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yunjey
2017-05-23 16:33:36 +09:00
parent 3923f4df6c
commit 47d70f91ac
11 changed files with 22 additions and 22 deletions
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4
tutorials/02 - Logistic Regression/main.py
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@ -13,12 +13,12 @@ batch_size = 100
learning_rate = 0.001 learning_rate = 0.001
# MNIST Dataset (Images and Labels) # MNIST Dataset (Images and Labels)
train_dataset = dsets.MNIST(root='../data', train_dataset = dsets.MNIST(root='./data',
train=True, train=True,
transform=transforms.ToTensor(), transform=transforms.ToTensor(),
download=True) download=True)
test_dataset = dsets.MNIST(root='../data', test_dataset = dsets.MNIST(root='./data',
train=False, train=False,
transform=transforms.ToTensor()) transform=transforms.ToTensor())

4
tutorials/03 - Feedforward Neural Network/main-gpu.py
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@ -14,12 +14,12 @@ batch_size = 100
learning_rate = 0.001 learning_rate = 0.001
# MNIST Dataset # MNIST Dataset
train_dataset = dsets.MNIST(root='../data', train_dataset = dsets.MNIST(root='./data',
train=True, train=True,
transform=transforms.ToTensor(), transform=transforms.ToTensor(),
download=True) download=True)
test_dataset = dsets.MNIST(root='../data', test_dataset = dsets.MNIST(root='./data',
train=False, train=False,
transform=transforms.ToTensor()) transform=transforms.ToTensor())

4
tutorials/03 - Feedforward Neural Network/main.py
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@ -14,12 +14,12 @@ batch_size = 100
learning_rate = 0.001 learning_rate = 0.001
# MNIST Dataset # MNIST Dataset
train_dataset = dsets.MNIST(root='../data', train_dataset = dsets.MNIST(root='./data',
train=True, train=True,
transform=transforms.ToTensor(), transform=transforms.ToTensor(),
download=True) download=True)
test_dataset = dsets.MNIST(root='../data', test_dataset = dsets.MNIST(root='./data',
train=False, train=False,
transform=transforms.ToTensor()) transform=transforms.ToTensor())

4
tutorials/04 - Convolutional Neural Network/main-gpu.py
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@ -11,12 +11,12 @@ batch_size = 100
learning_rate = 0.001 learning_rate = 0.001
# MNIST Dataset # MNIST Dataset
train_dataset = dsets.MNIST(root='../data/', train_dataset = dsets.MNIST(root='./data/',
train=True, train=True,
transform=transforms.ToTensor(), transform=transforms.ToTensor(),
download=True) download=True)
test_dataset = dsets.MNIST(root='../data/', test_dataset = dsets.MNIST(root='./data/',
train=False, train=False,
transform=transforms.ToTensor()) transform=transforms.ToTensor())

4
tutorials/04 - Convolutional Neural Network/main.py
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@ -11,12 +11,12 @@ batch_size = 100
learning_rate = 0.001 learning_rate = 0.001
# MNIST Dataset # MNIST Dataset
train_dataset = dsets.MNIST(root='../data/', train_dataset = dsets.MNIST(root='./data/',
train=True, train=True,
transform=transforms.ToTensor(), transform=transforms.ToTensor(),
download=True) download=True)
test_dataset = dsets.MNIST(root='../data/', test_dataset = dsets.MNIST(root='./data/',
train=False, train=False,
transform=transforms.ToTensor()) transform=transforms.ToTensor())

4
tutorials/05 - Deep Residual Network/main-gpu.py
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@ -16,12 +16,12 @@ transform = transforms.Compose([
transforms.ToTensor()]) transforms.ToTensor()])
# CIFAR-10 Dataset # CIFAR-10 Dataset
train_dataset = dsets.CIFAR10(root='../data/', train_dataset = dsets.CIFAR10(root='./data/',
train=True, train=True,
transform=transform, transform=transform,
download=True) download=True)
test_dataset = dsets.CIFAR10(root='../data/', test_dataset = dsets.CIFAR10(root='./data/',
train=False, train=False,
transform=transforms.ToTensor()) transform=transforms.ToTensor())

4
tutorials/05 - Deep Residual Network/main.py
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@ -16,12 +16,12 @@ transform = transforms.Compose([
transforms.ToTensor()]) transforms.ToTensor()])
# CIFAR-10 Dataset # CIFAR-10 Dataset
train_dataset = dsets.CIFAR10(root='../data/', train_dataset = dsets.CIFAR10(root='./data/',
train=True, train=True,
transform=transform, transform=transform,
download=True) download=True)
test_dataset = dsets.CIFAR10(root='../data/', test_dataset = dsets.CIFAR10(root='./data/',
train=False, train=False,
transform=transforms.ToTensor()) transform=transforms.ToTensor())

4
tutorials/06 - Recurrent Neural Network/main-gpu.py
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@ -16,12 +16,12 @@ num_epochs = 2
learning_rate = 0.01 learning_rate = 0.01
# MNIST Dataset # MNIST Dataset
train_dataset = dsets.MNIST(root='../data/', train_dataset = dsets.MNIST(root='./data/',
train=True, train=True,
transform=transforms.ToTensor(), transform=transforms.ToTensor(),
download=True) download=True)
test_dataset = dsets.MNIST(root='../data/', test_dataset = dsets.MNIST(root='./data/',
train=False, train=False,
transform=transforms.ToTensor()) transform=transforms.ToTensor())

4
tutorials/06 - Recurrent Neural Network/main.py
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@ -16,12 +16,12 @@ num_epochs = 2
learning_rate = 0.01 learning_rate = 0.01
# MNIST Dataset # MNIST Dataset
train_dataset = dsets.MNIST(root='../data/', train_dataset = dsets.MNIST(root='./data/',
train=True, train=True,
transform=transforms.ToTensor(), transform=transforms.ToTensor(),
download=True) download=True)
test_dataset = dsets.MNIST(root='../data/', test_dataset = dsets.MNIST(root='./data/',
train=False, train=False,
transform=transforms.ToTensor()) transform=transforms.ToTensor())

4
tutorials/07 - Bidirectional Recurrent Neural Network/main-gpu.py
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@ -16,12 +16,12 @@ num_epochs = 2
learning_rate = 0.003 learning_rate = 0.003
# MNIST Dataset # MNIST Dataset
train_dataset = dsets.MNIST(root='../data/', train_dataset = dsets.MNIST(root='./data/',
train=True, train=True,
transform=transforms.ToTensor(), transform=transforms.ToTensor(),
download=True) download=True)
test_dataset = dsets.MNIST(root='../data/', test_dataset = dsets.MNIST(root='./data/',
train=False, train=False,
transform=transforms.ToTensor()) transform=transforms.ToTensor())

4
tutorials/07 - Bidirectional Recurrent Neural Network/main.py
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@ -16,12 +16,12 @@ num_epochs = 2
learning_rate = 0.003 learning_rate = 0.003
# MNIST Dataset # MNIST Dataset
train_dataset = dsets.MNIST(root='../data/', train_dataset = dsets.MNIST(root='./data/',
train=True, train=True,
transform=transforms.ToTensor(), transform=transforms.ToTensor(),
download=True) download=True)
test_dataset = dsets.MNIST(root='../data/', test_dataset = dsets.MNIST(root='./data/',
train=False, train=False,
transform=transforms.ToTensor()) transform=transforms.ToTensor())