analysis/analyze_pend_lag_cavae.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#%%\n",
    "# Standard library imports\n",
    "from argparse import ArgumentParser\n",
    "import os, sys\n",
    "THIS_DIR = os.path.abspath('')\n",
    "PARENT_DIR = os.path.dirname(os.path.abspath(''))\n",
    "sys.path.append(PARENT_DIR)\n",
    "\n",
    "# Third party imports\n",
    "import torch\n",
    "from torch.nn import functional as F\n",
    "from torch.utils.data import DataLoader\n",
    "import pytorch_lightning as pl\n",
    "from pytorch_lightning import Trainer, seed_everything\n",
    "from pytorch_lightning.callbacks import ModelCheckpoint\n",
    "from torchdiffeq import odeint\n",
    "from torchvision import utils\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# local application imports\n",
    "from lag_caVAE.lag import Lag_Net\n",
    "from lag_caVAE.nn_models import MLP_Encoder, MLP, MLP_Decoder, PSD\n",
    "from hyperspherical_vae.distributions import VonMisesFisher\n",
    "from hyperspherical_vae.distributions import HypersphericalUniform\n",
    "from utils import arrange_data, from_pickle, my_collate, ImageDataset\n",
    "from examples.pend_lag_cavae_trainer import Model\n",
    "\n",
    "seed_everything(0)\n",
    "%matplotlib inline\n",
    "DPI = 600"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "checkpoint_path = os.path.join(PARENT_DIR, \n",
    "                               'checkpoints', \n",
    "                               'pend-lag-cavae-T_p=4-epoch=701.ckpt')\n",
    "model = Model.load_from_checkpoint(checkpoint_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Prepare data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_path=os.path.join(PARENT_DIR, 'datasets', 'pendulum-gym-image-dataset-test.pkl')\n",
    "test_dataset = ImageDataset(data_path, 19, ctrl=False)\n",
    "\n",
    "test_dataloader = DataLoader(test_dataset, batch_size=256, shuffle=False, collate_fn=my_collate)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_batch = next(iter(test_dataloader))\n",
    "X, u = test_batch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/desmond/.pyenv/versions/embed/lib/python3.7/site-packages/torch/nn/functional.py:3447: UserWarning: Default grid_sample and affine_grid behavior has changed to align_corners=False since 1.3.0. Please specify align_corners=True if the old behavior is desired. See the documentation of grid_sample for details.\n",
      "  warnings.warn(\"Default grid_sample and affine_grid behavior has changed \"\n",
      "/home/desmond/.pyenv/versions/embed/lib/python3.7/site-packages/torch/nn/functional.py:3384: UserWarning: Default grid_sample and affine_grid behavior has changed to align_corners=False since 1.3.0. Please specify align_corners=True if the old behavior is desired. See the documentation of grid_sample for details.\n",
      "  warnings.warn(\"Default grid_sample and affine_grid behavior has changed \"\n"
     ]
    }
   ],
   "source": [
    "model.t_eval = torch.from_numpy(test_dataset.t_eval)\n",
    "model.hparams.solver = 'rk4'\n",
    "model(X, u)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f25bd935450>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# data trajectory\n",
    "b_ind = 0\n",
    "grid = utils.make_grid(X[:, b_ind].view(-1, 1, 32, 32))\n",
    "plt.imshow(grid.permute(1,2,0).detach().cpu().numpy())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f25bd935810>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# prediction trajectory\n",
    "grid = utils.make_grid(model.Xrec[:, b_ind].view(-1, 1, 32, 32))\n",
    "plt.imshow(grid.permute(1,2,0).detach().cpu().numpy())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot learned potential energy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "q = np.linspace(0, 2*np.pi, 41)\n",
    "cos_q = np.cos(q[:-1])\n",
    "sin_q = np.sin(q[:-1])\n",
    "cos_q_sin_q = np.stack((cos_q, sin_q), axis=1)\n",
    "cos_q_sin_q = torch.tensor(cos_q_sin_q, dtype=torch.float32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, '$V(\\\\phi)$')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 3600x1800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "V_q = model.ode.V_net(cos_q_sin_q).detach().cpu().numpy()\n",
    "fig = plt.figure(figsize=[6, 3], dpi=DPI)\n",
    "markers_on = [0, 8, 16, 24, 32]\n",
    "plt.plot(q[:-1], V_q, marker = 'o', markevery=markers_on, markerfacecolor=(0,0,0,1), markeredgecolor=(0,0,0,1))\n",
    "plt.xlabel(r\"$\\phi$\", fontsize=14)\n",
    "plt.ylabel(r\"$V(\\phi)$\", fontsize=14)\n",
    "# plt.tight_layout()\n",
    "# fig.savefig(os.path.join(PARENT_DIR, 'figures', 'pend_potential_energy'), bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot 5 reconstruction images corresponding to the black dots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/desmond/.pyenv/versions/embed/lib/python3.7/site-packages/torch/nn/functional.py:3447: UserWarning: Default grid_sample and affine_grid behavior has changed to align_corners=False since 1.3.0. Please specify align_corners=True if the old behavior is desired. See the documentation of grid_sample for details.\n",
      "  warnings.warn(\"Default grid_sample and affine_grid behavior has changed \"\n",
      "/home/desmond/.pyenv/versions/embed/lib/python3.7/site-packages/torch/nn/functional.py:3384: UserWarning: Default grid_sample and affine_grid behavior has changed to align_corners=False since 1.3.0. Please specify align_corners=True if the old behavior is desired. See the documentation of grid_sample for details.\n",
      "  warnings.warn(\"Default grid_sample and affine_grid behavior has changed \"\n",
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f25bc2838d0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ones = torch.ones_like(cos_q_sin_q[:, 0:1])\n",
    "content = model.obs_net(ones)\n",
    "\n",
    "theta = model.get_theta_inv(cos_q_sin_q[:, 0], cos_q_sin_q[:, 1], 0, 0, bs=cos_q_sin_q.shape[0])\n",
    "grid = F.affine_grid(theta, torch.Size((40, 1, 32, 32)))\n",
    "Xrec = F.grid_sample(content.view(40, 1, 32, 32), grid)\n",
    "\n",
    "fig = plt.figure()\n",
    "grid = utils.make_grid(Xrec.view(40, 1, 32, 32), nrow=10)\n",
    "plt.imshow(grid.permute(1,2,0).detach().cpu().numpy())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f25bc257ad0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# for i in [0, 8, 16, 24, 32]:\n",
    "#     fig = plt.figure()\n",
    "#     plt.imshow(Xrec[i][0].detach().cpu().numpy(), cmap='gray')\n",
    "#     plt.axis('off')\n",
    "#     fig.savefig(os.path.join(PARENT_DIR, 'figures', f'pend_recon_{i}.png'), bbox_inches='tight')\n",
    "grid = utils.make_grid(Xrec[0:40:8])\n",
    "plt.imshow(grid.permute(1,2,0).detach().cpu().numpy())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Control"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/desmond/.pyenv/versions/embed/lib/python3.7/site-packages/gym/logger.py:30: UserWarning: \u001b[33mWARN: Box bound precision lowered by casting to float32\u001b[0m\n",
      "  warnings.warn(colorize('%s: %s'%('WARN', msg % args), 'yellow'))\n"
     ]
    }
   ],
   "source": [
    "import gym, myenv\n",
    "import numpy as np\n",
    "from skimage import color\n",
    "from gym import wrappers\n",
    "env = gym.make('MyPendulum-v0')\n",
    "\n",
    "# prepare model instance\n",
    "model.hparams.solver = 'rk4'\n",
    "model.bs = 1\n",
    "model.d = 32\n",
    "\n",
    "# get a goal image\n",
    "q_star = 0.0\n",
    "env.reset()\n",
    "env.state = np.array([q_star, 0.0], dtype=np.float32)\n",
    "goal_frame = env.render(mode='rgb_array')\n",
    "goal_frame = color.rgb2gray(goal_frame)\n",
    "goal_frame = torch.tensor(goal_frame, dtype=torch.float32)\n",
    "env.close()\n",
    "\n",
    "# given a goal image, design controller\n",
    "# first encode the goal image to goal coordinates\n",
    "_, _, goal_q_n = model.encode(goal_frame.view(1, 32*32))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([[ 0.8009, -0.5989]], grad_fn=<DivBackward0>)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "goal_q_n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "q0 = 3.14\n",
    "\n",
    "env.reset()\n",
    "env.state = np.array([q0, 0.0], dtype=np.float32)\n",
    "frame = color.rgb2gray(env.render(mode='rgb_array'))\n",
    "frames = [frame]\n",
    "\n",
    "frame = torch.tensor(frame, dtype=torch.float32)\n",
    "\n",
    "for i in range(100):\n",
    "    _, _, q_n = model.encode(frame.view(1, 32*32))\n",
    "    \n",
    "    if i==0:\n",
    "        prev_q_n = q_n\n",
    "        \n",
    "    q_dot = model.angle_vel_est(prev_q_n, q_n, 0.05)\n",
    "\n",
    "    V_q = model.ode.V_net(q_n)\n",
    "    dV = torch.autograd.grad(V_q, q_n)[0]\n",
    "    dV_dcos_q, dV_dsin_q = dV.split([1, 1], dim=1)\n",
    "    dV_dq = - dV_dcos_q * q_n[:, 1] + dV_dsin_q * q_n[:, 0]\n",
    "    g_q = model.ode.g_net(q_n)\n",
    "\n",
    "#     energy_shaping = torch.zeros(2, 1, dtype=torch.float32)\n",
    "#     energy_shaping[0][0] = dV_dr[0][0] - 3* (r_cos_phi_sin_phi[0][0] - 0.0)\n",
    "#     energy_shaping[1][0] = 2 * dV_dphi[0][0]\n",
    "\n",
    "    energy_shaping = dV_dq - 6 * (q_n[0, 1] * goal_q_n[0, 0] - q_n[0, 0] * goal_q_n[0, 1])\n",
    "    damping_injection = - 1 * q_dot.T\n",
    "\n",
    "    u = 1/g_q * (energy_shaping + damping_injection)\n",
    "\n",
    "    u = u.detach().cpu().numpy()\n",
    "    env.step(u)\n",
    "\n",
    "    frame = color.rgb2gray(env.render(mode='rgb_array'))\n",
    "    frames.append(frame)\n",
    "    frame = torch.tensor(frame, dtype=torch.float32)\n",
    "\n",
    "    prev_q_n = q_n\n",
    "\n",
    "env.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 9600x2400 with 13 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(16, 4), dpi=DPI)\n",
    "for i in range(13):\n",
    "    plt.subplot(1, 13, i+1)\n",
    "    plt.imshow(frames[i*8], cmap='gray')\n",
    "    plt.axis('off')\n",
    "    \n",
    "# fig.savefig(os.path.join(PARENT_DIR, 'figures', 'pend-ctrl.png'), bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import imageio\n",
    "# imageio.mimsave(os.path.join(PARENT_DIR, 'figures', 'pend-ctrl.gif'), frames, duration=0.05)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "control animation ![control sequence](../figures/pend-ctrl.gif)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"T_pred\":                         4\n",
       "\"accumulate_grad_batches\":        1\n",
       "\"amp_level\":                      O2\n",
       "\"auto_lr_find\":                   False\n",
       "\"auto_scale_batch_size\":          False\n",
       "\"auto_select_gpus\":               False\n",
       "\"batch_size\":                     512\n",
       "\"benchmark\":                      False\n",
       "\"check_val_every_n_epoch\":        1\n",
       "\"checkpoint_callback\":            True\n",
       "\"default_root_dir\":               None\n",
       "\"deterministic\":                  False\n",
       "\"distributed_backend\":            None\n",
       "\"early_stop_callback\":            False\n",
       "\"fast_dev_run\":                   False\n",
       "\"gradient_clip_val\":              0\n",
       "\"learning_rate\":                  0.001\n",
       "\"limit_test_batches\":             1.0\n",
       "\"limit_train_batches\":            1.0\n",
       "\"limit_val_batches\":              1.0\n",
       "\"log_gpu_memory\":                 None\n",
       "\"log_save_interval\":              100\n",
       "\"logger\":                         True\n",
       "\"max_epochs\":                     1000\n",
       "\"max_steps\":                      None\n",
       "\"min_epochs\":                     1\n",
       "\"min_steps\":                      None\n",
       "\"name\":                           pend-lag-cavae\n",
       "\"num_nodes\":                      1\n",
       "\"num_processes\":                  1\n",
       "\"num_sanity_val_steps\":           2\n",
       "\"overfit_batches\":                0.0\n",
       "\"overfit_pct\":                    None\n",
       "\"precision\":                      32\n",
       "\"prepare_data_per_node\":          True\n",
       "\"print_nan_grads\":                False\n",
       "\"process_position\":               0\n",
       "\"profiler\":                       None\n",
       "\"progress_bar_refresh_rate\":      1\n",
       "\"reload_dataloaders_every_epoch\": False\n",
       "\"replace_sampler_ddp\":            True\n",
       "\"resume_from_checkpoint\":         None\n",
       "\"row_log_interval\":               50\n",
       "\"solver\":                         rk4\n",
       "\"terminate_on_nan\":               False\n",
       "\"test_percent_check\":             None\n",
       "\"track_grad_norm\":                -1\n",
       "\"train_percent_check\":            None\n",
       "\"truncated_bptt_steps\":           None\n",
       "\"val_check_interval\":             1.0\n",
       "\"val_percent_check\":              None\n",
       "\"weights_save_path\":              None\n",
       "\"weights_summary\":                top"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.hparams"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.7.4 64-bit ('embed': venv)",
   "language": "python",
   "name": "python37464bitembedvenv00bda69ab17746c28ffa9a3e65936c26"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}