问题
I have the following pieces of code:
# Device configuration
device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
seed = 42
np.random.seed(seed)
torch.manual_seed(seed)
# split the dataset into validation and test sets
len_valid_set = int(0.1*len(dataset))
len_train_set = len(dataset) - len_valid_set
print("The length of Train set is {}".format(len_train_set))
print("The length of Test set is {}".format(len_valid_set))
train_dataset , valid_dataset, = torch.utils.data.random_split(dataset , [len_train_set, len_valid_set])
# shuffle and batch the datasets
train_loader = torch.utils.data.DataLoader(train_dataset, batch_size=8, shuffle=True, num_workers=4)
test_loader = torch.utils.data.DataLoader(valid_dataset, batch_size=8, shuffle=True, num_workers=4)
print("LOADERS",
len(dataloader),
len(train_loader),
len(test_loader))
The length of Train set is 720
The length of Test set is 80
LOADERS 267 90 10
mean = 0.0
std = 0.0
nb_samples = 0.0
for data in train_loader:
images, landmarks = data["image"], data["landmarks"]
batch_samples = images.size(0)
images_data = images.view(batch_samples, images.size(1), -1)
mean += images_data.mean(2).sum(0)
std += images_data.std(2).sum(0)
nb_samples += batch_samples
mean /= nb_samples
std /= nb_samples
And I get this error:
---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
<ipython-input-23-9e47ddfeff5e> in <module>
7
8 images_data = images.view(batch_samples, images.size(1), -1)
----> 9 mean += images_data.mean(2).sum(0)
10 std += images_data.std(2).sum(0)
11 nb_samples += batch_samples
RuntimeError: Can only calculate the mean of floating types. Got Byte instead.
The fixed code is taken from https://stackoverflow.com/a/64349380/2414957 it worked for dataloader but not train_loader
Also, these are the results of
print(type(images_data))
print(images_data)
We have:
<class 'torch.Tensor'>
tensor([[[74, 74, 74, ..., 63, 63, 63],
[73, 73, 73, ..., 61, 61, 61],
[75, 75, 75, ..., 61, 61, 61],
...,
[74, 74, 74, ..., 38, 38, 38],
[75, 75, 75, ..., 39, 39, 39],
[72, 72, 72, ..., 38, 38, 38]],
[[75, 75, 75, ..., 65, 65, 65],
[75, 75, 75, ..., 62, 62, 62],
[75, 75, 75, ..., 63, 63, 63],
...,
[71, 71, 71, ..., 39, 39, 39],
[74, 74, 74, ..., 38, 38, 38],
[73, 73, 73, ..., 37, 37, 37]],
[[72, 72, 72, ..., 62, 62, 62],
[74, 74, 74, ..., 63, 63, 63],
[75, 75, 75, ..., 61, 61, 61],
...,
[74, 74, 74, ..., 38, 38, 38],
[74, 74, 74, ..., 39, 39, 39],
[73, 73, 73, ..., 37, 37, 37]],
...,
[[75, 75, 75, ..., 63, 63, 63],
[73, 73, 73, ..., 63, 63, 63],
[74, 74, 74, ..., 62, 62, 62],
...,
[74, 74, 74, ..., 38, 38, 38],
[73, 73, 73, ..., 39, 39, 39],
[73, 73, 73, ..., 37, 37, 37]],
[[73, 73, 73, ..., 62, 62, 62],
[75, 75, 75, ..., 62, 62, 62],
[74, 74, 74, ..., 63, 63, 63],
...,
[73, 73, 73, ..., 39, 39, 39],
[74, 74, 74, ..., 38, 38, 38],
[74, 74, 74, ..., 38, 38, 38]],
[[74, 74, 74, ..., 62, 62, 62],
[74, 74, 74, ..., 63, 63, 63],
[74, 74, 74, ..., 62, 62, 62],
...,
[74, 74, 74, ..., 38, 38, 38],
[73, 73, 73, ..., 38, 38, 38],
[72, 72, 72, ..., 36, 36, 36]]], dtype=torch.uint8)
When I tried
images_data = images_data.float()
mean += images_data.mean(2).sum(0)
I didn't get a tensor for 3 values for mean and 3 values for std like I expected but got a very large tensor (each torch.Size([600]))
回答1:
As the error says, your images_data
is a ByteTensor, i.e. has dtype uint8
. Torch refuses to compute the mean of integers. You can convert the data to float
with:
(images_data * 1.0).mean(2)
Or
torch.Tensor.float(images_data).mean(2)
来源:https://stackoverflow.com/questions/64358283/runtimeerror-can-only-calculate-the-mean-of-floating-types-got-byte-instead-f