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udlbook
2023-12-17 20:30:17 +00:00
parent 905d7d1ac4
commit 2e343bc652
1 changed files with 3 additions and 3 deletions
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Notebooks/Chap10/10_2_Convolution_for_MNIST_1D.ipynb
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@@ -4,7 +4,7 @@
"metadata": { "metadata": {
"colab": { "colab": {
"provenance": [], "provenance": [],
"authorship_tag": "ABX9TyN1qtywBuyezaVMnc9MI7x2", "authorship_tag": "ABX9TyNJodaaCLMRWL9vTl8B/iLI",
"include_colab_link": true "include_colab_link": true
}, },
"kernelspec": { "kernelspec": {
@@ -188,9 +188,9 @@
"scheduler = StepLR(optimizer, step_size=20, gamma=0.5)\n", "scheduler = StepLR(optimizer, step_size=20, gamma=0.5)\n",
"# create 100 dummy data points and store in data loader class\n", "# create 100 dummy data points and store in data loader class\n",
"x_train = torch.tensor(train_data_x.transpose().astype('float32'))\n", "x_train = torch.tensor(train_data_x.transpose().astype('float32'))\n",
"y_train = torch.tensor(train_data_y.astype('long'))\n", "y_train = torch.tensor(train_data_y.astype('long')).long()\n",
"x_val= torch.tensor(val_data_x.transpose().astype('float32'))\n", "x_val= torch.tensor(val_data_x.transpose().astype('float32'))\n",
"y_val = torch.tensor(val_data_y.astype('long'))\n", "y_val = torch.tensor(val_data_y.astype('long')).long()\n",
"\n", "\n",
"# load the data into a class that creates the batches\n", "# load the data into a class that creates the batches\n",
"data_loader = DataLoader(TensorDataset(x_train,y_train), batch_size=100, shuffle=True, worker_init_fn=np.random.seed(1))\n", "data_loader = DataLoader(TensorDataset(x_train,y_train), batch_size=100, shuffle=True, worker_init_fn=np.random.seed(1))\n",