def _data_loader(is_train, batch_size, trans):
return torch.utils.data.DataLoader(
datasets.CIFAR10(str(logger.get_data_path()),
train=is_train,
download=True,
transform=trans),
batch_size=batch_size, shuffle=True)
def _data_loader(is_train, batch_size):
return torch.utils.data.DataLoader(
datasets.MNIST(str(logger.get_data_path()),
train=is_train,
download=True,
transform=transforms.Compose([
transforms.ToTensor(),
transforms.Normalize(mean=[0.5], std=[0.5])
])),
batch_size=batch_size, shuffle=True, drop_last=True)
def _data_loader(is_train, batch_size, dl_args):
return torch.utils.data.DataLoader(
datasets.MNIST(str(logger.get_data_path()),
train=is_train,
download=True,
transform=transforms.Compose([
transforms.ToTensor(),
transforms.Normalize((0.1307,), (0.3081,))
])),
batch_size=batch_size, shuffle=True, **dl_args)