Basic tensor operations
Example on how to use tensorly.base to perform basic tensor operations.
import matplotlib.pyplot as plt
from tensorly.base import unfold, fold
import numpy as np
import tensorly.backend as T
A tensor is simply a numpy array
tensor = T.tensor(np.arange(24).reshape((3, 4, 2)))
print('* original tensor:\n{}'.format(tensor))
Out:
* original tensor:
[[[ 0 1]
[ 2 3]
[ 4 5]
[ 6 7]]
[[ 8 9]
[10 11]
[12 13]
[14 15]]
[[16 17]
[18 19]
[20 21]
[22 23]]]
Unfolding a tensor is easy
for mode in range(tensor.ndim):
print('* mode-{} unfolding:\n{}'.format(mode, unfold(tensor, mode)))
Out:
* mode-0 unfolding:
[[ 0 1 2 3 4 5 6 7]
[ 8 9 10 11 12 13 14 15]
[16 17 18 19 20 21 22 23]]
* mode-1 unfolding:
[[ 0 1 8 9 16 17]
[ 2 3 10 11 18 19]
[ 4 5 12 13 20 21]
[ 6 7 14 15 22 23]]
* mode-2 unfolding:
[[ 0 2 4 6 8 10 12 14 16 18 20 22]
[ 1 3 5 7 9 11 13 15 17 19 21 23]]
Re-folding the tensor is as easy:
for mode in range(tensor.ndim):
unfolding = unfold(tensor, mode)
folded = fold(unfolding, mode, tensor.shape)
T.assert_array_equal(folded, tensor)
Total running time of the script: ( 0 minutes 0.003 seconds)