torchvision_loader_exp.py

# --
# Helpers

def do_time(trainloader):
    t = time()
    
    for epoch in range(3):
        for _ in trainloader:
            pass
            
    return time() - t

# --
# Default

transform = torchvision.transforms.Compose([
   torchvision.transforms.ToTensor(),
])
     
trainset = original_MNIST(root='data', train=True, download=True, transform=None, pretensor=True)
trainloader = torch.utils.data.DataLoader(trainset, batch_size=128)

do_time(trainloader)
# 15.72680401802063

# --
# Preconvert to Image; Convert to Tensor on the fly

transform = torchvision.transforms.Compose([
   torchvision.transforms.ToTensor(),
])

trainset = new_MNIST(root='data', train=True, download=True, transform=transform)
trainloader = torch.utils.data.DataLoader(trainset, batch_size=128)

do_time(trainloader)
# 9.789423942565918

# --   
# Preconvert to Tensor

trainset = new_MNIST(root='data', train=True, download=True, pretensor=True)
trainloader = torch.utils.data.DataLoader(trainset, batch_size=128)

do_time(trainloader)
# 0.6025290489196777