MCVD_demo_SMMNIST.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "7636673f",
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "import sys, os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "4c28d3ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "import glob, os\n",
    "import mediapy as media\n",
    "import torch\n",
    "from torch.utils.data import DataLoader\n",
    "\n",
    "from load_model_from_ckpt import load_model, get_sampler, init_samples\n",
    "from datasets import get_dataset, data_transform, inverse_data_transform\n",
    "from runners.ncsn_runner import conditioning_fn\n",
    "\n",
    "from os.path import expanduser\n",
    "home = expanduser(\"~\")\n",
    "\n",
    "device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d956de9-6fba-4824-bfdb-3d36b4178836",
   "metadata": {},
   "source": [
    "# Set directories to download model, data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "08f0476c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# SET THESE!!!\n",
    "GDRIVE_URL = \"https://drive.google.com/drive/folders/1bM6wqU_kymoljz5uYQRCYNup_8adBfLH\" # smmnist_big_5c5_unetm_b2\n",
    "EXP_PATH = os.path.join(home, \"scratch/MCVD_SMMNIST_pred\")\n",
    "DATA_PATH = os.path.join(home, \"scratch/Datasets/MNIST\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eefab24a",
   "metadata": {},
   "source": [
    "# Download experiment (model checkpoint, config, etc.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "eef31cee",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Retrieving folder list\n",
      "Retrieving folder 1CzwozDKbsOH_V2099N9-HBeeMO4441iT logs\n",
      "Processing file 14Di0OplaG_F-Ogmmv8w_K0NqYP5Bag9r args.yml\n",
      "Processing file 1uTfMtTfTT5WMAdDR1x2WNrOQnldk__yA checkpoint_140000.pt\n",
      "Processing file 1xOY4-oh7jSCSKqtDktvtTCt3CasNzT64 config.yml\n",
      "Processing file 1zuqnoOOxfvBzjpgaFR77j8OGUUs808oj epochs.png\n",
      "Processing file 1PMXh9CluffmccQO_llGmRMf6DRhXU9Db fvd_log.png\n",
      "Processing file 1BWgT0O20aaa-TtsKezIB1UxMzNkL0HOH fvd.png\n",
      "Processing file 1DWk2o8zyj4h9lfaZcLbUxln4ZiV7z04v grad_log.png\n",
      "Processing file 10iH96rRLPlHPRaZHuS7SNdYg0KjOlah6 grad.png\n",
      "Processing file 1Eebka2ybBXoYXBGOdom1059LEl2wyC-f loss_log.png\n",
      "Processing file 1SmtLNaMHHUV4L6SXGV_QacQ7augGQBC3 loss.png\n",
      "Processing file 1hQo6pWh3pIHteyVx90_YzsDg9Z-BKSHm lpips_log.png\n",
      "Processing file 1I2sme46c9twlixOYkThZxcIh8ptpzBZz lpips.png\n",
      "Processing file 1B_LvuvnNmmNKqacX2NLx4_-_0o6dniuZ lr.png\n",
      "Processing file 1v6i8iwed7QDw84LKpsl9jpoAQZ-UZ410 meters.pkl\n",
      "Processing file 1cmaGJZ3El7xe91JvJkt4QpA00HYwnATA mse_log.png\n",
      "Processing file 1Pgl_r02PK_FF16dmWIe9yTy-86Y8qr3K mse.png\n",
      "Processing file 1WzFIEP5HjdtWzeiqSdYZgXDmDlOTqY-q psnr_log.png\n",
      "Processing file 1FTRbdRjNWjgzhPgo830ryRoQbtHK4MIB psnr.png\n",
      "Processing file 1zhhX8DbMWO2I_SQgHSY1owV6YGKYh63F ssim_log.png\n",
      "Processing file 1cFGvi1IlVp6LuhBs8tWWLxiggAmBGIT8 ssim.png\n",
      "Processing file 1JSzpI1ulL7rr2ViPoaT9vnIvOliXTz_J stdout.txt\n",
      "Processing file 1Wb9uHqMN3ZsayV5K9XvKtMlKwYkYKfg6 time_elapsed.png\n",
      "Processing file 11LJ_8ikBK891lGoXylixieqbOeDiLqlJ time_train.png\n",
      "Retrieving folder list completed\n",
      "Building directory structure\n",
      "Building directory structure completed\n",
      "Downloading...\n",
      "From: https://drive.google.com/uc?id=14Di0OplaG_F-Ogmmv8w_K0NqYP5Bag9r\n",
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      "Download completed\n"
     ]
    }
   ],
   "source": [
    "GDRIVE_URL = GDRIVE_URL.removesuffix(\"?usp=sharing\")\n",
    "!gdown --fuzzy {GDRIVE_URL} -O {EXP_PATH}/ --folder"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7497708",
   "metadata": {},
   "source": [
    "# Load model checkpoint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "bed12d90",
   "metadata": {},
   "outputs": [],
   "source": [
    "ckpt_path = glob.glob(os.path.join(EXP_PATH, \"checkpoint_*.pt\"))[0]\n",
    "scorenet, config = load_model(ckpt_path, device)\n",
    "sampler = get_sampler(config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "dc8c5945",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cuda\n",
      "/home/mila/v/voletivi/scratch/MCVD_SMMNIST_pred/checkpoint_140000.pt\n",
      "Namespace(data=Namespace(channels=1, dataset='StochasticMovingMNIST', gaussian_dequantization=False, image_size=64, logit_transform=False, num_digits=2, num_frames=5, num_frames_cond=5, num_workers=0, prob_mask_cond=0.0, random_flip=True, rescaled=True, step_length=0.1, uniform_dequantization=False), fast_fid=Namespace(batch_size=1000, begin_ckpt=5000, end_ckpt=300000, ensemble=False, freq=5000, n_steps_each=0, num_samples=1000, pr_nn_k=3, step_lr=0.0, verbose=False), model=Namespace(arch='unetmore', attn_resolutions=[8, 16, 32], ch_mult=[1, 2, 3, 4], cond_emb=False, conditional=True, depth='deep', dropout=0.1, ema=True, ema_rate=0.999, gamma=False, gff=False, n_head_channels=64, ngf=64, noise_in_cond=False, nonlinearity='swish', normalization='InstanceNorm++', num_classes=1000, num_res_blocks=2, output_all_frames=False, sigma_begin=0.02, sigma_dist='linear', sigma_end=0.0001, spade=True, spec_norm=False, time_conditional=True, type='v1', version='DDPM'), optim=Namespace(amsgrad=False, beta1=0.9, eps=1e-08, grad_clip=1.0, lr=0.0002, optimizer='Adam', warmup=1000, weight_decay=0.0), sampling=Namespace(batch_size=100, ckpt_id=0, clip_before=True, consistent=True, data_init=False, denoise=True, fid=False, final_only=True, fvd=True, init_prev_t=-1.0, inpainting=False, interpolation=False, max_data_iter=100000, n_interpolations=15, n_steps_each=0, num_frames_pred=20, num_samples4fid=10000, num_samples4fvd=10000, one_frame_at_a_time=False, preds_per_test=1, ssim=True, step_lr=0.0, subsample=100, train=False), test=Namespace(batch_size=100, begin_ckpt=5000, end_ckpt=300000), training=Namespace(L1=False, batch_size=64, log_all_sigmas=False, log_freq=50, n_epochs=1000000, n_iters=3000001, sample_freq=50000, snapshot_freq=50000, snapshot_sampling=True, val_freq=100), device=device(type='cuda'))\n"
     ]
    }
   ],
   "source": [
    "print(device)\n",
    "print(ckpt_path)\n",
    "print(config)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "717769fc",
   "metadata": {},
   "source": [
    "# Load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ed043f4b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dataset length: 60000\n",
      "Dataset length: 256\n"
     ]
    }
   ],
   "source": [
    "dataset, test_dataset = get_dataset(DATA_PATH, config, video_frames_pred=config.data.num_frames)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "277c205a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([64, 10, 1, 64, 64])\n"
     ]
    }
   ],
   "source": [
    "# dataloader = DataLoader(dataset, batch_size=config.training.batch_size, shuffle=True,\n",
    "#                         num_workers=config.data.num_workers)\n",
    "# train_iter = iter(dataloader)\n",
    "# x, y = next(train_iter)\n",
    "\n",
    "test_loader = DataLoader(test_dataset, batch_size=config.training.batch_size, shuffle=False,\n",
    "                         num_workers=config.data.num_workers, drop_last=True)\n",
    "test_iter = iter(test_loader)\n",
    "test_x, test_y = next(test_iter)\n",
    "print(test_x.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9cebee4b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([64, 5, 64, 64]) torch.Size([64, 5, 64, 64])\n"
     ]
    }
   ],
   "source": [
    "test_x = data_transform(config, test_x)\n",
    "real, cond, cond_mask = conditioning_fn(config, test_x, num_frames_pred=config.data.num_frames,\n",
    "                                        prob_mask_cond=getattr(config.data, 'prob_mask_cond', 0.0),\n",
    "                                        prob_mask_future=getattr(config.data, 'prob_mask_future', 0.0))\n",
    "print(real.shape, cond.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a4b6e45b",
   "metadata": {},
   "outputs": [
    {
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object-fit:cover;\" src=\"data:image/png;base64,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\"/></td><td style=\"padding:1px;\"><img width=\"64\" height=\"64\" style=\"image-rendering:pixelated; object-fit:cover;\" src=\"data:image/png;base64,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\"/></td></tr></table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "i = 1\n",
    "# media.show_images(torch.cat([cond[i].permute(0, 2, 3, 1), real[i].permute(0, 2, 3, 1)]))\n",
    "media.show_images(torch.cat([cond[i], real[i]]))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d37ea28",
   "metadata": {},
   "source": [
    "# Load initial samples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "55bde034",
   "metadata": {},
   "outputs": [],
   "source": [
    "init = init_samples(len(real), config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "9253a5ad",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([64, 5, 64, 64])\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"show_images\" style=\"border-spacing:0px;\"><tr><td style=\"padding:1px;\"><img width=\"64\" height=\"64\" style=\"image-rendering:pixelated; object-fit:cover;\" 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\"/></td><td style=\"padding:1px;\"><img width=\"64\" height=\"64\" style=\"image-rendering:pixelated; object-fit:cover;\" 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\"/></td><td style=\"padding:1px;\"><img width=\"64\" height=\"64\" style=\"image-rendering:pixelated; object-fit:cover;\" 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\"/></td><td style=\"padding:1px;\"><img width=\"64\" height=\"64\" style=\"image-rendering:pixelated; object-fit:cover;\" 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\"/></td><td style=\"padding:1px;\"><img width=\"64\" height=\"64\" style=\"image-rendering:pixelated; object-fit:cover;\" 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\"/></td></tr></table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(init.shape)\n",
    "media.show_images(init[i])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47b62c71",
   "metadata": {},
   "source": [
    "# Predict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "5d2a372b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DDPM: 1/100, grad_norm: 143.2518768310547, image_norm: 129.60122680664062, grad_mean_norm: 325.6442565917969\n",
      "DDPM: 10/100, grad_norm: 143.25779724121094, image_norm: 130.69338989257812, grad_mean_norm: 320.6053466796875\n",
      "DDPM: 20/100, grad_norm: 143.30130004882812, image_norm: 131.94703674316406, grad_mean_norm: 321.99261474609375\n",
      "DDPM: 30/100, grad_norm: 143.56088256835938, image_norm: 133.11929321289062, grad_mean_norm: 321.1786193847656\n",
      "DDPM: 40/100, grad_norm: 144.76840209960938, image_norm: 134.29885864257812, grad_mean_norm: 322.8674621582031\n",
      "DDPM: 50/100, grad_norm: 148.45303344726562, image_norm: 135.35610961914062, grad_mean_norm: 322.8923034667969\n",
      "DDPM: 60/100, grad_norm: 157.97732543945312, image_norm: 136.23965454101562, grad_mean_norm: 325.763916015625\n",
      "DDPM: 70/100, grad_norm: 180.5244903564453, image_norm: 136.7104034423828, grad_mean_norm: 320.1344299316406\n",
      "DDPM: 80/100, grad_norm: 235.61495971679688, image_norm: 137.1285400390625, grad_mean_norm: 319.7248229980469\n",
      "DDPM: 90/100, grad_norm: 407.8251647949219, image_norm: 137.60614013671875, grad_mean_norm: 324.1687316894531\n",
      "DDPM: 100/100, grad_norm: 3216.2890625, image_norm: 138.50021362304688, grad_mean_norm: 302.0787048339844\n"
     ]
    }
   ],
   "source": [
    "pred = sampler(init, scorenet, cond=cond, cond_mask=cond_mask, subsample=100, verbose=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "881fc304",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([64, 5, 64, 64])\n"
     ]
    },
    {
     "data": {
      "text/html": [
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object-fit:cover;\" src=\"data:image/png;base64,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\"/></td></tr></table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(pred.shape)\n",
    "i = 1\n",
    "media.show_images(torch.cat([cond[i], real[i]]))\n",
    "media.show_images(torch.cat([cond[i], pred[i]]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "7937cd9f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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object-fit:cover;\" src=\"data:image/png;base64,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\"/></td></tr></table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "i = 4\n",
    "media.show_images(torch.cat([cond[i], real[i]]))\n",
    "media.show_images(torch.cat([cond[i], pred[i]]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f0f85ca1-3100-4d14-beeb-0b103ce4fcb7",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}