I have 2 numpy arrays, which I convert into tensors to use the TensorDataset object.
import torch.utils.data as data_utils
X = np.zeros((100,30))
Y = np.zeros
Your numpy
arrays are 64-bit floating point
and will be converted to torch.DoubleTensor
standardly. Now, if you use them with your model, you'll need to make sure that your model parameters are also Double
. Or you need to make sure, that your numpy
arrays are cast as Float
, because model parameters are standardly cast as float
.
Hence, do either of the following:
data_utils.TensorDataset(torch.from_numpy(X).float(), torch.from_numpy(Y).float())
or do:
model.double()
Depeding, if you want to cast your model parameters, inputs and targets as Float
or as Double
.