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"from tensorflow.keras.models import Sequential\n", + "from tensorflow.keras.layers import LSTM, Dense, Normalization\n", + "\n", + "# Fix seed for NumPy\n", + "np.random.seed(42)\n", + "\n", + "# Fix seed for TensorFlow\n", + "tf.random.set_seed(42)\n", + "\n", + "rn.seed(42)\n", + "\n", + "tf.keras.utils.set_random_seed(42)" + ], + "metadata": { + "id": "RX2AKL-mDuL7" + }, + "execution_count": 1, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "# Data generation and plot" + ], + "metadata": { + "id": "391Mb-JwrN2d" + } + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "id": "wdd3K0E9DMzy" + }, + "outputs": [], + "source": [ + "def make_sine_ts(n_points, start_time=0, dimension=1, n_periods=4, ampl=10):\n", + " sigma = ampl / 10\n", + " time = np.arange(1, n_points + 1)\n", + " series_sine = ampl * np.sin(np.tile(time * (2 * np.pi * n_periods) / n_points + start_time, (dimension, 1)).T) + sigma * np.random.randn(n_points, dimension)\n", + " table = np.column_stack((time, series_sine))\n", + " columns = ['Time'] + [f'Sine_{i}' for i in range(1, dimension + 1)]\n", + " ts = pd.DataFrame(table, columns=columns)\n", + " return ts" + ] + }, + { + "cell_type": "code", + "source": [ + "# generate synthetic time series\n", + "time = 500000\n", + "time_series_data = pd.DataFrame()\n", + "for i in range(28):\n", + " ts = make_sine_ts(time, dimension=1, start_time=i * 10)\n", + " time_series_data[f'Sine_{i+1}'] = ts.iloc[:, 1]\n", + "time_series_data" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 444 + }, + "id": "z25QSoBsDOEx", + "outputId": "51606af9-8656-442a-f025-ae26a685758f" + }, + "execution_count": 3, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " Sine_1 Sine_2 Sine_3 Sine_4 Sine_5 Sine_6 \\\n", + "0 0.497217 -6.503658 9.298829 -10.018320 8.515519 -3.087901 \n", + "1 -0.137259 -6.261307 9.008358 -9.833064 6.953748 -1.567958 \n", + "2 0.649197 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\n" + ], + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "dataframe", + "variable_name": "time_series_data" + } + }, + "metadata": {}, + "execution_count": 3 + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "# Forecast with score based model" + ], + "metadata": { + "id": "68jZbwWpYWub" + } + }, + { + "cell_type": "code", + "source": [ + "from sklearn.preprocessing import StandardScaler\n", + "from sklearn.decomposition import PCA\n", + "from sklearn.manifold import MDS\n", + "from sklearn.metrics import mean_squared_error\n", + "from scipy.linalg import hankel\n", + "from sklearn.covariance import LedoitWolf" + ], + "metadata": { + "id": "zSrJWMwb5963" + }, + "execution_count": 4, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "time_series_data.shape" + ], + "metadata": { + "id": "5oL91A1MMD1i", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "213a7b63-87e5-4a60-c008-137faaf141f4" + }, + "execution_count": 5, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(500000, 28)" + ] + }, + "metadata": {}, + "execution_count": 5 + } + ] + }, + { + "cell_type": "code", + "source": [ + "window_size = 6" + ], + "metadata": { + "id": "Lw8VtWANCKRp" + }, + "execution_count": 6, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "def create_hankel_matrix(time_series, window_size):\n", + " hankel_matrix = hankel(time_series[:-window_size+1], time_series[-window_size:])\n", + " return hankel_matrix" + ], + "metadata": { + "id": "IX0QaWv1_U0e" + }, + "execution_count": 7, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "def calculate_distance_matrix(matrices):\n", + " # Check if the matrices have the same number of vectors\n", + " # matrices shape (num_series, num_times, window_sz)\n", + " distances_matrix = np.zeros((matrices.shape[1], matrices.shape[0], matrices.shape[0]))\n", + "\n", + " # Iterate through the vectors in the matrices\n", + " for i in range(distances_matrix.shape[0]):\n", + " mu = np.mean(matrices[:,i,:], axis=-1)\n", + " T = matrices.shape[2]\n", + " for t in range(T):\n", + " x = (matrices[:,i,t] - mu).reshape(-1, 1)\n", + " distances_matrix[i] += x @ x.T\n", + " distances_matrix[i] *= 1/T\n", + " return distances_matrix" + ], + "metadata": { + "id": "E1A5wfDRCnlh" + }, + "execution_count": 8, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "def reshape_to_2d(matrix):\n", + " return matrix.reshape(matrix.shape[0], -1)\n", + "\n", + "def reshape_to_3d(matrix, num):\n", + " return matrix.reshape(matrix.shape[0], num, -1)" + ], + "metadata": { + "id": "Nfs2Jg3uKEKI" + }, + "execution_count": 9, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "def get_distance_matrix(time_series, window_size=6):\n", + " matrices = np.stack([create_hankel_matrix(time_series.iloc[:, i], window_size) for i in range(time_series.shape[1])])\n", + " print(matrices.shape)\n", + " distances = calculate_distance_matrix(matrices)\n", + " print(distances.shape)\n", + " return distances" + ], + "metadata": { + "id": "pf1HrIN9LtZ2" + }, + "execution_count": 10, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "X = get_distance_matrix(time_series_data)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "POySDwjOFk84", + "outputId": "b25ec455-8b28-4788-f618-fb817cc4bc04" + }, + "execution_count": 11, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "(28, 499995, 6)\n", + "(499995, 28, 28)\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "X = X.reshape(X.shape[0], 1, X.shape[1], X.shape[2])\n", + "X.shape" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "1IdWi25aVUOL", + "outputId": "a6633c89-5894-454a-f407-160435c2cd4a" + }, + "execution_count": 12, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(499995, 1, 28, 28)" + ] + }, + "metadata": {}, + "execution_count": 12 + } + ] + }, + { + "cell_type": "code", + "source": [ + "N = int(0.8 * len(X))\n", + "X_train, X_test = X[:N], X[N:]\n", + "X_train.shape, X_test.shape" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "7axvnxSgGY82", + "outputId": "281d0656-cb5a-465c-e3ae-d8d034715a81" + }, + "execution_count": 13, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "((399996, 1, 28, 28), (99999, 1, 28, 28))" + ] + }, + "metadata": {}, + "execution_count": 13 + } + ] + }, + { + "cell_type": "code", + "source": [ + "import torch\n", + "import torch.nn as nn\n", + "import torch.nn.functional as F\n", + "import numpy as np\n", + "import functools\n", + "\n", + "from torch.optim import Adam\n", + "from torch.utils.data import DataLoader, TensorDataset\n", + "from torchvision import datasets, transforms\n", + "from torchvision.datasets import MNIST\n", + "import tqdm" + ], + "metadata": { + "id": "rr9h4xIyKxg3" + }, + "execution_count": 14, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "YyQtV7155Nht" + }, + "source": [ + "#@title Defining a time-dependent score-based model (double click to expand or collapse)\n", + "\n", + "class GaussianFourierProjection(nn.Module):\n", + " \"\"\"Gaussian random features for encoding time steps.\"\"\"\n", + " def __init__(self, embed_dim, scale=30.):\n", + " super().__init__()\n", + " # Randomly sample weights during initialization. These weights are fixed\n", + " # during optimization and are not trainable.\n", + " self.W = nn.Parameter(torch.randn(embed_dim // 2) * scale, requires_grad=False)\n", + " def forward(self, x):\n", + " x_proj = x[:, None] * self.W[None, :] * 2 * np.pi\n", + " return torch.cat([torch.sin(x_proj), torch.cos(x_proj)], dim=-1)\n", + "\n", + "\n", + "class Dense(nn.Module):\n", + " \"\"\"A fully connected layer that reshapes outputs to feature maps.\"\"\"\n", + " def __init__(self, input_dim, output_dim):\n", + " super().__init__()\n", + " self.dense = nn.Linear(input_dim, output_dim)\n", + " def forward(self, x):\n", + " return self.dense(x)[..., None, None]\n", + "\n", + "\n", + "class ScoreNet(nn.Module):\n", + " \"\"\"A time-dependent score-based model built upon U-Net architecture.\"\"\"\n", + "\n", + " def __init__(self, marginal_prob_std, channels=[32, 64, 128, 256], embed_dim=256):\n", + " \"\"\"Initialize a time-dependent score-based network.\n", + "\n", + " Args:\n", + " marginal_prob_std: A function that takes time t and gives the standard\n", + " deviation of the perturbation kernel p_{0t}(x(t) | x(0)).\n", + " channels: The number of channels for feature maps of each resolution.\n", + " embed_dim: The dimensionality of Gaussian random feature embeddings.\n", + " \"\"\"\n", + " super().__init__()\n", + " # Gaussian random feature embedding layer for time\n", + " self.embed = nn.Sequential(GaussianFourierProjection(embed_dim=embed_dim),\n", + " nn.Linear(embed_dim, embed_dim))\n", + " # Encoding layers where the resolution decreases\n", + " self.conv1 = nn.Conv2d(1, channels[0], 3, stride=1, bias=False)\n", + " self.dense1 = Dense(embed_dim, channels[0])\n", + " self.gnorm1 = nn.GroupNorm(4, num_channels=channels[0])\n", + " self.conv2 = nn.Conv2d(channels[0], channels[1], 3, stride=2, bias=False)\n", + " self.dense2 = Dense(embed_dim, channels[1])\n", + " self.gnorm2 = nn.GroupNorm(32, num_channels=channels[1])\n", + " self.conv3 = nn.Conv2d(channels[1], channels[2], 3, stride=2, bias=False)\n", + " self.dense3 = Dense(embed_dim, channels[2])\n", + " self.gnorm3 = nn.GroupNorm(32, num_channels=channels[2])\n", + " self.conv4 = nn.Conv2d(channels[2], channels[3], 3, stride=2, bias=False)\n", + " self.dense4 = Dense(embed_dim, channels[3])\n", + " self.gnorm4 = nn.GroupNorm(32, num_channels=channels[3])\n", + "\n", + " # Decoding layers where the resolution increases\n", + " self.tconv4 = nn.ConvTranspose2d(channels[3], channels[2], 3, stride=2, bias=False)\n", + " self.dense5 = Dense(embed_dim, channels[2])\n", + " self.tgnorm4 = nn.GroupNorm(32, num_channels=channels[2])\n", + " self.tconv3 = nn.ConvTranspose2d(channels[2] + channels[2], channels[1], 3, stride=2, bias=False, output_padding=1)\n", + " self.dense6 = Dense(embed_dim, channels[1])\n", + " self.tgnorm3 = nn.GroupNorm(32, num_channels=channels[1])\n", + " self.tconv2 = nn.ConvTranspose2d(channels[1] + channels[1], channels[0], 3, stride=2, bias=False, output_padding=1)\n", + " self.dense7 = Dense(embed_dim, channels[0])\n", + " self.tgnorm2 = nn.GroupNorm(32, num_channels=channels[0])\n", + " self.tconv1 = nn.ConvTranspose2d(channels[0] + channels[0], 1, 3, stride=1)\n", + "\n", + " # The swish activation function\n", + " self.act = lambda x: x * torch.sigmoid(x)\n", + " self.marginal_prob_std = marginal_prob_std\n", + "\n", + " def forward(self, x, t):\n", + " # Obtain the Gaussian random feature embedding for t\n", + " embed = self.act(self.embed(t))\n", + " # Encoding path\n", + " h1 = self.conv1(x)\n", + " ## Incorporate information from t\n", + " h1 += self.dense1(embed)\n", + " ## Group normalization\n", + " h1 = self.gnorm1(h1)\n", + " h1 = self.act(h1)\n", + " h2 = self.conv2(h1)\n", + " h2 += self.dense2(embed)\n", + " h2 = self.gnorm2(h2)\n", + " h2 = self.act(h2)\n", + " h3 = self.conv3(h2)\n", + " h3 += self.dense3(embed)\n", + " h3 = self.gnorm3(h3)\n", + " h3 = self.act(h3)\n", + " h4 = self.conv4(h3)\n", + " h4 += self.dense4(embed)\n", + " h4 = self.gnorm4(h4)\n", + " h4 = self.act(h4)\n", + "\n", + " # Decoding path\n", + " h = self.tconv4(h4)\n", + " ## Skip connection from the encoding path\n", + " h += self.dense5(embed)\n", + " h = self.tgnorm4(h)\n", + " h = self.act(h)\n", + " h = self.tconv3(torch.cat([h, h3], dim=1))\n", + " h += self.dense6(embed)\n", + " h = self.tgnorm3(h)\n", + " h = self.act(h)\n", + " h = self.tconv2(torch.cat([h, h2], dim=1))\n", + " h += self.dense7(embed)\n", + " h = self.tgnorm2(h)\n", + " h = self.act(h)\n", + " h = self.tconv1(torch.cat([h, h1], dim=1))\n", + "\n", + " # Normalize output\n", + " h = h / self.marginal_prob_std(t)[:, None, None, None]\n", + " return h" + ], + "execution_count": 15, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "#@title Set up the SDE\n", + "\n", + "device = 'cuda' #@param ['cuda', 'cpu'] {'type':'string'}\n", + "\n", + "def marginal_prob_std(t, sigma):\n", + " \"\"\"Compute the mean and standard deviation of $p_{0t}(x(t) | x(0))$.\n", + "\n", + " Args:\n", + " t: A vector of time steps.\n", + " sigma: The $\\sigma$ in our SDE.\n", + "\n", + " Returns:\n", + " The standard deviation.\n", + " \"\"\"\n", + " t = torch.tensor(t, device=device)\n", + " return torch.sqrt((sigma**(2 * t) - 1.) / 2. / np.log(sigma))\n", + "\n", + "def diffusion_coeff(t, sigma):\n", + " \"\"\"Compute the diffusion coefficient of our SDE.\n", + "\n", + " Args:\n", + " t: A vector of time steps.\n", + " sigma: The $\\sigma$ in our SDE.\n", + "\n", + " Returns:\n", + " The vector of diffusion coefficients.\n", + " \"\"\"\n", + " return torch.tensor(sigma**t, device=device)\n", + "\n", + "sigma = 25.0#@param {'type':'number'}\n", + "marginal_prob_std_fn = functools.partial(marginal_prob_std, sigma=sigma)\n", + "diffusion_coeff_fn = functools.partial(diffusion_coeff, sigma=sigma)" + ], + "metadata": { + "id": "QQGWsLzUTEsB" + }, + "execution_count": 16, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "zOsoqPdXHuL5" + }, + "source": [ + "#@title Define the loss function (double click to expand or collapse)\n", + "\n", + "def loss_fn(model, x, marginal_prob_std, eps=1e-5):\n", + " \"\"\"The loss function for training score-based generative models.\n", + "\n", + " Args:\n", + " model: A PyTorch model instance that represents a\n", + " time-dependent score-based model.\n", + " x: A mini-batch of training data.\n", + " marginal_prob_std: A function that gives the standard deviation of\n", + " the perturbation kernel.\n", + " eps: A tolerance value for numerical stability.\n", + " \"\"\"\n", + " random_t = torch.rand(x.shape[0], device=x.device) * (1. - eps) + eps\n", + " z = torch.randn_like(x)\n", + " std = marginal_prob_std(random_t)\n", + " perturbed_x = x + z * std[:, None, None, None]\n", + " score = model(perturbed_x, random_t)\n", + " loss = torch.mean(torch.sum((score * std[:, None, None, None] + z)**2, dim=(1,2,3)))\n", + " return loss" + ], + "execution_count": 17, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "8PPsLx4dGCGa", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 208, + "referenced_widgets": [ + "6f4478ea94964503aed6695c389cd8d4", + "0ddcab2b812f48558a8cdfc2aa22abee", + "c2a0b4a38be5484fa2992c6d2b3154e9", + "3a6bee3c17884ae6bd5655cc75fdacd3", + "8b7219c434164f58a21b788ee3d0d1e1", + "ee984355aa894cd2a0b68edc85823036", + "424d7a61642b44ad86d01dd88bc04d87", + "129881e1ff164c218164b8f6466b8bf8", + "017c61b626974a5681acb5fd030b927c", + "9ac6148f92494e37990294a60a63164c", + "518bcf6e325b410292f18771b5f0ab1c" + ] + }, + "outputId": "6d2dd74d-7a80-4cc1-d302-f820e5a6c5e1" + }, + "source": [ + "#@title Training (double click to expand or collapse)\n", + "\n", + "score_model = torch.nn.DataParallel(ScoreNet(marginal_prob_std=marginal_prob_std_fn))\n", + "score_model = score_model.to(device)\n", + "\n", + "n_epochs = 50#@param {'type':'integer'}\n", + "## size of a mini-batch\n", + "batch_size = 32 #@param {'type':'integer'}\n", + "## learning rate\n", + "lr=1e-4 #@param {'type':'number'}\n", + "\n", + "# dataset = MNIST('.', train=True, transform=transforms.ToTensor(), download=True)\n", + "dataset = TensorDataset(torch.from_numpy(X_train).float(), torch.from_numpy(X_train).float())\n", + "data_loader = DataLoader(dataset, batch_size=batch_size, shuffle=True, num_workers=4)\n", + "\n", + "optimizer = Adam(score_model.parameters(), lr=lr)\n", + "tqdm_epoch = tqdm.notebook.trange(n_epochs)\n", + "for epoch in tqdm_epoch:\n", + " avg_loss = 0.\n", + " num_items = 0\n", + " for x, y in data_loader:\n", + " x = x.to(device)\n", + " loss = loss_fn(score_model, x, marginal_prob_std_fn)\n", + " optimizer.zero_grad()\n", + " loss.backward()\n", + " optimizer.step()\n", + " avg_loss += loss.item() * x.shape[0]\n", + " num_items += x.shape[0]\n", + " # Print the averaged training loss so far.\n", + " tqdm_epoch.set_description('Average Loss: {:5f}'.format(avg_loss / num_items))\n", + " # Update the checkpoint after each epoch of training.\n", + " torch.save(score_model.state_dict(), 'ckpt.pth')" + ], + "execution_count": 18, + "outputs": [ + { + "output_type": "stream", + "name": "stderr", + "text": [ + "/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py:558: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.\n", + " warnings.warn(_create_warning_msg(\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + " 0%| | 0/50 [00:00:15: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n", + " t = torch.tensor(t, device=device)\n", + "/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n", + " self.pid = os.fork()\n" + ] + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "6FxBTOSSH2QR" + }, + "source": [ + "#@title Define the Euler-Maruyama sampler (double click to expand or collapse)\n", + "\n", + "## The number of sampling steps.\n", + "num_steps = 500#@param {'type':'integer'}\n", + "def Euler_Maruyama_sampler(score_model,\n", + " init_x,\n", + " marginal_prob_std,\n", + " diffusion_coeff,\n", + " batch_size=64,\n", + " num_steps=num_steps,\n", + " device='cuda',\n", + " eps=1e-3):\n", + " \"\"\"Generate samples from score-based models with the Euler-Maruyama solver.\n", + "\n", + " Args:\n", + " score_model: A PyTorch model that represents the time-dependent score-based model.\n", + " marginal_prob_std: A function that gives the standard deviation of\n", + " the perturbation kernel.\n", + " diffusion_coeff: A function that gives the diffusion coefficient of the SDE.\n", + " batch_size: The number of samplers to generate by calling this function once.\n", + " num_steps: The number of sampling steps.\n", + " Equivalent to the number of discretized time steps.\n", + " device: 'cuda' for running on GPUs, and 'cpu' for running on CPUs.\n", + " eps: The smallest time step for numerical stability.\n", + "\n", + " Returns:\n", + " Samples.\n", + " \"\"\"\n", + " t = torch.ones(batch_size, device=device)\n", + " init_x = init_x * marginal_prob_std(t)[:, None, None, None]\n", + " time_steps = torch.linspace(1., eps, num_steps, device=device)\n", + " step_size = time_steps[0] - time_steps[1]\n", + " x = init_x\n", + " with torch.no_grad():\n", + " for time_step in tqdm.notebook.tqdm(time_steps):\n", + " batch_time_step = torch.ones(batch_size, device=device) * time_step\n", + " g = diffusion_coeff(batch_time_step)\n", + " mean_x = x + (g**2)[:, None, None, None] * score_model(x, batch_time_step) * step_size\n", + " x = mean_x + torch.sqrt(step_size) * g[:, None, None, None] * torch.randn_like(x)\n", + " # Do not include any noise in the last sampling step.\n", + " return mean_x" + ], + "execution_count": 19, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "#@title Define the Predictor-Corrector sampler (double click to expand or collapse)\n", + "\n", + "signal_to_noise_ratio = 0.16 #@param {'type':'number'}\n", + "\n", + "## The number of sampling steps.\n", + "num_steps = 500#@param {'type':'integer'}\n", + "def pc_sampler(score_model,\n", + " init_x,\n", + " marginal_prob_std,\n", + " diffusion_coeff,\n", + " batch_size=64,\n", + " num_steps=num_steps,\n", + " snr=signal_to_noise_ratio,\n", + " device='cuda',\n", + " eps=1e-3):\n", + " \"\"\"Generate samples from score-based models with Predictor-Corrector method.\n", + "\n", + " Args:\n", + " score_model: A PyTorch model that represents the time-dependent score-based model.\n", + " marginal_prob_std: A function that gives the standard deviation\n", + " of the perturbation kernel.\n", + " diffusion_coeff: A function that gives the diffusion coefficient\n", + " of the SDE.\n", + " batch_size: The number of samplers to generate by calling this function once.\n", + " num_steps: The number of sampling steps.\n", + " Equivalent to the number of discretized time steps.\n", + " device: 'cuda' for running on GPUs, and 'cpu' for running on CPUs.\n", + " eps: The smallest time step for numerical stability.\n", + "\n", + " Returns:\n", + " Samples.\n", + " \"\"\"\n", + " t = torch.ones(batch_size, device=device)\n", + " init_x = init_x * marginal_prob_std(t)[:, None, None, None]\n", + " time_steps = np.linspace(1., eps, num_steps)\n", + " step_size = time_steps[0] - time_steps[1]\n", + " x = init_x\n", + " with torch.no_grad():\n", + " for time_step in tqdm.notebook.tqdm(time_steps):\n", + " batch_time_step = torch.ones(batch_size, device=device) * time_step\n", + " # Corrector step (Langevin MCMC)\n", + " grad = score_model(x, batch_time_step)\n", + " grad_norm = torch.norm(grad.reshape(grad.shape[0], -1), dim=-1).mean()\n", + " noise_norm = np.sqrt(np.prod(x.shape[1:]))\n", + " langevin_step_size = 2 * (snr * noise_norm / grad_norm)**2\n", + " x = x + langevin_step_size * grad + torch.sqrt(2 * langevin_step_size) * torch.randn_like(x)\n", + "\n", + " # Predictor step (Euler-Maruyama)\n", + " g = diffusion_coeff(batch_time_step)\n", + " x_mean = x + (g**2)[:, None, None, None] * score_model(x, batch_time_step) * step_size\n", + " x = x_mean + torch.sqrt(g**2 * step_size)[:, None, None, None] * torch.randn_like(x)\n", + "\n", + " # The last step does not include any noise\n", + " return x_mean" + ], + "metadata": { + "id": "bd_FC442w1Pq" + }, + "execution_count": 42, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "#@title Define the ODE sampler (double click to expand or collapse)\n", + "\n", + "from scipy import integrate\n", + "\n", + "## The error tolerance for the black-box ODE solver\n", + "error_tolerance = 1e-5 #@param {'type': 'number'}\n", + "def ode_sampler(score_model,\n", + " init_x,\n", + " marginal_prob_std,\n", + " diffusion_coeff,\n", + " batch_size=64,\n", + " atol=error_tolerance,\n", + " rtol=error_tolerance,\n", + " device='cuda',\n", + " z=None,\n", + " eps=1e-3):\n", + " \"\"\"Generate samples from score-based models with black-box ODE solvers.\n", + "\n", + " Args:\n", + " score_model: A PyTorch model that represents the time-dependent score-based model.\n", + " marginal_prob_std: A function that returns the standard deviation\n", + " of the perturbation kernel.\n", + " diffusion_coeff: A function that returns the diffusion coefficient of the SDE.\n", + " batch_size: The number of samplers to generate by calling this function once.\n", + " atol: Tolerance of absolute errors.\n", + " rtol: Tolerance of relative errors.\n", + " device: 'cuda' for running on GPUs, and 'cpu' for running on CPUs.\n", + " z: The latent code that governs the final sample. If None, we start from p_1;\n", + " otherwise, we start from the given z.\n", + " eps: The smallest time step for numerical stability.\n", + " \"\"\"\n", + " t = torch.ones(batch_size, device=device)\n", + " # Create the latent code\n", + " if z is None:\n", + " init_x = init_x * marginal_prob_std(t)[:, None, None, None]\n", + " else:\n", + " init_x = z\n", + "\n", + " shape = init_x.shape\n", + "\n", + " def score_eval_wrapper(sample, time_steps):\n", + " \"\"\"A wrapper of the score-based model for use by the ODE solver.\"\"\"\n", + " sample = torch.tensor(sample, device=device, dtype=torch.float32).reshape(shape)\n", + " time_steps = torch.tensor(time_steps, device=device, dtype=torch.float32).reshape((sample.shape[0], ))\n", + " with torch.no_grad():\n", + " score = score_model(sample, time_steps)\n", + " return score.cpu().numpy().reshape((-1,)).astype(np.float64)\n", + "\n", + " def ode_func(t, x):\n", + " \"\"\"The ODE function for use by the ODE solver.\"\"\"\n", + " time_steps = np.ones((shape[0],)) * t\n", + " g = diffusion_coeff(torch.tensor(t)).cpu().numpy()\n", + " return -0.5 * (g**2) * score_eval_wrapper(x, time_steps)\n", + "\n", + " # Run the black-box ODE solver.\n", + " res = integrate.solve_ivp(ode_func, (1., eps), init_x.reshape(-1).cpu().numpy(), rtol=rtol, atol=atol, method='RK45')\n", + " print(f\"Number of function evaluations: {res.nfev}\")\n", + " x = torch.tensor(res.y[:, -1], device=device).reshape(shape)\n", + "\n", + " return x\n" + ], + "metadata": { + "id": "rsx-ik6Jw4iv" + }, + "execution_count": 43, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "kKoAPnr7Pf2B", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 606 + }, + "outputId": "73a1e373-f55e-4df3-a77b-10c5ad81f3cf" + }, + "source": [ + "#@title Sampling (double click to expand or collapse)\n", + "\n", + "from torchvision.utils import make_grid\n", + "\n", + "## Load the pre-trained checkpoint from disk.\n", + "device = 'cuda' #@param ['cuda', 'cpu'] {'type':'string'}\n", + "\n", + "ckpt = torch.load('ckpt.pth', map_location=device)\n", + "score_model.load_state_dict(ckpt)\n", + "\n", + "sample_batch_size = 64 #@param {'type':'integer'}\n", + "sampler = ode_sampler #@param ['Euler_Maruyama_sampler', 'pc_sampler', 'ode_sampler'] {'type': 'raw'}\n", + "\n", + "init_x = torch.tensor(X_test[:sample_batch_size].copy(), device=device).float()\n", + "# init_x = torch.randn(sample_batch_size, 1, 28, 28, device=device)\n", + "\n", + "## Generate samples using the specified sampler.\n", + "samples = sampler(score_model,\n", + " init_x,\n", + " marginal_prob_std_fn,\n", + " diffusion_coeff_fn,\n", + " sample_batch_size,\n", + " device=device)\n", + "test_sampled = samples\n", + "## Sample visualization.\n", + "samples = samples.clamp(0.0, 1.0)\n", + "%matplotlib inline\n", + "import matplotlib.pyplot as plt\n", + "sample_grid = make_grid(samples, nrow=int(np.sqrt(sample_batch_size)))\n", + "\n", + "plt.figure(figsize=(6,6))\n", + "plt.axis('off')\n", + "plt.imshow(sample_grid.permute(1, 2, 0).cpu(), vmin=0., vmax=1.)\n", + "plt.show()" + ], + "execution_count": 62, + "outputs": [ + { + "output_type": "stream", + "name": "stderr", + "text": [ + ":15: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n", + " t = torch.tensor(t, device=device)\n", + ":28: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n", + " return torch.tensor(sigma**t, device=device)\n" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Number of function evaluations: 290\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "Просемплировали первые 64 матрицы из X_test.\n", + "\n", + "test_sampled - сгенерированные семплы\n", + "\n", + "init_x - первые 64 матрицы из X_test" + ], + "metadata": { + "id": "eXqGGFvYsr5S" + } + }, + { + "cell_type": "code", + "source": [ + "test_sampled.shape" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "xd2EjJUVatpR", + "outputId": "c62a1054-29b5-468c-dd79-936aa55041a5" + }, + "execution_count": 63, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "torch.Size([64, 1, 28, 28])" + ] + }, + "metadata": {}, + "execution_count": 63 + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "Далее, чтобы выводится только небольшой угол матрицы (5 x 5)" + ], + "metadata": { + "id": "IFV1xhd_xpdM" + } + }, + { + "cell_type": "markdown", + "source": [ + "Так выглядит первая сгенерированная матрица" + ], + "metadata": { + "id": "dAiKVP5xtt-C" + } + }, + { + "cell_type": "code", + "source": [ + "test_sampled[0, 0, :5, :5]" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "iXk3ywikd0yb", + "outputId": "ba8f594c-2255-4bf6-d050-f91016d51396" + }, + "execution_count": 64, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "tensor([[ 1.2607, 0.2827, -0.0887, -0.4888, 0.4323],\n", + " [ 0.2480, 0.3359, 0.0516, -0.0825, 0.0881],\n", + " [-0.0693, -0.0301, 0.2724, -0.0427, 0.0851],\n", + " [-0.4273, -0.0964, -0.0165, 0.5173, -0.3786],\n", + " [ 0.4271, 0.1012, 0.0454, -0.4077, 0.8874]], device='cuda:0',\n", + " dtype=torch.float64)" + ] + }, + "metadata": {}, + "execution_count": 64 + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "вторая матрица из X_test (к которой хотелось бы нормально приблизить первую сгенерированную матрицу)" + ], + "metadata": { + "id": "afZCv0IctrLH" + } + }, + { + "cell_type": "code", + "source": [ + "init_x = torch.tensor(X_test[:sample_batch_size].copy(), device=device).float()" + ], + "metadata": { + "id": "lrZN3HLAit6o" + }, + "execution_count": 65, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "init_x[1, 0, :5, :5]" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "_AzQ52cre0--", + "outputId": "9b66609f-a6f9-445c-98d6-28224aa6de48" + }, + "execution_count": 66, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "tensor([[ 2.0444, 1.7438, 0.2346, -0.2732, -0.1702],\n", + " [ 1.7438, 1.7142, 0.1825, -0.4120, -0.1365],\n", + " [ 0.2346, 0.1825, 0.1054, -0.0522, 0.0075],\n", + " [-0.2732, -0.4120, -0.0522, 0.7558, -0.2105],\n", + " [-0.1702, -0.1365, 0.0075, -0.2105, 0.5151]], device='cuda:0')" + ] + }, + "metadata": {}, + "execution_count": 66 + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "Проектируем сгенерированную матрицу" + ], + "metadata": { + "id": "I_rKFkgCuIm-" + } + }, + { + "cell_type": "code", + "source": [ + "from statsmodels.stats.correlation_tools import corr_nearest, cov_nearest" + ], + "metadata": { + "id": "PVbFpANje_Tu" + }, + "execution_count": 67, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "m = test_sampled[0, 0].cpu().numpy()\n", + "m = np.minimum( m, m.transpose() )\n", + "# m = m * m.transpose()\n", + "cov_nearest(m)[:5, :5]" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "6vB5EKvygVPl", + "outputId": "61253855-a6b3-42cf-9993-f085a5f1fd72" + }, + "execution_count": 72, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "array([[ 1.2606788 , 0.25203891, -0.08424888, -0.42537638, 0.3866388 ],\n", + " [ 0.25203891, 0.33587423, -0.02789081, -0.06622439, 0.07062489],\n", + " [-0.08424888, -0.02789081, 0.27243285, -0.02661243, 0.06419943],\n", + " [-0.42537638, -0.06622439, -0.02661243, 0.51728341, -0.3421899 ],\n", + " [ 0.3866388 , 0.07062489, 0.06419943, -0.3421899 , 0.88735916]])" + ] + }, + "metadata": {}, + "execution_count": 72 + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "Как видно выше, psd матрица совсем не похожа на вторую матрицу из X_test" + ], + "metadata": { + "id": "slrb9PkoufEU" + } + }, + { + "cell_type": "code", + "source": [], + "metadata": { + "id": "lcLZmn1-lZhA" + }, + "execution_count": 26, + "outputs": [] + } + ] +} \ No newline at end of file

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