpha_w_WWFit: test_compute_alphas\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict_Alpha_w_WWFit: test_fix_fingers_clip_xmax\n",
      "WARNING:weightwatcher:fix_fingers ignores xmax = None\n",
      "WARNING:weightwatcher:fix_fingers ignores xmax = None\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict_Alpha_w_WWFit: test_fix_fingers_clip_xmax_w_Force\n",
      "WARNING:weightwatcher:clipped fit may be spurious, new alpha found: 12.55\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict_Alpha_w_WWFit: test_kernel_fft\n",
      "WARNING:weightwatcher:KERNEL_FFT option not currently supported, may be deprecated\n",
      "ERROR:weightwatcher:Error, params not valid: \n",
      " {'glorot_fix': False, 'normalize': False, 'conv2d_norm': True, 'randomize': True, 'savedir': 'ww-img', 'savefig': 'ww-img', 'rescale': True, 'plot': False, 'deltaEs': False, 'intra': False, 'channels': None, 'conv2d_fft': False, 'kernel_fft': True, 'ww2x': False, 'pool': True, 'vectors': True, 'smooth': None, 'stacked': False, 'svd_method': 'accurate', 'fix_fingers': None, 'fit': 'power_law', 'sparsify': True, 'detX': True, 'mp_fit': False, 'min_evals': 0, 'max_evals': None, 'max_N': 10, 'tolerance': 1e-06, 'layer_ids_start': 0, 'add_biases': False, 'pl_package': 'ww', 'xmax': None, 'glorot_fit': False, 'layers': [1]}\n",
      "E\n",
      "======================================================================\n",
      "ERROR: test_density_fit_on_randomized_W (tests.test.Test_VGG11_StateDict)\n",
      "Test the fitted sigma from the density fit: FIX\n",
      "----------------------------------------------------------------------\n",
      "Traceback (most recent call last):\n",
      "  File \"/darda/WeightWatcher/tests/test.py\", line 1648, in test_density_fit_on_randomized_W\n",
      "    print(\"sigma mp\", sigma_mp)\n",
      "NameError: name 'sigma_mp' is not defined\n",
      "\n",
      "======================================================================\n",
      "ERROR: test_kernel_fft (tests.test.Test_VGG11_StateDict_Alpha_w_WWFit)\n",
      "Test the FFT method\"; why does this fail ?\n",
      "----------------------------------------------------------------------\n",
      "Traceback (most recent call last):\n",
      "  File \"/darda/WeightWatcher/tests/test.py\", line 2385, in test_kernel_fft\n",
      "    details = self.watcher.describe(layers=[self.first_layer], kernel_fft=True)\n",
      "  File \"/darda/WeightWatcher/weightwatcher/weightwatcher.py\", line 2752, in describe\n",
      "    raise Exception(msg)\n",
      "Exception: Error, params not valid: \n",
      " {'glorot_fix': False, 'normalize': False, 'conv2d_norm': True, 'randomize': True, 'savedir': 'ww-img', 'savefig': 'ww-img', 'rescale': True, 'plot': False, 'deltaEs': False, 'intra': False, 'channels': None, 'conv2d_fft': False, 'kernel_fft': True, 'ww2x': False, 'pool': True, 'vectors': True, 'smooth': None, 'stacked': False, 'svd_method': 'accurate', 'fix_fingers': None, 'fit': 'power_law', 'sparsify': True, 'detX': True, 'mp_fit': False, 'min_evals': 0, 'max_evals': None, 'max_N': 10, 'tolerance': 1e-06, 'layer_ids_start': 0, 'add_biases': False, 'pl_package': 'ww', 'xmax': None, 'glorot_fit': False, 'layers': [1]}\n",
      "\n",
      "======================================================================\n",
      "FAIL: test_bad_params (tests.test.Test_VGG11_StateDict)\n",
      "N/A yet\n",
      "----------------------------------------------------------------------\n",
      "Traceback (most recent call last):\n",
      "  File \"/darda/WeightWatcher/tests/test.py\", line 1242, in test_bad_params\n",
      "    self.watcher.describe(ww2x=True)\n",
      "AssertionError: Exception not raised\n",
      "\n",
      "======================================================================\n",
      "FAIL: test_get_framework_layer (tests.test.Test_VGG11_StateDict)\n",
      "Issue #165, get the underlying framework layer\n",
      "----------------------------------------------------------------------\n",
      "Traceback (most recent call last):\n",
      "  File \"/darda/WeightWatcher/tests/test.py\", line 1122, in test_get_framework_layer\n",
      "    self.assertTrue(isinstance(layer,torch.nn.modules.linear.Linear))\n",
      "AssertionError: False is not true\n",
      "\n",
      "----------------------------------------------------------------------\n",
      "Ran 64 tests in 559.262s\n",
      "\n",
      "FAILED (failures=2, errors=2)\n"
     ]
    }
   ],
   "source": [
    "!python -m unittest -k Test_VGG11_StateDict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-------------------------------------\n",
      "In Test_VGG11_Alpha_w_PowerLawFit: test_compute_alphas\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Alpha_w_PowerLawFit: test_extended_truncated_power_law_fit\n",
      "WARNING:weightwatcher:E-TPL and fix_fingers can not both be set\n",
      "ERROR:weightwatcher:Error, params not valid: \n",
      " {'glorot_fix': False, 'normalize': False, 'conv2d_norm': True, 'randomize': False, 'savedir': 'ww-img', 'savefig': 'ww-img', 'rescale': True, 'plot': False, 'deltaEs': False, 'intra': False, 'channels': None, 'conv2d_fft': False, 'kernel_fft': False, 'ww2x': False, 'pool': True, 'vectors': False, 'smooth': None, 'stacked': False, 'svd_method': 'fast', 'fix_fingers': False, 'fit': 'E_TPL', 'sparsify': True, 'detX': False, 'mp_fit': False, 'min_evals': 50, 'max_evals': 10000, 'max_N': 10, 'tolerance': 1e-06, 'layer_ids_start': 0, 'add_biases': False, 'pl_package': 'powerlaw', 'xmax': 'force', 'glorot_fit': False, False: False, 'layers': [25], 'xmin_max': None}\n",
      "E\n",
      "-------------------------------------\n",
      "In Test_VGG11_Alpha_w_PowerLawFit: test_fix_fingers_clip_xmax_None\n",
      "WARNING:weightwatcher:fix_fingers ignores xmax = None\n",
      "WARNING:weightwatcher:fix_fingers ignores xmax = None\n",
      "WARNING:weightwatcher:fix_fingers ignores xmax = None\n",
      "WARNING:weightwatcher:fix_fingers ignores xmax = None\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Alpha_w_PowerLawFit: test_fix_fingers_clip_xmax_w_Force\n",
      "WARNING:weightwatcher:clipped fit may be spurious, new alpha found: 12.55\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Alpha_w_PowerLawFit: test_fix_fingers_xmin_peak\n",
      "ACTUAL 7.116214252109355\n",
      "WARNING:weightwatcher:fix_fingers ignores xmax = None\n",
      "WARNING:weightwatcher:fix_fingers ignores xmax = None\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Alpha_w_PowerLawFit: test_intra_power_law_fit\n",
      "<class 'list'> [25, 28]\n",
      "2.6582871598100333 lognormal\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Alpha_w_PowerLawFit: test_intra_power_law_fit2\n",
      "<class 'list'> [25, 28]\n",
      "2.721327147678566 lognormal\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Alpha_w_PowerLawFit: test_powerlaw_package_available\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Alpha_w_PowerLawFit: test_truncated_power_law_fit\n",
      ".\n",
      "======================================================================\n",
      "ERROR: test_extended_truncated_power_law_fit (tests.test.Test_VGG11_Alpha_w_PowerLawFit)\n",
      "Test E-TPL fits.  Runs TPL with fix_fingets = XMIN_PEAK\n",
      "----------------------------------------------------------------------\n",
      "Traceback (most recent call last):\n",
      "  File \"/darda/WeightWatcher/tests/test.py\", line 2209, in test_extended_truncated_power_law_fit\n",
      "    details= self.watcher.analyze(layers=[self.fc1_layer], fit=E_TPL, pl_package=POWERLAW_PACKAGE, xmax=XMAX_FORCE)\n",
      "  File \"/darda/WeightWatcher/weightwatcher/weightwatcher.py\", line 2590, in analyze\n",
      "    raise Exception(msg)\n",
      "Exception: Error, params not valid: \n",
      " {'glorot_fix': False, 'normalize': False, 'conv2d_norm': True, 'randomize': False, 'savedir': 'ww-img', 'savefig': 'ww-img', 'rescale': True, 'plot': False, 'deltaEs': False, 'intra': False, 'channels': None, 'conv2d_fft': False, 'kernel_fft': False, 'ww2x': False, 'pool': True, 'vectors': False, 'smooth': None, 'stacked': False, 'svd_method': 'fast', 'fix_fingers': False, 'fit': 'E_TPL', 'sparsify': True, 'detX': False, 'mp_fit': False, 'min_evals': 50, 'max_evals': 10000, 'max_N': 10, 'tolerance': 1e-06, 'layer_ids_start': 0, 'add_biases': False, 'pl_package': 'powerlaw', 'xmax': 'force', 'glorot_fit': False, False: False, 'layers': [25], 'xmin_max': None}\n",
      "\n",
      "----------------------------------------------------------------------\n",
      "Ran 9 tests in 3194.247s\n",
      "\n",
      "FAILED (errors=1)\n"
     ]
    }
   ],
   "source": [
    "!python -m unittest -k Test_VGG11_Alpha_w_PowerLawFit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-------------------------------------\n",
      "In Test_VGG11_Alpha_w_WWFit: test_WWFit_available\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Alpha_w_WWFit: test_compute_alphas\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Alpha_w_WWFit: test_fix_fingers_clip_xmax\n",
      "WARNING:weightwatcher:fix_fingers ignores xmax = None\n",
      "WARNING:weightwatcher:fix_fingers ignores xmax = None\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Alpha_w_WWFit: test_fix_fingers_clip_xmax_w_Force\n",
      "WARNING:weightwatcher:clipped fit may be spurious, new alpha found: 12.55\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_Alpha_w_WWFit: test_kernel_fft\n",
      "WARNING:weightwatcher:KERNEL_FFT option not currently supported, may be deprecated\n",
      "ERROR:weightwatcher:Error, params not valid: \n",
      " {'glorot_fix': False, 'normalize': False, 'conv2d_norm': True, 'randomize': True, 'savedir': 'ww-img', 'savefig': 'ww-img', 'rescale': True, 'plot': False, 'deltaEs': False, 'intra': False, 'channels': None, 'conv2d_fft': False, 'kernel_fft': True, 'ww2x': False, 'pool': True, 'vectors': True, 'smooth': None, 'stacked': False, 'svd_method': 'accurate', 'fix_fingers': None, 'fit': 'power_law', 'sparsify': True, 'detX': True, 'mp_fit': False, 'min_evals': 0, 'max_evals': None, 'max_N': 10, 'tolerance': 1e-06, 'layer_ids_start': 0, 'add_biases': False, 'pl_package': 'ww', 'xmax': None, 'glorot_fit': False, 'layers': [2]}\n",
      "E\n",
      "======================================================================\n",
      "ERROR: test_kernel_fft (tests.test.Test_VGG11_Alpha_w_WWFit)\n",
      "Test the FFT method\"; why does this fail ?\n",
      "----------------------------------------------------------------------\n",
      "Traceback (most recent call last):\n",
      "  File \"/darda/WeightWatcher/tests/test.py\", line 2385, in test_kernel_fft\n",
      "    details = self.watcher.describe(layers=[self.first_layer], kernel_fft=True)\n",
      "  File \"/darda/WeightWatcher/weightwatcher/weightwatcher.py\", line 2752, in describe\n",
      "    raise Exception(msg)\n",
      "Exception: Error, params not valid: \n",
      " {'glorot_fix': False, 'normalize': False, 'conv2d_norm': True, 'randomize': True, 'savedir': 'ww-img', 'savefig': 'ww-img', 'rescale': True, 'plot': False, 'deltaEs': False, 'intra': False, 'channels': None, 'conv2d_fft': False, 'kernel_fft': True, 'ww2x': False, 'pool': True, 'vectors': True, 'smooth': None, 'stacked': False, 'svd_method': 'accurate', 'fix_fingers': None, 'fit': 'power_law', 'sparsify': True, 'detX': True, 'mp_fit': False, 'min_evals': 0, 'max_evals': None, 'max_N': 10, 'tolerance': 1e-06, 'layer_ids_start': 0, 'add_biases': False, 'pl_package': 'ww', 'xmax': None, 'glorot_fit': False, 'layers': [2]}\n",
      "\n",
      "----------------------------------------------------------------------\n",
      "Ran 5 tests in 16.320s\n",
      "\n",
      "FAILED (errors=1)\n"
     ]
    }
   ],
   "source": [
    "!python -m unittest -k Test_VGG11_Alpha_w_WWFit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict_Alpha_w_WWFit: test_WWFit_available\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict_Alpha_w_WWFit: test_compute_alphas\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict_Alpha_w_WWFit: test_fix_fingers_clip_xmax\n",
      "WARNING:weightwatcher:fix_fingers ignores xmax = None\n",
      "WARNING:weightwatcher:fix_fingers ignores xmax = None\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict_Alpha_w_WWFit: test_fix_fingers_clip_xmax_w_Force\n",
      "WARNING:weightwatcher:clipped fit may be spurious, new alpha found: 12.55\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_VGG11_StateDict_Alpha_w_WWFit: test_kernel_fft\n",
      "WARNING:weightwatcher:KERNEL_FFT option not currently supported, may be deprecated\n",
      "ERROR:weightwatcher:Error, params not valid: \n",
      " {'glorot_fix': False, 'normalize': False, 'conv2d_norm': True, 'randomize': True, 'savedir': 'ww-img', 'savefig': 'ww-img', 'rescale': True, 'plot': False, 'deltaEs': False, 'intra': False, 'channels': None, 'conv2d_fft': False, 'kernel_fft': True, 'ww2x': False, 'pool': True, 'vectors': True, 'smooth': None, 'stacked': False, 'svd_method': 'accurate', 'fix_fingers': None, 'fit': 'power_law', 'sparsify': True, 'detX': True, 'mp_fit': False, 'min_evals': 0, 'max_evals': None, 'max_N': 10, 'tolerance': 1e-06, 'layer_ids_start': 0, 'add_biases': False, 'pl_package': 'ww', 'xmax': None, 'glorot_fit': False, 'layers': [1]}\n",
      "E\n",
      "======================================================================\n",
      "ERROR: test_kernel_fft (tests.test.Test_VGG11_StateDict_Alpha_w_WWFit)\n",
      "Test the FFT method\"; why does this fail ?\n",
      "----------------------------------------------------------------------\n",
      "Traceback (most recent call last):\n",
      "  File \"/darda/WeightWatcher/tests/test.py\", line 2385, in test_kernel_fft\n",
      "    details = self.watcher.describe(layers=[self.first_layer], kernel_fft=True)\n",
      "  File \"/darda/WeightWatcher/weightwatcher/weightwatcher.py\", line 2752, in describe\n",
      "    raise Exception(msg)\n",
      "Exception: Error, params not valid: \n",
      " {'glorot_fix': False, 'normalize': False, 'conv2d_norm': True, 'randomize': True, 'savedir': 'ww-img', 'savefig': 'ww-img', 'rescale': True, 'plot': False, 'deltaEs': False, 'intra': False, 'channels': None, 'conv2d_fft': False, 'kernel_fft': True, 'ww2x': False, 'pool': True, 'vectors': True, 'smooth': None, 'stacked': False, 'svd_method': 'accurate', 'fix_fingers': None, 'fit': 'power_law', 'sparsify': True, 'detX': True, 'mp_fit': False, 'min_evals': 0, 'max_evals': None, 'max_N': 10, 'tolerance': 1e-06, 'layer_ids_start': 0, 'add_biases': False, 'pl_package': 'ww', 'xmax': None, 'glorot_fit': False, 'layers': [1]}\n",
      "\n",
      "----------------------------------------------------------------------\n",
      "Ran 5 tests in 16.162s\n",
      "\n",
      "FAILED (errors=1)\n"
     ]
    }
   ],
   "source": [
    "!python -m unittest -k Test_VGG11_StateDict_Alpha_w_WWFit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-------------------------------------\n",
      "In Test_Keras: test_N_ge_M\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_Keras: test_basic_columns\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_Keras: test_channels_first\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_Keras: test_kayer_ids\n",
      "    layer_id          name     M  ...  longname  num_evals rf\n",
      "0          1  block1_conv1     3  ...      None         27  9\n",
      "1          2  block1_conv2    64  ...      None        576  9\n",
      "2          4  block2_conv1    64  ...      None        576  9\n",
      "3          5  block2_conv2   128  ...      None       1152  9\n",
      "4          7  block3_conv1   128  ...      None       1152  9\n",
      "5          8  block3_conv2   256  ...      None       2304  9\n",
      "6          9  block3_conv3   256  ...      None       2304  9\n",
      "7         11  block4_conv1   256  ...      None       2304  9\n",
      "8         12  block4_conv2   512  ...      None       4608  9\n",
      "9         13  block4_conv3   512  ...      None       4608  9\n",
      "10        15  block5_conv1   512  ...      None       4608  9\n",
      "11        16  block5_conv2   512  ...      None       4608  9\n",
      "12        17  block5_conv3   512  ...      None       4608  9\n",
      "13        20           fc1  4096  ...      None       4096  1\n",
      "14        21           fc2  4096  ...      None       4096  1\n",
      "15        22   predictions  1000  ...      None       1000  1\n",
      "\n",
      "[16 rows x 9 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_Keras: test_keras_model_with_no_bias\n",
      "   layer_id     name    M    N     Q        layer_type longname  num_evals  rf\n",
      "0         0    dense  100  190   1.9  LAYER_TYPE.DENSE     None        100   1\n",
      "1         2  dense_1   10  100  10.0  LAYER_TYPE.DENSE     None         10   1\n",
      "   layer_id   name         D  ...  weak_rank_loss      xmax      xmin\n",
      "0         0  dense  0.137323  ...               0  3.809343  1.891676\n",
      "\n",
      "[1 rows x 34 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_Keras: test_layer_ids\n",
      "    layer_id          name     M  ...  longname  num_evals rf\n",
      "0          1  block1_conv1     3  ...      None         27  9\n",
      "1          2  block1_conv2    64  ...      None        576  9\n",
      "2          4  block2_conv1    64  ...      None        576  9\n",
      "3          5  block2_conv2   128  ...      None       1152  9\n",
      "4          7  block3_conv1   128  ...      None       1152  9\n",
      "5          8  block3_conv2   256  ...      None       2304  9\n",
      "6          9  block3_conv3   256  ...      None       2304  9\n",
      "7         11  block4_conv1   256  ...      None       2304  9\n",
      "8         12  block4_conv2   512  ...      None       4608  9\n",
      "9         13  block4_conv3   512  ...      None       4608  9\n",
      "10        15  block5_conv1   512  ...      None       4608  9\n",
      "11        16  block5_conv2   512  ...      None       4608  9\n",
      "12        17  block5_conv3   512  ...      None       4608  9\n",
      "13        20           fc1  4096  ...      None       4096  1\n",
      "14        21           fc2  4096  ...      None       4096  1\n",
      "15        22   predictions  1000  ...      None       1000  1\n",
      "\n",
      "[16 rows x 9 columns]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_Keras: test_num_layers\n",
      "Testing Keras on VGG16\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_Keras: test_num_layers_with_model\n",
      "Testing Keras on VGG16\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_KerasLayers: test_keras_layer_constructor\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_KerasLayers: test_replace_weights_and_biases\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_KerasLayers: test_replace_weights_only\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_KerasLayers: test_ww_layer_attributes\n",
      "the longname is None\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_KerasLayers: test_ww_layer_iterator\n",
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 13 tests in 37.271s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "!python -m unittest -k Test_Keras"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "..\n",
      "-------------------------------------\n",
      "In Test_ResNet_Models: test_num_evals\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_ResNet_Models: test_weight_watcher\n",
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 4 tests in 2.085s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "!python -m unittest -k Test_ResNet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-------------------------------------\n",
      "In Test_ResNet_Models: test_num_evals\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_ResNet_Models: test_weight_watcher\n",
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 2 tests in 1.257s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "!python -m unittest -k Test_ResNet_Models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-------------------------------------\n",
      "In Test_RMT_Util: test_combine_weights_and_biases\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_RMT_Util: test_detX_constraint\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_RMT_Util: test_line_entropy\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_RMT_Util: test_permute_matrix\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_RMT_Util: test_vector_entropy\n",
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 5 tests in 0.910s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "!python -m unittest -k Test_RMT_Util"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-------------------------------------\n",
      "In Test_Vector_Metrics: test_valid_vectors\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_Vector_Metrics: test_vector_iterator\n",
      "v=  [0 1 2 3 4]\n",
      "v=  [0 1 2 3 4]\n",
      "v=  [0 1 2 3 4]\n",
      "v=  [0 1 2 3 4]\n",
      "v=  [0 1 2 3 4]\n",
      "v=  [0 1 2 3 4]\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_Vector_Metrics: test_vector_metrics\n",
      "/darda/WeightWatcher/weightwatcher/weightwatcher.py:2319: FutureWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.\n",
      "  df.loc[iv] = None\n",
      "   length   entropy  ...  participation_ratio  discete_entropy\n",
      "0     5.0  0.025796  ...             1.262728         1.609438\n",
      "\n",
      "[1 rows x 6 columns]\n",
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 3 tests in 0.603s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "!python -m unittest -k Test_Vector_Metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "----------------------------------------------------------------------\n",
      "Ran 0 tests in 0.000s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "!python -m unittest -k Test_Distances"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-------------------------------------\n",
      "In Test_PyTorchSVD: test_bad_methods\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_PyTorchSVD: test_torch_availability\n",
      "torch is available and cuda is available\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_PyTorchSVD: test_torch_linalg\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_PyTorchSVD: test_torch_svd\n",
      "PyTorch (fast): 7.375410318374634s\n",
      "SciPy (accurate): 38.66134762763977s\n",
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 4 tests in 51.293s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "!python -m unittest -k Test_PyTorchSVD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-------------------------------------\n",
      "In Test_PowerLaw: test_PL_speed\n",
      "Calculating best minimal value for power law fit\n",
      "WW powerlaw time is 5.97x faster with M = 512\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_PowerLaw: test_fit_attributes\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_PowerLaw: test_fit_clipped_powerlaw\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_PowerLaw: test_ww_power_law_fit_directly\n",
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 4 tests in 5.275s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "!python -m unittest -k Test_PowerLaw"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-------------------------------------\n",
      "In Test_Plots: testPlots\n",
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 1 test in 7.875s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "!python -m unittest -k Test_Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-------------------------------------\n",
      "In Test_Pandas: test_column_names_analyze\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_Pandas: test_column_names_analyze_detX\n",
      "/home/hman/anaconda3/envs/kaggle/lib/python3.9/site-packages/numpy/core/fromnumeric.py:86: RuntimeWarning: overflow encountered in reduce\n",
      "  return ufunc.reduce(obj, axis, dtype, out, **passkwargs)\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_Pandas: test_column_names_analyze_intra\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_Pandas: test_column_names_analyze_mp_fit\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_Pandas: test_column_names_analyze_randomize\n",
      ".\n",
      "-------------------------------------\n",
      "In Test_Pandas: test_column_names_describe_basic\n",
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 6 tests in 8.132s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "!python -m unittest -k Test_Pandas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "4KhAqmYFZvij"
   },
   "source": [
    "### Deploy to test pypi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "Siilv3JpZu-o",
    "outputId": "95598d4d-ee7b-4730-8bcc-ae6ccb128596"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
      "Requirement already satisfied: setuptools in /usr/local/lib/python3.8/dist-packages (57.4.0)\n",
      "Collecting setuptools\n",
      "  Downloading setuptools-67.1.0-py3-none-any.whl (1.1 MB)\n",
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      "\u001b[?25hRequirement already satisfied: wheel in /usr/local/lib/python3.8/dist-packages (0.38.4)\n",
      "Collecting twine\n",
      "  Downloading twine-4.0.2-py3-none-any.whl (36 kB)\n",
      "Collecting pkginfo>=1.8.1\n",
      "  Downloading pkginfo-1.9.6-py3-none-any.whl (30 kB)\n",
      "Requirement already satisfied: requests>=2.20 in /usr/local/lib/python3.8/dist-packages (from twine) (2.25.1)\n",
      "Collecting rfc3986>=1.4.0\n",
      "  Downloading rfc3986-2.0.0-py2.py3-none-any.whl (31 kB)\n",
      "Collecting requests-toolbelt!=0.9.0,>=0.8.0\n",
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      "Collecting readme-renderer>=35.0\n",
      "  Downloading readme_renderer-37.3-py3-none-any.whl (14 kB)\n",
      "Collecting urllib3>=1.26.0\n",
      "  Downloading urllib3-1.26.14-py2.py3-none-any.whl (140 kB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m140.6/140.6 KB\u001b[0m \u001b[31m14.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25hCollecting keyring>=15.1\n",
      "  Downloading keyring-23.13.1-py3-none-any.whl (37 kB)\n",
      "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.8/dist-packages (from importlib-metadata>=3.6->twine) (3.12.0)\n",
      "Collecting jaraco.classes\n",
      "  Downloading jaraco.classes-3.2.3-py3-none-any.whl (6.0 kB)\n",
      "Requirement already satisfied: importlib-resources in /usr/local/lib/python3.8/dist-packages (from keyring>=15.1->twine) (5.10.2)\n",
      "Collecting SecretStorage>=3.2\n",
      "  Downloading SecretStorage-3.3.3-py3-none-any.whl (15 kB)\n",
      "Collecting jeepney>=0.4.2\n",
      "  Downloading jeepney-0.8.0-py3-none-any.whl (48 kB)\n",
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      "Requirement already satisfied: chardet<5,>=3.0.2 in /usr/local/lib/python3.8/dist-packages (from requests>=2.20->twine) (4.0.0)\n",
      "Requirement already satisfied: typing-extensions<5.0,>=4.0.0 in /usr/local/lib/python3.8/dist-packages (from rich>=12.0.0->twine) (4.4.0)\n",
      "Collecting markdown-it-py<3.0.0,>=2.1.0\n",
      "  Downloading markdown_it_py-2.1.0-py3-none-any.whl (84 kB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m84.5/84.5 KB\u001b[0m \u001b[31m9.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25hCollecting Pygments>=2.5.1\n",
      "  Downloading Pygments-2.14.0-py3-none-any.whl (1.1 MB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.1/1.1 MB\u001b[0m \u001b[31m41.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25hRequirement already satisfied: webencodings in /usr/local/lib/python3.8/dist-packages (from bleach>=2.1.0->readme-renderer>=35.0->twine) (0.5.1)\n",
      "Requirement already satisfied: six>=1.9.0 in /usr/local/lib/python3.8/dist-packages (from bleach>=2.1.0->readme-renderer>=35.0->twine) (1.15.0)\n",
      "Collecting mdurl~=0.1\n",
      "  Downloading mdurl-0.1.2-py3-none-any.whl (10.0 kB)\n",
      "Collecting cryptography>=2.0\n",
      "  Downloading cryptography-39.0.0-cp36-abi3-manylinux_2_28_x86_64.whl (4.2 MB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m4.2/4.2 MB\u001b[0m \u001b[31m76.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25hRequirement already satisfied: more-itertools in /usr/local/lib/python3.8/dist-packages (from jaraco.classes->keyring>=15.1->twine) (9.0.0)\n",
      "Requirement already satisfied: cffi>=1.12 in /usr/local/lib/python3.8/dist-packages (from cryptography>=2.0->SecretStorage>=3.2->keyring>=15.1->twine) (1.15.1)\n",
      "Requirement already satisfied: pycparser in /usr/local/lib/python3.8/dist-packages (from cffi>=1.12->cryptography>=2.0->SecretStorage>=3.2->keyring>=15.1->twine) (2.21)\n",
      "Installing collected packages: urllib3, setuptools, rfc3986, Pygments, pkginfo, mdurl, jeepney, jaraco.classes, readme-renderer, markdown-it-py, cryptography, SecretStorage, rich, requests-toolbelt, keyring, twine\n",
      "  Attempting uninstall: urllib3\n",
      "    Found existing installation: urllib3 1.24.3\n",
      "    Uninstalling urllib3-1.24.3:\n",
      "      Successfully uninstalled urllib3-1.24.3\n",
      "  Attempting uninstall: setuptools\n",
      "    Found existing installation: setuptools 57.4.0\n",
      "    Uninstalling setuptools-57.4.0:\n",
      "      Successfully uninstalled setuptools-57.4.0\n",
      "  Attempting uninstall: Pygments\n",
      "    Found existing installation: Pygments 2.6.1\n",
      "    Uninstalling Pygments-2.6.1:\n",
      "      Successfully uninstalled Pygments-2.6.1\n",
      "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
      "ipython 7.9.0 requires jedi>=0.10, which is not installed.\n",
      "cvxpy 1.2.3 requires setuptools<=64.0.2, but you have setuptools 67.1.0 which is incompatible.\u001b[0m\u001b[31m\n",
      "\u001b[0mSuccessfully installed Pygments-2.14.0 SecretStorage-3.3.3 cryptography-39.0.0 jaraco.classes-3.2.3 jeepney-0.8.0 keyring-23.13.1 markdown-it-py-2.1.0 mdurl-0.1.2 pkginfo-1.9.6 readme-renderer-37.3 requests-toolbelt-0.10.1 rfc3986-2.0.0 rich-13.3.1 setuptools-67.1.0 twine-4.0.2 urllib3-1.26.14\n",
      "/usr/local/lib/python3.8/dist-packages/setuptools/dist.py:775: UserWarning: Usage of dash-separated 'description-file' will not be supported in future versions. Please use the underscore name 'description_file' instead\n",
      "  warnings.warn(\n",
      "error in weightwatcher setup command: 'python_requires' must be a string containing valid version specifiers; Invalid specifier: '>= 3.3.*'\n",
      "Checking dist/weightwatcher-0.6.4.1-py3.8.egg: \u001b[32mPASSED\u001b[0m\n",
      "weightwatcher-0.6.4.1-py3.8.egg\n"
     ]
    }
   ],
   "source": [
    "!python -m pip install --upgrade setuptools wheel twine\n",
    "!python setup.py sdist bdist_wheel\n",
    "!twine check dist/*\n",
    "!ls dist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "vVf89jPdZ8tS"
   },
   "outputs": [],
   "source": [
    "#!twine upload --repository testpypi dist/*\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 169
    },
    "id": "6MB-2fulKYiA",
    "outputId": "fd157a27-d39c-49a5-cb1f-b9503d0190fd"
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "ignored",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-7-48a517fe9889>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mcharles\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m: name 'charles' is not defined"
     ]
    }
   ],
   "source": [
    "charles"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "authorship_tag": "ABX9TyObaKJ1PL5IPCqxk8Jj45FK",
   "include_colab_link": true,
   "provenance": []
  },
  "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": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}