{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "**Important: This notebook will only work with fastai-0.7.x. Do not try to run any fastai-1.x code from this path in the repository because it will load fastai-0.7.x**" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "%reload_ext autoreload\n", "%autoreload 2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## WGAN" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from fastai.conv_learner import *\n", "from fastai.dataset import *\n", "import gzip\n", "torch.cuda.set_device(3)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Download the LSUN scene classification dataset bedroom category, unzip it, and convert it to jpg files (the scripts folder is here in the `dl2` folder):\n", "\n", "```\n", "curl 'http://lsun.cs.princeton.edu/htbin/download.cgi?tag=latest&category=bedroom&set=train' -o bedroom.zip\n", "unzip bedroom.zip\n", "pip install lmdb\n", "python lsun-data.py {PATH}/bedroom_train_lmdb --out_dir {PATH}/bedroom\n", "```\n", "\n", "This isn't tested on Windows - if it doesn't work, you could use a Linux box to convert the files, then copy them over. Alternatively, you can download [this 20% sample](https://www.kaggle.com/jhoward/lsun_bedroom) from Kaggle datasets." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "PATH = Path('data/lsun/')\n", "IMG_PATH = PATH/'bedroom'\n", "CSV_PATH = PATH/'files.csv'\n", "TMP_PATH = PATH/'tmp'\n", "TMP_PATH.mkdir(exist_ok=True)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "files = PATH.glob('bedroom/**/*.jpg')\n", "\n", "with CSV_PATH.open('w') as fo:\n", " for f in files: fo.write(f'{f.relative_to(IMG_PATH)},0\\n')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Optional - sampling a subset of files\n", "CSV_PATH = PATH/'files_sample.csv'" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "files = PATH.glob('bedroom/**/*.jpg')\n", "\n", "with CSV_PATH.open('w') as fo:\n", " for f in files:\n", " if random.random()<0.1: fo.write(f'{f.relative_to(IMG_PATH)},0\\n')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "class ConvBlock(nn.Module):\n", " def __init__(self, ni, no, ks, stride, bn=True, pad=None):\n", " super().__init__()\n", " if pad is None: pad = ks//2//stride\n", " self.conv = nn.Conv2d(ni, no, ks, stride, padding=pad, bias=False)\n", " self.bn = nn.BatchNorm2d(no) if bn else None\n", " self.relu = nn.LeakyReLU(0.2, inplace=True)\n", " \n", " def forward(self, x):\n", " x = self.relu(self.conv(x))\n", " return self.bn(x) if self.bn else x" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "class DCGAN_D(nn.Module):\n", " def __init__(self, isize, nc, ndf, n_extra_layers=0):\n", " super().__init__()\n", " assert isize % 16 == 0, \"isize has to be a multiple of 16\"\n", "\n", " self.initial = ConvBlock(nc, ndf, 4, 2, bn=False)\n", " csize,cndf = isize/2,ndf\n", " self.extra = nn.Sequential(*[ConvBlock(cndf, cndf, 3, 1)\n", " for t in range(n_extra_layers)])\n", "\n", " pyr_layers = []\n", " while csize > 4:\n", " pyr_layers.append(ConvBlock(cndf, cndf*2, 4, 2))\n", " cndf *= 2; csize /= 2\n", " self.pyramid = nn.Sequential(*pyr_layers)\n", " \n", " self.final = nn.Conv2d(cndf, 1, 4, padding=0, bias=False)\n", "\n", " def forward(self, input):\n", " x = self.initial(input)\n", " x = self.extra(x)\n", " x = self.pyramid(x)\n", " return self.final(x).mean(0).view(1)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "class DeconvBlock(nn.Module):\n", " def __init__(self, ni, no, ks, stride, pad, bn=True):\n", " super().__init__()\n", " self.conv = nn.ConvTranspose2d(ni, no, ks, stride, padding=pad, bias=False)\n", " self.bn = nn.BatchNorm2d(no)\n", " self.relu = nn.ReLU(inplace=True)\n", " \n", " def forward(self, x):\n", " x = self.relu(self.conv(x))\n", " return self.bn(x) if self.bn else x" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "class DCGAN_G(nn.Module):\n", " def __init__(self, isize, nz, nc, ngf, n_extra_layers=0):\n", " super().__init__()\n", " assert isize % 16 == 0, \"isize has to be a multiple of 16\"\n", "\n", " cngf, tisize = ngf//2, 4\n", " while tisize!=isize: cngf*=2; tisize*=2\n", " layers = [DeconvBlock(nz, cngf, 4, 1, 0)]\n", "\n", " csize, cndf = 4, cngf\n", " while csize < isize//2:\n", " layers.append(DeconvBlock(cngf, cngf//2, 4, 2, 1))\n", " cngf //= 2; csize *= 2\n", "\n", " layers += [DeconvBlock(cngf, cngf, 3, 1, 1) for t in range(n_extra_layers)]\n", " layers.append(nn.ConvTranspose2d(cngf, nc, 4, 2, 1, bias=False))\n", " self.features = nn.Sequential(*layers)\n", "\n", " def forward(self, input): return F.tanh(self.features(input))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "bs,sz,nz = 64,64,100" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "tfms = tfms_from_stats(inception_stats, sz)\n", "md = ImageClassifierData.from_csv(PATH, 'bedroom', CSV_PATH, tfms=tfms, bs=128,\n", " skip_header=False, continuous=True)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "f462f6041a1849309f7f8b8a8b60818b", "version_major": 2, "version_minor": 0 }, "text/plain": [ "A Jupyter Widget" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "md = md.resize(128)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "x,_ = next(iter(md.val_dl))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.imshow(md.trn_ds.denorm(x)[0]);" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "netG = DCGAN_G(sz, nz, 3, 64, 1).cuda()\n", "netD = DCGAN_D(sz, 3, 64, 1).cuda()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "def create_noise(b): return V(torch.zeros(b, nz, 1, 1).normal_(0, 1))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "preds = netG(create_noise(4))\n", "pred_ims = md.trn_ds.denorm(preds)\n", "\n", "fig, axes = plt.subplots(2, 2, figsize=(6, 6))\n", "for i,ax in enumerate(axes.flat): ax.imshow(pred_ims[i])" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "def gallery(x, nc=3):\n", " n,h,w,c = x.shape\n", " nr = n//nc\n", " assert n == nr*nc\n", " return (x.reshape(nr, nc, h, w, c)\n", " .swapaxes(1,2)\n", " .reshape(h*nr, w*nc, c))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "optimizerD = optim.RMSprop(netD.parameters(), lr = 1e-4)\n", "optimizerG = optim.RMSprop(netG.parameters(), lr = 1e-4)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "def train(niter, first=True):\n", " gen_iterations = 0\n", " for epoch in trange(niter):\n", " netD.train(); netG.train()\n", " data_iter = iter(md.trn_dl)\n", " i,n = 0,len(md.trn_dl)\n", " with tqdm(total=n) as pbar:\n", " while i < n:\n", " set_trainable(netD, True)\n", " set_trainable(netG, False)\n", " d_iters = 100 if (first and (gen_iterations < 25) or (gen_iterations % 500 == 0)) else 5\n", " j = 0\n", " while (j < d_iters) and (i < n):\n", " j += 1; i += 1\n", " for p in netD.parameters(): p.data.clamp_(-0.01, 0.01)\n", " real = V(next(data_iter)[0])\n", " real_loss = netD(real)\n", " fake = netG(create_noise(real.size(0)))\n", " fake_loss = netD(V(fake.data))\n", " netD.zero_grad()\n", " lossD = real_loss-fake_loss\n", " lossD.backward()\n", " optimizerD.step()\n", " pbar.update()\n", "\n", " set_trainable(netD, False)\n", " set_trainable(netG, True)\n", " netG.zero_grad()\n", " lossG = netD(netG(create_noise(bs))).mean(0).view(1)\n", " lossG.backward()\n", " optimizerG.step()\n", " gen_iterations += 1\n", " \n", " print(f'Loss_D {to_np(lossD)}; Loss_G {to_np(lossG)}; '\n", " f'D_real {to_np(real_loss)}; Loss_D_fake {to_np(fake_loss)}')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "torch.backends.cudnn.benchmark=True" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 0%| | 0/1 [00:00" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "netD.eval(); netG.eval();\n", "fake = netG(fixed_noise).data.cpu()\n", "faked = np.clip(md.trn_ds.denorm(fake),0,1)\n", "\n", "plt.figure(figsize=(9,9))\n", "plt.imshow(gallery(faked, 8));" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "torch.save(netG.state_dict(), TMP_PATH/'netG_2.h5')\n", "torch.save(netD.state_dict(), TMP_PATH/'netD_2.h5')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" } }, "nbformat": 4, "nbformat_minor": 2 }