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‎tutorials/02 - Logistic Regression/main.py‎

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learning_rate = 0.001
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# MNIST Dataset (Images and Labels)
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train_dataset = dsets.MNIST(root='../data',
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train_dataset = dsets.MNIST(root='./data',
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train=True,
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transform=transforms.ToTensor(),
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download=True)
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test_dataset = dsets.MNIST(root='../data',
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test_dataset = dsets.MNIST(root='./data',
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train=False,
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transform=transforms.ToTensor())
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‎tutorials/03 - Feedforward Neural Network/main-gpu.py‎

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learning_rate = 0.001
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# MNIST Dataset
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train_dataset = dsets.MNIST(root='../data',
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train_dataset = dsets.MNIST(root='./data',
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train=True,
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transform=transforms.ToTensor(),
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download=True)
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test_dataset = dsets.MNIST(root='../data',
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test_dataset = dsets.MNIST(root='./data',
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train=False,
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transform=transforms.ToTensor())
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‎tutorials/03 - Feedforward Neural Network/main.py‎

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@@ -14,12 +14,12 @@
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learning_rate = 0.001
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# MNIST Dataset
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train_dataset = dsets.MNIST(root='../data',
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train_dataset = dsets.MNIST(root='./data',
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train=True,
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transform=transforms.ToTensor(),
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download=True)
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test_dataset = dsets.MNIST(root='../data',
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test_dataset = dsets.MNIST(root='./data',
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train=False,
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transform=transforms.ToTensor())
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‎tutorials/04 - Convolutional Neural Network/main-gpu.py‎

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@@ -11,12 +11,12 @@
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learning_rate = 0.001
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# MNIST Dataset
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train_dataset = dsets.MNIST(root='../data/',
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train_dataset = dsets.MNIST(root='./data/',
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train=True,
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transform=transforms.ToTensor(),
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download=True)
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test_dataset = dsets.MNIST(root='../data/',
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test_dataset = dsets.MNIST(root='./data/',
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train=False,
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transform=transforms.ToTensor())
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‎tutorials/04 - Convolutional Neural Network/main.py‎

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learning_rate = 0.001
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# MNIST Dataset
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train_dataset = dsets.MNIST(root='../data/',
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train_dataset = dsets.MNIST(root='./data/',
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train=True,
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transform=transforms.ToTensor(),
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download=True)
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test_dataset = dsets.MNIST(root='../data/',
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test_dataset = dsets.MNIST(root='./data/',
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train=False,
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transform=transforms.ToTensor())
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‎tutorials/05 - Deep Residual Network/main-gpu.py‎

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transforms.ToTensor()])
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# CIFAR-10 Dataset
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train_dataset = dsets.CIFAR10(root='../data/',
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train_dataset = dsets.CIFAR10(root='./data/',
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train=True,
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transform=transform,
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download=True)
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test_dataset = dsets.CIFAR10(root='../data/',
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test_dataset = dsets.CIFAR10(root='./data/',
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train=False,
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transform=transforms.ToTensor())
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‎tutorials/05 - Deep Residual Network/main.py‎

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transforms.ToTensor()])
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# CIFAR-10 Dataset
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train_dataset = dsets.CIFAR10(root='../data/',
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train_dataset = dsets.CIFAR10(root='./data/',
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train=True,
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transform=transform,
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download=True)
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test_dataset = dsets.CIFAR10(root='../data/',
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test_dataset = dsets.CIFAR10(root='./data/',
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train=False,
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transform=transforms.ToTensor())
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‎tutorials/06 - Recurrent Neural Network/main-gpu.py‎

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learning_rate = 0.01
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# MNIST Dataset
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train_dataset = dsets.MNIST(root='../data/',
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train_dataset = dsets.MNIST(root='./data/',
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train=True,
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transform=transforms.ToTensor(),
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download=True)
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test_dataset = dsets.MNIST(root='../data/',
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test_dataset = dsets.MNIST(root='./data/',
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train=False,
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transform=transforms.ToTensor())
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‎tutorials/06 - Recurrent Neural Network/main.py‎

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learning_rate = 0.01
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# MNIST Dataset
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train_dataset = dsets.MNIST(root='../data/',
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train_dataset = dsets.MNIST(root='./data/',
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train=True,
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transform=transforms.ToTensor(),
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download=True)
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test_dataset = dsets.MNIST(root='../data/',
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test_dataset = dsets.MNIST(root='./data/',
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train=False,
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transform=transforms.ToTensor())
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‎tutorials/07 - Bidirectional Recurrent Neural Network/main-gpu.py‎

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learning_rate = 0.003
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# MNIST Dataset
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train_dataset = dsets.MNIST(root='../data/',
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train_dataset = dsets.MNIST(root='./data/',
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train=True,
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transform=transforms.ToTensor(),
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download=True)
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test_dataset = dsets.MNIST(root='../data/',
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test_dataset = dsets.MNIST(root='./data/',
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train=False,
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transform=transforms.ToTensor())
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