05_train_dual_lstm.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from fastai.vision.all import *\n",
    "from moving_mnist.models.phy_original import *\n",
    "from moving_mnist.models.seq2seq import TeacherForcing\n",
    "from moving_mnist.models.conv_rnn import StackUnstack, StackLoss, MultiImageDice\n",
    "from moving_mnist.data import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Quadro RTX 8000\n"
     ]
    }
   ],
   "source": [
    "if torch.cuda.is_available():\n",
    "    torch.cuda.set_device(0)\n",
    "    print(torch.cuda.get_device_name())\n",
    "    device = 0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Train PhyDNet:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We wil predict:\n",
    "- `n_in`: 5 images\n",
    "- `n_out`: 5 images  \n",
    "- `n_obj`: up to 3 objects"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Path('/home/tcapelle/SteadySun/moving_mnist')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Path.cwd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "DATA_PATH = Path.cwd()/'data'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = MovingMNIST(DATA_PATH, n_in=5, n_out=5, n_obj=[1,2], th=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_tl = TfmdLists(range(25000), ImageTupleTransform(ds))\n",
    "valid_tl = TfmdLists(range(100), ImageTupleTransform(ds))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# i=0\n",
    "# fat_tensor = torch.stack([torch.cat(train_tl[i][0], 0) for i in range(100)])\n",
    "\n",
    "# m,s = fat_tensor.mean(), fat_tensor.std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "dls = DataLoaders.from_dsets(train_tl, valid_tl, bs=64,#).cuda()\n",
    "                             after_batch=[Normalize.from_stats(*mnist_stats)]).cuda()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "mse_loss = StackLoss(MSELossFlat(axis=1))\n",
    "metrics = []"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Left: Input, Right: Target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x777.6 with 18 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dls.show_batch()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "b = dls.one_batch()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{tuple: [{moving_mnist.data.ImageSeq: [fastai.torch_core.TensorImageBW,\n",
       "    fastai.torch_core.TensorImageBW,\n",
       "    fastai.torch_core.TensorImageBW,\n",
       "    fastai.torch_core.TensorImageBW,\n",
       "    fastai.torch_core.TensorImageBW]},\n",
       "  {moving_mnist.data.ImageSeq: [fastai.torch_core.TensorImageBW,\n",
       "    fastai.torch_core.TensorImageBW,\n",
       "    fastai.torch_core.TensorImageBW,\n",
       "    fastai.torch_core.TensorImageBW,\n",
       "    fastai.torch_core.TensorImageBW]}]}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "explode_types(b)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## PhyDNet with dual LSTM instead of PhyCell\n",
    "> We replace the inner PhyCell by just ConvLSTM layers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "layer  0 input dim  64  hidden dim  128\n",
      "layer  1 input dim  128  hidden dim  128\n",
      "layer  2 input dim  128  hidden dim  64\n",
      "layer  0 input dim  64  hidden dim  128\n",
      "layer  1 input dim  128  hidden dim  128\n",
      "layer  2 input dim  128  hidden dim  64\n"
     ]
    }
   ],
   "source": [
    "# phycell =  PhyCell(input_shape=(16,16), input_dim=64, F_hidden_dims=[49], n_layers=1, kernel_size=(7,7)) \n",
    "convlstm = ConvLSTM(input_shape=(16,16), input_dim=64, hidden_dims=[128,128,64], n_layers=3, kernel_size=(3,3))   \n",
    "convlstm2 = ConvLSTM(input_shape=(16,16), input_dim=64, hidden_dims=[128,128,64], n_layers=3, kernel_size=(3,3))   \n",
    "encoder =  EncoderRNN(convlstm2, convlstm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = StackUnstack(PhyDNet(encoder, sigmoid=False, moment=True), dim=1).cuda()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A handy callback to include the loss computed inside the model to the target loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "#export\n",
    "class PHyCallback(Callback):\n",
    "    def after_pred(self):\n",
    "        self.learn.pred, self.loss_phy = self.pred\n",
    "    def after_loss(self):\n",
    "        self.learn.loss += self.loss_phy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "learn = Learner(dls, model, loss_func=mse_loss, metrics=metrics, \n",
    "                cbs=[TeacherForcing(10), PHyCallback()], opt_func=ranger)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "SuggestedLRs(lr_min=0.05248074531555176, lr_steep=0.0012022644514217973)"
      ]
     },
     "execution_count": 17,
     "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": [
    "learn.lr_find()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.751772</td>\n",
       "      <td>0.828895</td>\n",
       "      <td>02:09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0.726362</td>\n",
       "      <td>0.774711</td>\n",
       "      <td>02:10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>0.711228</td>\n",
       "      <td>0.754423</td>\n",
       "      <td>02:10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0.710111</td>\n",
       "      <td>0.669803</td>\n",
       "      <td>02:10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0.676292</td>\n",
       "      <td>0.706133</td>\n",
       "      <td>02:10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>0.666376</td>\n",
       "      <td>0.661772</td>\n",
       "      <td>02:10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>0.653669</td>\n",
       "      <td>0.644562</td>\n",
       "      <td>02:10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>0.648538</td>\n",
       "      <td>0.601583</td>\n",
       "      <td>02:10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>0.652141</td>\n",
       "      <td>0.655571</td>\n",
       "      <td>02:10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>0.645463</td>\n",
       "      <td>0.591926</td>\n",
       "      <td>02:10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>0.634670</td>\n",
       "      <td>0.630315</td>\n",
       "      <td>02:11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>0.629667</td>\n",
       "      <td>0.631815</td>\n",
       "      <td>02:10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>0.634186</td>\n",
       "      <td>0.610886</td>\n",
       "      <td>02:10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>0.627405</td>\n",
       "      <td>0.634087</td>\n",
       "      <td>02:11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>0.622789</td>\n",
       "      <td>0.609048</td>\n",
       "      <td>02:11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>0.624476</td>\n",
       "      <td>0.644521</td>\n",
       "      <td>02:11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>0.614848</td>\n",
       "      <td>0.598800</td>\n",
       "      <td>02:11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>0.609313</td>\n",
       "      <td>0.557119</td>\n",
       "      <td>02:11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>0.600565</td>\n",
       "      <td>0.624972</td>\n",
       "      <td>02:11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>0.600336</td>\n",
       "      <td>0.583689</td>\n",
       "      <td>02:11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>0.603146</td>\n",
       "      <td>0.586298</td>\n",
       "      <td>02:11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>0.588113</td>\n",
       "      <td>0.586281</td>\n",
       "      <td>02:11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>0.577486</td>\n",
       "      <td>0.575047</td>\n",
       "      <td>02:11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23</td>\n",
       "      <td>0.580078</td>\n",
       "      <td>0.552759</td>\n",
       "      <td>02:11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>0.575861</td>\n",
       "      <td>0.630428</td>\n",
       "      <td>02:11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "learn.fit_flat_cos(25, 3e-3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p,t = learn.get_preds(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5, torch.Size([100, 1, 64, 64]))"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(p), p[0].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "def show_res(t, idx, argmax=False):\n",
    "    if argmax:\n",
    "        im_seq = ImageSeq.create([t[i][idx].argmax(0).unsqueeze(0) for i in range(5)], TensorMask)\n",
    "    else:\n",
    "        im_seq = ImageSeq.create([t[i][idx] for i in range(5)])\n",
    "    im_seq.show(figsize=(8,4));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "k = random.randint(0,99)\n",
    "show_res(t,k)\n",
    "show_res(p,k)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Path('models/phydnet.pth')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "learn.save('phydnet')"
   ]
  },
  {
   "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": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}