I meet a problem to convert a python matrix of torch.tensor to a torch.tensor
For example, M is an (n,m) matrix, with each element M[i][j] is a torch.tensor with same size (p, q, r, ...). How to convert python list of list M to a torch.tensor with size (n,m,p,q,r,...)
e.g.
M = []
for i in range(5):
row = []
for j in range(10):
row.append(torch.rand(3,4))
M.append(row)
How to convert above M to a torch.tensor with size (5,10,3,4).
Try torch.stack() to stack a list of tensors on the first dimension.
import torch
M = []
for i in range(5):
row = []
for j in range(10):
row.append(torch.rand(3,4))
row = torch.stack(row)
M.append(row)
M = torch.stack(M)
print(M.size())
# torch.Size([5, 10, 3, 4])
Try this.
ref = np.arange(3*4*5).reshape(3,4,5) # numpy array
values = [ref.copy()+i for i in range(6)] # List of numpy arrays
b = torch.from_numpy(np.array(values)) # torch-array from List of numpy arrays
