vae-mmd.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import cm\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import json\n",
    "import os\n",
    "from pandas.io.json import json_normalize\n",
    "from functools import partial\n",
    "from pdb import set_trace\n",
    "\n",
    "from datetime import datetime, timedelta\n",
    "import urllib.request\n",
    "\n",
    "from fastai.vision.all import *\n",
    "from fastai.tabular.all import *\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import platform\n",
    "sys = platform.system()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "url = URLs.MNIST\n",
    "path = untar_data(url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "class PILImageBWNoised(PILImageBW): pass\n",
    "class TensorImageBWNoised(TensorImageBW): pass\n",
    "PILImageBWNoised._tensor_cls = TensorImageBWNoised\n",
    "\n",
    "class PILImageTarget(PILImageBW): pass\n",
    "class TensorImageTarget(TensorImageBW): pass\n",
    "PILImageTarget._tensor_cls = TensorImageTarget\n",
    "\n",
    "@Normalize\n",
    "def encodes(self, to:TensorImageTarget): return to\n",
    "\n",
    "class AddNoiseTransform(Transform):\n",
    "    \"Add noise to image\"\n",
    "    order = 11\n",
    "    def __init__(self, noise_factor=0.1): self.noise_factor=noise_factor\n",
    "    def encodes(self, o:TensorImageBWNoised): return (o + (self.noise_factor * torch.randn(*o.shape).to(o.device))).clamp(0,1)\n",
    "\n",
    "mnist = DataBlock(blocks=(ImageBlock(cls=PILImageBWNoised), ImageBlock(cls=PILImageTarget)), \n",
    "                 get_items=get_image_files,\n",
    "                 get_x= [noop],\n",
    "                 splitter=GrandparentSplitter(train_name='training' if url == URLs.MNIST else 'train', valid_name='testing' if url == URLs.MNIST else 'valid'),\n",
    "                 batch_tfms=[AddNoiseTransform(0), Normalize()],\n",
    "                 n_inp=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dls = mnist.dataloaders(path, num_workers=0 if sys != 'Linux' else 8, bs=1024)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "class UnFlatten(Module):\n",
    "    def __init__(self, size=7):\n",
    "        self.size = size\n",
    "    def forward(self, input):\n",
    "        return input.view(input.size(0), -1, self.size, self.size)\n",
    "\n",
    "class VAE(nn.Module):\n",
    "    def __init__(self, image_channels=3, h_dim=1024, z_dim=32, dropout=.01):\n",
    "        super(VAE, self).__init__()\n",
    "        self.z_dim = z_dim\n",
    "        kernel_size = 2\n",
    "        self.encoder = nn.Sequential(\n",
    "            ResBlock(1, 1, 16, act_cls=nn.ReLU, norm_type=None),\n",
    "            nn.MaxPool2d(2, 2),\n",
    "            ResBlock(1, 16, 4, act_cls=nn.ReLU, norm_type=None),\n",
    "            nn.MaxPool2d(2, 2),\n",
    "            Flatten()\n",
    "        )\n",
    "        \n",
    "        last_size = model_sizes(self.encoder, size=(28,28))[-1][1]\n",
    "        \n",
    "        self.encoder = nn.Sequential(self.encoder, nn.Linear(last_size, z_dim))\n",
    "        \n",
    "        self.decoder = nn.Sequential(\n",
    "            nn.Linear(z_dim, last_size),\n",
    "            UnFlatten(),\n",
    "            ResBlock(1, 4, 8, ks=1, act_cls=nn.ReLU, norm_type=None),\n",
    "            nn.Dropout2d(dropout),\n",
    "            nn.Upsample(scale_factor=2),\n",
    "            ResBlock(1, 8, 16, act_cls=nn.ReLU, norm_type=None),\n",
    "            nn.Dropout2d(dropout),\n",
    "            nn.Upsample(scale_factor=2),\n",
    "            nn.Conv2d(16, 1, 3, padding=1),\n",
    "            nn.Dropout2d(dropout),\n",
    "            nn.Sigmoid()\n",
    "        )\n",
    "        \n",
    "        \n",
    "\n",
    "    def encode(self, x):\n",
    "        h = self.encoder(x)\n",
    "\n",
    "        return h\n",
    "\n",
    "    def decode(self, z):        \n",
    "        img = self.decoder(z)\n",
    "        return img\n",
    "\n",
    "    def forward(self, x):\n",
    "        z = self.encode(x)\n",
    "        img = self.decode(z)\n",
    "        return img, z\n",
    "    \n",
    "    def inference(self, n=1, c=None):\n",
    "\n",
    "        batch_size = n\n",
    "        z = torch.randn([batch_size, self.latent_size])\n",
    "\n",
    "        recon_x = self.decoder(z, c)\n",
    "\n",
    "        return recon_x\n",
    "    \n",
    "model = VAE(image_channels=1, h_dim=196, z_dim=128, dropout=.1).cuda()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Reshape(nn.Module):\n",
    "    '''\n",
    "        Used in a nn.Sequential pipeline to reshape on the fly.\n",
    "    '''\n",
    "    def __init__(self, *target_shape):\n",
    "        super().__init__()\n",
    "        self.target_shape = target_shape\n",
    "    \n",
    "    def forward(self, x):\n",
    "        return x.view(*self.target_shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "class MMD_VAE(Module):\n",
    "    def __init__(self, latent_size):        \n",
    "        self.encoder = nn.Sequential(\n",
    "            ResBlock(1, 1, 5, stride=2, act_cls=Mish),\n",
    "            ResBlock(1, 5, 5, stride=2, act_cls=Mish),\n",
    "            ResBlock(1, 5, 1, stride=2, act_cls=Mish),\n",
    "            Flatten(),\n",
    "            nn.Linear(16, latent_size)\n",
    "        )\n",
    "        \n",
    "        dropout=0\n",
    "        \n",
    "        self.decoder = nn.Sequential(\n",
    "            nn.Linear(latent_size, 16),\n",
    "            UnFlatten(4),\n",
    "            ResBlock(1, 1, 4, act_cls=Mish),\n",
    "            nn.Dropout2d(dropout),\n",
    "            nn.Upsample(scale_factor=2),\n",
    "            ResBlock(1, 4, 8, act_cls=Mish),\n",
    "            nn.Dropout2d(dropout),\n",
    "            nn.Upsample(scale_factor=2),\n",
    "            ResBlock(1, 8, 16, act_cls=Mish),\n",
    "            nn.Dropout2d(dropout),\n",
    "            nn.Upsample(scale_factor=2),\n",
    "            nn.Conv2d(16, 1, 3),\n",
    "            nn.Dropout2d(dropout),\n",
    "            nn.AdaptiveAvgPool2d((28, 28)),\n",
    "            nn.Sigmoid()\n",
    "        )\n",
    "        \n",
    "#         last_size = model_sizes(self.decoder, size=(16,16))[-1][1]\n",
    "#         breakpoint()\n",
    "    \n",
    "    def forward(self, X):\n",
    "        latent = self.encoder(X)\n",
    "        return self.decoder(latent), latent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "onebatch = dls.one_batch()\n",
    "img, targets_img = onebatch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = MMD_VAE(4).cuda()\n",
    "with torch.no_grad():\n",
    "    res = model(img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "res[0].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "class L2Metric(Metric):\n",
    "    def __init__(self): self.preds = []\n",
    "    def accumulate(self, learn):\n",
    "        x = to_detach(learn.y)\n",
    "        recon_x = to_detach(learn.pred[0])\n",
    "        nll = torch.mean((recon_x - x)**2)\n",
    "        self.preds.append(nll)\n",
    "    @property\n",
    "    def value(self):\n",
    "        return np.array(self.preds).mean()\n",
    "    \n",
    "class MMDMetric(Metric):\n",
    "    def __init__(self, alpha=1):\n",
    "        self.preds = []\n",
    "        store_attr('alpha')\n",
    "        \n",
    "    def accumulate(self, learn):\n",
    "        \n",
    "        z = to_detach(learn.pred[1])\n",
    "        hidden_size = z.shape[1]\n",
    "        true_samples = torch.randn((learn.pred[0].shape[0],hidden_size), requires_grad=False)\n",
    "\n",
    "        mmd_loss = MMD(true_samples, z) * self.alpha\n",
    "        \n",
    "        self.preds.append(mmd_loss)\n",
    "    @property\n",
    "    def value(self):\n",
    "        return np.array(self.preds).mean()\n",
    "\n",
    "def gaussian_kernel(a, b):\n",
    "    dim1_1, dim1_2 = a.shape[0], b.shape[0]\n",
    "    depth = a.shape[1]\n",
    "    a = a.view(dim1_1, 1, depth)\n",
    "    b = b.view(1, dim1_2, depth)\n",
    "    a_core = a.expand(dim1_1, dim1_2, depth)\n",
    "    b_core = b.expand(dim1_1, dim1_2, depth)\n",
    "    numerator = (a_core - b_core).pow(2).mean(2)/depth\n",
    "    return torch.exp(-numerator)\n",
    "\n",
    "def MMD(a, b):\n",
    "    return gaussian_kernel(a, a).mean() + gaussian_kernel(b, b).mean() - 2*gaussian_kernel(a, b).mean()\n",
    "    \n",
    "    \n",
    "class LossVAE(Module):\n",
    "    def __init__(self, alpha=1):\n",
    "        store_attr('alpha')\n",
    "        \n",
    "    def forward(self, output, x):\n",
    "        recon_x, z = output\n",
    "    \n",
    "        bs = recon_x.shape[0]\n",
    "        hidden_size = z.shape[1]\n",
    "\n",
    "        nll = torch.mean((recon_x - x)**2)\n",
    "\n",
    "        true_samples = torch.randn((bs,hidden_size), requires_grad=False).cuda()\n",
    "\n",
    "        mmd_loss = MMD(true_samples, z) * self.alpha\n",
    "\n",
    "        return nll + mmd_loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "@typedispatch\n",
    "def wandb_process(x:tuple, y:TensorImageTarget, samples, outs):\n",
    "    img_input, category = x\n",
    "    img_preds, z = outs\n",
    "    \n",
    "    img_inputs = []\n",
    "    for img, cat,target,pred in zip(img_input, category, y, img_preds):\n",
    "        i = torch.cat([img.clamp(0,1), target, pred], dim=2).squeeze(0)\n",
    "        img_inputs += [wandb.Image(i)]\n",
    "    \n",
    "    return {\"Predictions\": img_inputs}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import wandb\n",
    "from fastai.callback.wandb import *\n",
    "\n",
    "# wandb.init(project='VAE-MNIST-MMD')\n",
    "\n",
    "alpha = 1\n",
    "hidden_size = 128\n",
    "\n",
    "class WandbCallbackCustom(WandbCallback):\n",
    "    def log_predictions(self, preds):\n",
    "        inp,preds,targs,out = preds\n",
    "        tolog = wandb_process(inp, targs, inp, preds)\n",
    "        \n",
    "#         num = 10 if url == URLs.MNIST else 2\n",
    "#         fig, axes = plt.subplots(ncols=num, nrows=10, figsize=(19,19))\n",
    "        \n",
    "#         i = 0\n",
    "#         with torch.no_grad():\n",
    "#             self.model.eval()\n",
    "#             for row in axes:\n",
    "#                 z = torch.empty([num,128]).normal_().cuda()\n",
    "#                 img = self.model.decode(z.half(), torch.Tensor(range(num)).long().cuda()).detach().cpu().float()\n",
    "#                 for ax in row:\n",
    "#                     ax.imshow(img[i%num][0], cmap='Greys')\n",
    "#                     ax.axis('off')`\n",
    "#                     ax.set_title(str(i%num))\n",
    "#                     i += 1\n",
    "#             self.model.train()\n",
    "        \n",
    "#         tolog['Samples'] = [wandb.Image(fig)]\n",
    "        \n",
    "        wandb.log(tolog, step=self._wandb_step)\n",
    "        \n",
    "def prepare_preds(preds):\n",
    "    inp,preds,targs,out = preds\n",
    "    return inp, targs, inp, preds\n",
    "\n",
    "\n",
    "cbs=[]\n",
    "# cbs += [EarlyStoppingCallback(patience=2)]\n",
    "# cbs += [WandbCallbackCustom(reorder=False, n_preds=20)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# model = VAE(image_channels=1, h_dim=196, z_dim=128).cuda()\n",
    "model = MMD_VAE(4)\n",
    "\n",
    "learn = Learner(dls, model, cbs=cbs, loss_func=LossVAE(alpha), metrics=[L2Metric(), MMDMetric(alpha)],opt_func=ranger)\n",
    "learn = learn.to_fp16()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "learn.fit_one_cycle(30)\n",
    "\n",
    "# learn.save(datetime.now().strftime('%Y-%m-%d %Hh%M.%S') + '.model')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 265,
   "metadata": {},
   "outputs": [
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\n",
      "text/plain": [
       "<Figure size 720x1368 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "b = learn.dls[0].one_batch()\n",
    "input_img, targets = to_detach(b)\n",
    "preds, targs = learn.get_preds(dl=[b], reorder=False)\n",
    "imgs, _ = preds\n",
    "\n",
    "_, axes = plt.subplots(ncols=1, nrows=10, constrained_layout=True, figsize=(10, 19))\n",
    "i = 0\n",
    "for a in axes:\n",
    "#     a.set_title(nums[i].cpu().item())\n",
    "    img = torch.cat([TensorBase(input_img.clamp(0,1)), TensorBase(targs), imgs], dim=3)[i].squeeze(0).cpu()\n",
    "    a.imshow(img, cmap='Greys')\n",
    "    a.axis('off')\n",
    "    i = i + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 266,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1368x1368 with 100 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# %debug\n",
    "num = 10 if url == URLs.MNIST else 2\n",
    "_, axes = plt.subplots(ncols=num, nrows=10, figsize=(19,19))\n",
    "learn.model.eval()\n",
    "i = 0\n",
    "with torch.no_grad():\n",
    "    for row in axes:\n",
    "        z = torch.empty([num,4]).normal_().cuda()\n",
    "        img = learn.model.decoder(z).detach().cpu()\n",
    "        for ax in row:\n",
    "            ax.imshow(img[i%num][0], cmap='Greys')\n",
    "            ax.axis('off')\n",
    "            ax.set_title(str(i%num))\n",
    "            i += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 267,
   "metadata": {},
   "outputs": [],
   "source": [
    "from itertools import product\n",
    "\n",
    "#Manages device/graph status/type handling\n",
    "def from_latent(net, vec):\n",
    "    with torch.no_grad():\n",
    "        net.eval()\n",
    "        return net.decoder( torch.tensor(vec).to('cuda').float()[None,:] ).cpu().detach().numpy().reshape(28,28)\n",
    "\n",
    "def get_sampling_grid(net, grid):\n",
    "    base = torch.randn(4-2)\n",
    "    image = torch.tensor([])\n",
    "    for vec in grid:\n",
    "        image = torch.cat([image, torch.from_numpy(from_latent(net, np.hstack([vec, base]) ) ) ] )\n",
    "    return image.view(64,1,28,28)\n",
    "\n",
    "def sample_from_latent(net, save = True, location = 'grid.png'):\n",
    "    grid = list(product(np.linspace(-1,1,8), np.linspace(-1,1,8) ) )\n",
    "    results = get_sampling_grid(net, grid)\n",
    "    if save:\n",
    "        save_image(results, location)\n",
    "    return results\n",
    "\n",
    "from torchvision.utils import make_grid\n",
    "def show_image_grid(results):\n",
    "    img = make_grid(results, nrow = 8)\n",
    "    _, ax = plt.subplots(ncols=1, nrows=1, figsize=(19,19))\n",
    "    ax.imshow(img.permute(1,2,0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 268,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1368x1368 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sampled_images = sample_from_latent(learn.model, save = False)\n",
    "\n",
    "show_image_grid(sampled_images)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}