AntoineH/smart_augmentation
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F1 par classes + plot OK

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Harle, Antoine (Contracteur) 2020-02-03 11:21:54 -05:00
parent 3ccacd0366
commit fcd0217d54
5 changed files with 57 additions and 22 deletions
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6
higher/smart_aug/datasets.py
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@ -13,7 +13,7 @@ TEST_SIZE = BATCH_SIZE
#TEST_SIZE = 10000 #legerement +Rapide / + Consomation memoire !
#Wether to download data.
download_data=True
download_data=False
#Number of worker to use.
num_workers=2 #4
#Pin GPU memory
@ -46,7 +46,7 @@ transform_train = torchvision.transforms.Compose([
#data_test = torchvision.datasets.MNIST("../data", train=False, download=True, transform=transform)
#CIFAR
data_train = torchvision.datasets.CIFAR10("../data", train=True, download=download_data, transform=transform_train)
data_val = torchvision.datasets.CIFAR10("../data", train=True, download=download_data, transform=transform)
#data_val = torchvision.datasets.CIFAR10("../data", train=True, download=download_data, transform=transform)
data_test = torchvision.datasets.CIFAR10("../data", train=False, download=download_data, transform=transform)
train_subset_indices=range(int(len(data_train)/2))
@ -55,5 +55,5 @@ val_subset_indices=range(int(len(data_train)/2),len(data_train))
#val_subset_indices=range(BATCH_SIZE*10, BATCH_SIZE*20)
dl_train = torch.utils.data.DataLoader(data_train, batch_size=BATCH_SIZE, shuffle=False, sampler=SubsetRandomSampler(train_subset_indices), num_workers=num_workers, pin_memory=pin_memory)
dl_val = torch.utils.data.DataLoader(data_val, batch_size=BATCH_SIZE, shuffle=False, sampler=SubsetRandomSampler(val_subset_indices), num_workers=num_workers, pin_memory=pin_memory)
dl_val = torch.utils.data.DataLoader(data_train, batch_size=BATCH_SIZE, shuffle=False, sampler=SubsetRandomSampler(val_subset_indices), num_workers=num_workers, pin_memory=pin_memory)
dl_test = torch.utils.data.DataLoader(data_test, batch_size=TEST_SIZE, shuffle=False, num_workers=num_workers, pin_memory=pin_memory)