08-seq_classification.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# An example of many-to-one (sequence classification)\n",
    "\n",
    "Original experiment from [Hochreiter & Schmidhuber (1997)](www.bioinf.jku.at/publications/older/2604.pdf).\n",
    "\n",
    "The goal is to classify sequences.\n",
    "Elements and targets are represented locally (input vectors with only one non-zero bit).\n",
    "The sequence starts with an `B`, ends with a `E` (the “trigger symbol”), and otherwise consists of randomly chosen symbols from the set `{a, b, c, d}` except for two elements at positions `t1` and `t2` that are either `X` or `Y`.\n",
    "For the `DifficultyLevel.HARD` case, the sequence length is randomly chosen between `100` and `110`, `t1` is randomly chosen between `10` and `20`, and `t2` is randomly chosen between `50` and `60`.\n",
    "There are `4` sequence classes `Q`, `R`, `S`, and `U`, which depend on the temporal order of `X` and `Y`.\n",
    "\n",
    "The rules are:\n",
    "\n",
    "```\n",
    "X, X -> Q,\n",
    "X, Y -> R,\n",
    "Y, X -> S,\n",
    "Y, Y -> U.\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Dataset Exploration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from res.sequential_tasks import TemporalOrderExp6aSequence as QRSU"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The return type is a <class 'tuple'> with length 2.\n",
      "The first item in the tuple is the batch of sequences with shape (32, 9, 8).\n",
      "The first element in the batch of sequences is:\n",
      " [[0 0 0 0 0 0 0 0]\n",
      " [0 0 0 0 0 0 1 0]\n",
      " [0 0 0 1 0 0 0 0]\n",
      " [1 0 0 0 0 0 0 0]\n",
      " [0 0 0 0 1 0 0 0]\n",
      " [1 0 0 0 0 0 0 0]\n",
      " [0 0 0 0 1 0 0 0]\n",
      " [0 0 0 1 0 0 0 0]\n",
      " [0 0 0 0 0 0 0 1]]\n",
      "The second item in the tuple is the corresponding batch of class labels with shape (32, 4).\n",
      "The first element in the batch of class labels is:\n",
      " [1. 0. 0. 0.]\n"
     ]
    }
   ],
   "source": [
    "# Create a data generator\n",
    "example_generator = QRSU.get_predefined_generator(\n",
    "    difficulty_level=QRSU.DifficultyLevel.EASY,\n",
    "    batch_size=32,\n",
    ")\n",
    "\n",
    "example_batch = example_generator[1]\n",
    "print(f'The return type is a {type(example_batch)} with length {len(example_batch)}.')\n",
    "print(f'The first item in the tuple is the batch of sequences with shape {example_batch[0].shape}.')\n",
    "print(f'The first element in the batch of sequences is:\\n {example_batch[0][0, :, :]}')\n",
    "print(f'The second item in the tuple is the corresponding batch of class labels with shape {example_batch[1].shape}.')\n",
    "print(f'The first element in the batch of class labels is:\\n {example_batch[1][0, :]}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The sequence is: BbXcXcbE\n",
      "The class label is: Q\n"
     ]
    }
   ],
   "source": [
    "# Decoding the first sequence\n",
    "sequence_decoded = example_generator.decode_x(example_batch[0][0, :, :])\n",
    "print(f'The sequence is: {sequence_decoded}')\n",
    "\n",
    "# Decoding the class label of the first sequence\n",
    "class_label_decoded = example_generator.decode_y(example_batch[1][0])\n",
    "print(f'The class label is: {class_label_decoded}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Defining the Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import torch.nn as nn\n",
    "\n",
    "# Set the random seed for reproducible results\n",
    "torch.manual_seed(1)\n",
    "\n",
    "class SimpleRNN(nn.Module):\n",
    "    def __init__(self, input_size, hidden_size, output_size):\n",
    "        # This just calls the base class constructor\n",
    "        super().__init__()\n",
    "        # Neural network layers assigned as attributes of a Module subclass\n",
    "        # have their parameters registered for training automatically.\n",
    "        self.rnn = torch.nn.RNN(input_size, hidden_size, nonlinearity='relu', batch_first=True)\n",
    "        self.linear = torch.nn.Linear(hidden_size, output_size)\n",
    "\n",
    "    def forward(self, x):\n",
    "        # The RNN also returns its hidden state but we don't use it.\n",
    "        # While the RNN can also take a hidden state as input, the RNN\n",
    "        # gets passed a hidden state initialized with zeros by default.\n",
    "        h = self.rnn(x)[0]\n",
    "        x = self.linear(h)\n",
    "        return x\n",
    "\n",
    "class SimpleLSTM(nn.Module):\n",
    "    def __init__(self, input_size, hidden_size, output_size):\n",
    "        super().__init__()\n",
    "        self.lstm = torch.nn.LSTM(input_size, hidden_size, batch_first=True)\n",
    "        self.linear = torch.nn.Linear(hidden_size, output_size)\n",
    "\n",
    "    def forward(self, x):\n",
    "        h = self.lstm(x)[0]\n",
    "        x = self.linear(h)\n",
    "        return x\n",
    "    \n",
    "    def get_states_across_time(self, x):\n",
    "        h_c = None\n",
    "        h_list, c_list = list(), list()\n",
    "        with torch.no_grad():\n",
    "            for t in range(x.size(1)):\n",
    "                h_c = self.lstm(x[:, [t], :], h_c)[1]\n",
    "                h_list.append(h_c[0])\n",
    "                c_list.append(h_c[1])\n",
    "            h = torch.cat(h_list)\n",
    "            c = torch.cat(c_list)\n",
    "        return h, c"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Defining the Training Loop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def train(model, train_data_gen, criterion, optimizer, device):\n",
    "    # Set the model to training mode. This will turn on layers that would\n",
    "    # otherwise behave differently during evaluation, such as dropout.\n",
    "    model.train()\n",
    "\n",
    "    # Store the number of sequences that were classified correctly\n",
    "    num_correct = 0\n",
    "\n",
    "    # Iterate over every batch of sequences. Note that the length of a data generator\n",
    "    # is defined as the number of batches required to produce a total of roughly 1000\n",
    "    # sequences given a batch size.\n",
    "    for batch_idx in range(len(train_data_gen)):\n",
    "\n",
    "        # Request a batch of sequences and class labels, convert them into tensors\n",
    "        # of the correct type, and then send them to the appropriate device.\n",
    "        data, target = train_data_gen[batch_idx]\n",
    "        data, target = torch.from_numpy(data).float().to(device), torch.from_numpy(target).long().to(device)\n",
    "\n",
    "        # Perform the forward pass of the model\n",
    "        output = model(data)  # Step ①\n",
    "\n",
    "        # Pick only the output corresponding to last sequence element (input is pre padded)\n",
    "        output = output[:, -1, :]\n",
    "\n",
    "        # Compute the value of the loss for this batch. For loss functions like CrossEntropyLoss,\n",
    "        # the second argument is actually expected to be a tensor of class indices rather than\n",
    "        # one-hot encoded class labels. One approach is to take advantage of the one-hot encoding\n",
    "        # of the target and call argmax along its second dimension to create a tensor of shape\n",
    "        # (batch_size) containing the index of the class label that was hot for each sequence.\n",
    "        target = target.argmax(dim=1)\n",
    "\n",
    "        loss = criterion(output, target)  # Step ②\n",
    "\n",
    "        # Clear the gradient buffers of the optimized parameters.\n",
    "        # Otherwise, gradients from the previous batch would be accumulated.\n",
    "        optimizer.zero_grad()  # Step ③\n",
    "\n",
    "        loss.backward()  # Step ④\n",
    "\n",
    "        optimizer.step()  # Step ⑤\n",
    "\n",
    "        y_pred = output.argmax(dim=1)\n",
    "        num_correct += (y_pred == target).sum().item()\n",
    "\n",
    "    return num_correct, loss.item()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Defining the Testing Loop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def test(model, test_data_gen, criterion, device):\n",
    "    # Set the model to evaluation mode. This will turn off layers that would\n",
    "    # otherwise behave differently during training, such as dropout.\n",
    "    model.eval()\n",
    "\n",
    "    # Store the number of sequences that were classified correctly\n",
    "    num_correct = 0\n",
    "\n",
    "    # A context manager is used to disable gradient calculations during inference\n",
    "    # to reduce memory usage, as we typically don't need the gradients at this point.\n",
    "    with torch.no_grad():\n",
    "        for batch_idx in range(len(test_data_gen)):\n",
    "            data, target = test_data_gen[batch_idx]\n",
    "            data, target = torch.from_numpy(data).float().to(device), torch.from_numpy(target).long().to(device)\n",
    "\n",
    "            output = model(data)\n",
    "            # Pick only the output corresponding to last sequence element (input is pre padded)\n",
    "            output = output[:, -1, :]\n",
    "\n",
    "            target = target.argmax(dim=1)\n",
    "            loss = criterion(output, target)\n",
    "\n",
    "            y_pred = output.argmax(dim=1)\n",
    "            num_correct += (y_pred == target).sum().item()\n",
    "\n",
    "    return num_correct, loss.item()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Putting it All Together"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from res.plot_lib import set_default, plot_state, print_colourbar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "set_default()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def train_and_test(model, train_data_gen, test_data_gen, criterion, optimizer, max_epochs, verbose=True):\n",
    "    # Automatically determine the device that PyTorch should use for computation\n",
    "    device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')\n",
    "\n",
    "    # Move model to the device which will be used for train and test\n",
    "    model.to(device)\n",
    "\n",
    "    # Track the value of the loss function and model accuracy across epochs\n",
    "    history_train = {'loss': [], 'acc': []}\n",
    "    history_test = {'loss': [], 'acc': []}\n",
    "\n",
    "    for epoch in range(max_epochs):\n",
    "        # Run the training loop and calculate the accuracy.\n",
    "        # Remember that the length of a data generator is the number of batches,\n",
    "        # so we multiply it by the batch size to recover the total number of sequences.\n",
    "        num_correct, loss = train(model, train_data_gen, criterion, optimizer, device)\n",
    "        accuracy = float(num_correct) / (len(train_data_gen) * train_data_gen.batch_size) * 100\n",
    "        history_train['loss'].append(loss)\n",
    "        history_train['acc'].append(accuracy)\n",
    "\n",
    "        # Do the same for the testing loop\n",
    "        num_correct, loss = test(model, test_data_gen, criterion, device)\n",
    "        accuracy = float(num_correct) / (len(test_data_gen) * test_data_gen.batch_size) * 100\n",
    "        history_test['loss'].append(loss)\n",
    "        history_test['acc'].append(accuracy)\n",
    "\n",
    "        if verbose or epoch + 1 == max_epochs:\n",
    "            print(f'[Epoch {epoch + 1}/{max_epochs}]'\n",
    "                  f\" loss: {history_train['loss'][-1]:.4f}, acc: {history_train['acc'][-1]:2.2f}%\"\n",
    "                  f\" - test_loss: {history_test['loss'][-1]:.4f}, test_acc: {history_test['acc'][-1]:2.2f}%\")\n",
    "\n",
    "    # Generate diagnostic plots for the loss and accuracy\n",
    "    fig, axes = plt.subplots(ncols=2, figsize=(9, 4.5))\n",
    "    for ax, metric in zip(axes, ['loss', 'acc']):\n",
    "        ax.plot(history_train[metric])\n",
    "        ax.plot(history_test[metric])\n",
    "        ax.set_xlabel('epoch', fontsize=12)\n",
    "        ax.set_ylabel(metric, fontsize=12)\n",
    "        ax.legend(['Train', 'Test'], loc='best')\n",
    "    plt.show()\n",
    "\n",
    "    return model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Simple RNN: 10 Epochs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Epoch 1/10] loss: 1.4213, acc: 24.29% - test_loss: 1.3710, test_acc: 31.35%\n",
      "[Epoch 2/10] loss: 1.3603, acc: 30.75% - test_loss: 1.3846, test_acc: 37.50%\n",
      "[Epoch 3/10] loss: 1.3673, acc: 40.22% - test_loss: 1.3910, test_acc: 40.12%\n",
      "[Epoch 4/10] loss: 1.3636, acc: 39.82% - test_loss: 1.3435, test_acc: 43.85%\n",
      "[Epoch 5/10] loss: 1.2752, acc: 44.35% - test_loss: 1.3282, test_acc: 36.59%\n",
      "[Epoch 6/10] loss: 1.2631, acc: 40.22% - test_loss: 1.2412, test_acc: 41.03%\n",
      "[Epoch 7/10] loss: 1.2340, acc: 44.35% - test_loss: 1.2670, test_acc: 47.58%\n",
      "[Epoch 8/10] loss: 1.1193, acc: 50.40% - test_loss: 1.2446, test_acc: 48.69%\n",
      "[Epoch 9/10] loss: 1.2194, acc: 48.89% - test_loss: 1.1098, test_acc: 50.81%\n",
      "[Epoch 10/10] loss: 1.0805, acc: 48.69% - test_loss: 1.0649, test_acc: 52.72%\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x450 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Setup the training and test data generators\n",
    "difficulty     = QRSU.DifficultyLevel.EASY\n",
    "batch_size     = 32\n",
    "train_data_gen = QRSU.get_predefined_generator(difficulty, batch_size)\n",
    "test_data_gen  = QRSU.get_predefined_generator(difficulty, batch_size)\n",
    "\n",
    "# Setup the RNN and training settings\n",
    "input_size  = train_data_gen.n_symbols\n",
    "hidden_size = 4\n",
    "output_size = train_data_gen.n_classes\n",
    "model       = SimpleRNN(input_size, hidden_size, output_size)\n",
    "criterion   = torch.nn.CrossEntropyLoss()\n",
    "optimizer   = torch.optim.RMSprop(model.parameters(), lr=0.001)\n",
    "max_epochs  = 10\n",
    "\n",
    "# Train the model\n",
    "model = train_and_test(model, train_data_gen, test_data_gen, criterion, optimizer, max_epochs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([4, 8])\n",
      "torch.Size([4, 4])\n",
      "torch.Size([4])\n",
      "torch.Size([4])\n",
      "torch.Size([4, 4])\n",
      "torch.Size([4])\n"
     ]
    }
   ],
   "source": [
    "for parameter_group in list(model.parameters()):\n",
    "    print(parameter_group.size())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Simple LSTM: 10 Epochs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Epoch 1/10] loss: 1.3307, acc: 32.66% - test_loss: 1.4515, test_acc: 29.03%\n",
      "[Epoch 2/10] loss: 1.3932, acc: 28.02% - test_loss: 1.3997, test_acc: 26.01%\n",
      "[Epoch 3/10] loss: 1.3456, acc: 37.40% - test_loss: 1.3411, test_acc: 50.71%\n",
      "[Epoch 4/10] loss: 1.2591, acc: 49.19% - test_loss: 1.2757, test_acc: 53.93%\n",
      "[Epoch 5/10] loss: 1.1803, acc: 48.89% - test_loss: 1.1728, test_acc: 50.50%\n",
      "[Epoch 6/10] loss: 1.1296, acc: 58.77% - test_loss: 1.0896, test_acc: 71.98%\n",
      "[Epoch 7/10] loss: 1.0777, acc: 77.72% - test_loss: 1.0764, test_acc: 80.14%\n",
      "[Epoch 8/10] loss: 1.0456, acc: 82.56% - test_loss: 1.0916, test_acc: 95.06%\n",
      "[Epoch 9/10] loss: 0.9874, acc: 96.27% - test_loss: 0.9321, test_acc: 99.40%\n",
      "[Epoch 10/10] loss: 0.8819, acc: 97.98% - test_loss: 0.8538, test_acc: 99.90%\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x450 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Setup the training and test data generators\n",
    "difficulty     = QRSU.DifficultyLevel.EASY\n",
    "batch_size     = 32\n",
    "train_data_gen = QRSU.get_predefined_generator(difficulty, batch_size)\n",
    "test_data_gen  = QRSU.get_predefined_generator(difficulty, batch_size)\n",
    "\n",
    "# Setup the RNN and training settings\n",
    "input_size  = train_data_gen.n_symbols\n",
    "hidden_size = 4\n",
    "output_size = train_data_gen.n_classes\n",
    "model       = SimpleLSTM(input_size, hidden_size, output_size)\n",
    "criterion   = torch.nn.CrossEntropyLoss()\n",
    "optimizer   = torch.optim.RMSprop(model.parameters(), lr=0.001)\n",
    "max_epochs  = 10\n",
    "\n",
    "# Train the model\n",
    "model = train_and_test(model, train_data_gen, test_data_gen, criterion, optimizer, max_epochs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([16, 8])\n",
      "torch.Size([16, 4])\n",
      "torch.Size([16])\n",
      "torch.Size([16])\n",
      "torch.Size([4, 4])\n",
      "torch.Size([4])\n"
     ]
    }
   ],
   "source": [
    "for parameter_group in list(model.parameters()):\n",
    "    print(parameter_group.size())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6. RNN: Increasing Epoch to 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Epoch 100/100] loss: 0.0077, acc: 100.00% - test_loss: 0.0070, test_acc: 100.00%\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x450 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Setup the training and test data generators\n",
    "difficulty     = QRSU.DifficultyLevel.EASY\n",
    "batch_size     = 32\n",
    "train_data_gen = QRSU.get_predefined_generator(difficulty, batch_size)\n",
    "test_data_gen  = QRSU.get_predefined_generator(difficulty, batch_size)\n",
    "\n",
    "# Setup the RNN and training settings\n",
    "input_size  = train_data_gen.n_symbols\n",
    "hidden_size = 4\n",
    "output_size = train_data_gen.n_classes\n",
    "model       = SimpleRNN(input_size, hidden_size, output_size)\n",
    "criterion   = torch.nn.CrossEntropyLoss()\n",
    "optimizer   = torch.optim.RMSprop(model.parameters(), lr=0.001)\n",
    "max_epochs  = 100\n",
    "\n",
    "# Train the model\n",
    "model = train_and_test(model, train_data_gen, test_data_gen, criterion, optimizer, max_epochs, verbose=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## LSTM: Increasing Epoch to 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Epoch 100/100] loss: 0.0017, acc: 100.00% - test_loss: 0.0017, test_acc: 100.00%\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x450 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Setup the training and test data generators\n",
    "difficulty     = QRSU.DifficultyLevel.EASY\n",
    "batch_size     = 32\n",
    "train_data_gen = QRSU.get_predefined_generator(difficulty, batch_size)\n",
    "test_data_gen  = QRSU.get_predefined_generator(difficulty, batch_size)\n",
    "\n",
    "# Setup the RNN and training settings\n",
    "input_size  = train_data_gen.n_symbols\n",
    "hidden_size = 4\n",
    "output_size = train_data_gen.n_classes\n",
    "model       = SimpleLSTM(input_size, hidden_size, output_size)\n",
    "criterion   = torch.nn.CrossEntropyLoss()\n",
    "optimizer   = torch.optim.RMSprop(model.parameters(), lr=0.001)\n",
    "max_epochs  = 100\n",
    "\n",
    "# Train the model\n",
    "model = train_and_test(model, train_data_gen, test_data_gen, criterion, optimizer, max_epochs, verbose=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7. Model Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "import collections\n",
    "import random\n",
    "\n",
    "def evaluate_model(model, difficulty, seed=9001, verbose=False):\n",
    "    # Define a dictionary that maps class indices to labels\n",
    "    class_idx_to_label = {0: 'Q', 1: 'R', 2: 'S', 3: 'U'}\n",
    "\n",
    "    # Create a new data generator\n",
    "    data_generator = QRSU.get_predefined_generator(difficulty, seed=seed)\n",
    "\n",
    "    # Track the number of times a class appears\n",
    "    count_classes = collections.Counter()\n",
    "\n",
    "    # Keep correctly classified and misclassified sequences, and their\n",
    "    # true and predicted class labels, for diagnostic information.\n",
    "    correct = []\n",
    "    incorrect = []\n",
    "\n",
    "    device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')\n",
    "\n",
    "    model.eval()\n",
    "\n",
    "    with torch.no_grad():\n",
    "        for batch_idx in range(len(data_generator)):\n",
    "            data, target = test_data_gen[batch_idx]\n",
    "            data, target = torch.from_numpy(data).float().to(device), torch.from_numpy(target).long().to(device)\n",
    "\n",
    "            data_decoded = data_generator.decode_x_batch(data.cpu().numpy())\n",
    "            target_decoded = data_generator.decode_y_batch(target.cpu().numpy())\n",
    "\n",
    "            output = model(data)\n",
    "            sequence_end = torch.tensor([len(sequence) for sequence in data_decoded]) - 1\n",
    "            output = output[torch.arange(data.shape[0]).long(), sequence_end, :]\n",
    "\n",
    "            target = target.argmax(dim=1)\n",
    "            y_pred = output.argmax(dim=1)\n",
    "            y_pred_decoded = [class_idx_to_label[y.item()] for y in y_pred]\n",
    "\n",
    "            count_classes.update(target_decoded)\n",
    "            for i, (truth, prediction) in enumerate(zip(target_decoded, y_pred_decoded)):\n",
    "                if truth == prediction:\n",
    "                    correct.append((data_decoded[i], truth, prediction))\n",
    "                else:\n",
    "                    incorrect.append((data_decoded[i], truth, prediction))\n",
    "\n",
    "    num_sequences = sum(count_classes.values())\n",
    "    accuracy = float(len(correct)) / num_sequences * 100\n",
    "    print(f'The accuracy of the model is measured to be {accuracy:.2f}%.\\n')\n",
    "\n",
    "    # Report the accuracy by class\n",
    "    for label in sorted(count_classes):\n",
    "        num_correct = sum(1 for _, truth, _ in correct if truth == label)\n",
    "        print(f'{label}: {num_correct} / {count_classes[label]} correct')\n",
    "\n",
    "    # Report some random sequences for examination\n",
    "    print('\\nHere are some example sequences:')\n",
    "    for i in range(10):\n",
    "        sequence, truth, prediction = correct[random.randrange(0, 10)]\n",
    "        print(f'{sequence} -> {truth} was labelled {prediction}')\n",
    "\n",
    "    # Report misclassified sequences for investigation\n",
    "    if incorrect and verbose:\n",
    "        print('\\nThe following sequences were misclassified:')\n",
    "        for sequence, truth, prediction in incorrect:\n",
    "            print(f'{sequence} -> {truth} was labelled {prediction}')\n",
    "    else:\n",
    "        print('\\nThere were no misclassified sequences.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The accuracy of the model is measured to be 85.08%.\n",
      "\n",
      "Q: 193 / 258 correct\n",
      "R: 249 / 249 correct\n",
      "S: 149 / 232 correct\n",
      "U: 253 / 253 correct\n",
      "\n",
      "Here are some example sequences:\n",
      "BbYaYdbE -> U was labelled U\n",
      "BYdcaYbE -> U was labelled U\n",
      "BbXcXbcE -> Q was labelled Q\n",
      "BcXbYdaE -> R was labelled R\n",
      "BcYdYdaE -> U was labelled U\n",
      "BcXbYdaE -> R was labelled R\n",
      "BcYacYbE -> U was labelled U\n",
      "BbXaXdE -> Q was labelled Q\n",
      "BYdcaYbE -> U was labelled U\n",
      "BbXcXbcE -> Q was labelled Q\n",
      "\n",
      "There were no misclassified sequences.\n"
     ]
    }
   ],
   "source": [
    "evaluate_model(model, difficulty)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 8. Visualize LSTM\n",
    "Setting difficulty to `MODERATE` and `hidden_size` to 12."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Epoch 100/100] loss: 0.1438, acc: 97.58% - test_loss: 0.0704, test_acc: 97.88%\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x450 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# For reproducibility\n",
    "torch.manual_seed(1)\n",
    "\n",
    "# Setup the training and test data generators\n",
    "difficulty     = QRSU.DifficultyLevel.MODERATE\n",
    "batch_size     = 32\n",
    "train_data_gen = QRSU.get_predefined_generator(difficulty, batch_size)\n",
    "test_data_gen  = QRSU.get_predefined_generator(difficulty, batch_size)\n",
    "\n",
    "# Setup the RNN and training settings\n",
    "input_size  = train_data_gen.n_symbols\n",
    "hidden_size = 12\n",
    "output_size = train_data_gen.n_classes\n",
    "model       = SimpleLSTM(input_size, hidden_size, output_size)\n",
    "criterion   = torch.nn.CrossEntropyLoss()\n",
    "optimizer   = torch.optim.RMSprop(model.parameters(), lr=0.001)\n",
    "max_epochs  = 100\n",
    "\n",
    "# Train the model\n",
    "model = train_and_test(model, train_data_gen, test_data_gen, criterion, optimizer, max_epochs, verbose=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get hidden (H) and cell (C) batch state given a batch input (X)\n",
    "device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')\n",
    "model.eval()\n",
    "with torch.no_grad():\n",
    "    data = test_data_gen[0][0]\n",
    "    X = torch.from_numpy(data).float().to(device)\n",
    "    H_t, C_t = model.get_states_across_time(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Color range is as follows:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<text style=color:#000;background-color:#85c2e1>-2.50 </text><text style=color:#000;background-color:#89c4e2>-2.24 </text><text style=color:#000;background-color:#95cae5>-1.97 </text><text style=color:#000;background-color:#99cce6>-1.71 </text><text style=color:#000;background-color:#a1d0e8>-1.45 </text><text style=color:#000;background-color:#b2d9ec>-1.18 </text><text style=color:#000;background-color:#baddee>-0.92 </text><text style=color:#000;background-color:#c2e1f0>-0.66 </text><text style=color:#000;background-color:#eff7fb>-0.39 </text><text style=color:#000;background-color:#f9e8e8>-0.13 </text><text style=color:#000;background-color:#f9e8e8>0.13 </text><text style=color:#000;background-color:#f9d4d4>0.39 </text><text style=color:#000;background-color:#f9bdbd>0.66 </text><text style=color:#000;background-color:#f8a8a8>0.92 </text><text style=color:#000;background-color:#f68f8f>1.18 </text><text style=color:#000;background-color:#f47676>1.45 </text><text style=color:#000;background-color:#f45f5f>1.71 </text><text style=color:#000;background-color:#f34343>1.97 </text><text style=color:#000;background-color:#f33b3b>2.24 </text><text style=color:#000;background-color:#f42e2e>2.50 </text>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Color range is as follows:\")\n",
    "print_colourbar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<IPython.core.display.HTML object>"
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       "<text style=color:#000;background-color:#f9d4d4>B </text><text style=color:#000;background-color:#f9d4d4>b </text><text style=color:#000;background-color:#f9bdbd>a </text><text style=color:#000;background-color:#f9bdbd>b </text><text style=color:#000;background-color:#f9d4d4>d </text><text style=color:#000;background-color:#f9d4d4>b </text><text style=color:#000;background-color:#f9bdbd>c </text><text style=color:#000;background-color:#f9d4d4>d </text><text style=color:#000;background-color:#f9e8e8>d </text><text style=color:#000;background-color:#f9e8e8>b </text><text style=color:#000;background-color:#f9e8e8>d </text><text style=color:#000;background-color:#f9d4d4>c </text><text style=color:#000;background-color:#f9d4d4>c </text><text style=color:#000;background-color:#f9e8e8>b </text><text style=color:#000;background-color:#f9d4d4>a </text><text style=color:#000;background-color:#f9e8e8>d </text><text style=color:#000;background-color:#f9e8e8>c </text><text style=color:#000;background-color:#f9e8e8>d </text><text style=color:#000;background-color:#f9e8e8>c </text><text style=color:#000;background-color:#f9e8e8>d </text><text style=color:#000;background-color:#c2e1f0>X </text><text style=color:#000;background-color:#f9e8e8>c </text><text style=color:#000;background-color:#f9e8e8>c </text><text style=color:#000;background-color:#f9e8e8>d </text><text style=color:#000;background-color:#f9e8e8>c </text><text style=color:#000;background-color:#f9d4d4>c </text><text style=color:#000;background-color:#f9d4d4>a </text><text style=color:#000;background-color:#f9d4d4>a </text><text style=color:#000;background-color:#f9e8e8>b </text><text style=color:#000;background-color:#f9e8e8>c </text><text style=color:#000;background-color:#f9e8e8>a </text><text style=color:#000;background-color:#f9e8e8>a </text><text style=color:#000;background-color:#f9e8e8>d </text><text style=color:#000;background-color:#f9e8e8>a </text><text style=color:#000;background-color:#f9e8e8>b </text><text style=color:#000;background-color:#f9e8e8>d </text><text style=color:#000;background-color:#eff7fb>b </text><text style=color:#000;background-color:#f9e8e8>c </text><text style=color:#000;background-color:#f9e8e8>a </text><text style=color:#000;background-color:#f9e8e8>a </text><text style=color:#000;background-color:#f9e8e8>d </text><text style=color:#000;background-color:#f9d4d4>d </text><text style=color:#000;background-color:#f9bdbd>c </text><text style=color:#000;background-color:#f9bdbd>b </text><text style=color:#000;background-color:#f9bdbd>b </text><text style=color:#000;background-color:#f9bdbd>b </text><text style=color:#000;background-color:#f8a8a8>c </text><text style=color:#000;background-color:#f8a8a8>d </text><text style=color:#000;background-color:#f8a8a8>a </text><text style=color:#000;background-color:#f8a8a8>d </text><text style=color:#000;background-color:#f8a8a8>d </text><text style=color:#000;background-color:#f8a8a8>d </text><text style=color:#000;background-color:#f8a8a8>c </text><text style=color:#000;background-color:#f8a8a8>d </text><text style=color:#000;background-color:#f9d4d4>X </text><text style=color:#000;background-color:#f9bdbd>a </text><text style=color:#000;background-color:#f9bdbd>d </text><text style=color:#000;background-color:#f9bdbd>b </text><text style=color:#000;background-color:#f8a8a8>c </text><text style=color:#000;background-color:#f68f8f>E </text>"
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       "<IPython.core.display.HTML object>"
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       "<IPython.core.display.HTML object>"
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   ],
   "source": [
    "plot_state(X.cpu(), C_t, b=9, decoder=test_data_gen.decode_x)  # 3, 6, 9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
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