https://github.com/tensorly/tensorly
Tip revision: c729db708aa5d9f6126114b5c6443ac410c111bf authored by Jean Kossaifi on 01 May 2018, 10:58:45 UTC
Add nose as a dependency
Add nose as a dependency
Tip revision: c729db7
test_tucker_tensor.py
import numpy as np
from .. import backend as T
from ..base import unfold, tensor_to_vec
from ..tucker_tensor import tucker_to_tensor, tucker_to_unfolded, tucker_to_vec
from ..tenalg import kronecker
def test_tucker_to_tensor():
"""Test for tucker_to_tensor"""
X = T.tensor([[[1, 13],
[4, 16],
[7, 19],
[10, 22]],
[[2, 14],
[5, 17],
[8, 20],
[11, 23]],
[[3, 15],
[6, 18],
[9, 21],
[12, 24]]])
ranks = [2, 3, 4]
U = [T.tensor(np.arange(R * s).reshape((R, s))) for (R, s) in zip(ranks, T.shape(X))]
true_res = np.array([[[390, 1518, 2646, 3774],
[1310, 4966, 8622, 12278],
[2230, 8414, 14598, 20782]],
[[1524, 5892, 10260, 14628],
[5108, 19204, 33300, 47396],
[8692, 32516, 56340, 80164]]])
res = tucker_to_tensor(X, U)
T.assert_array_equal(true_res, res)
def test_tucker_to_unfolded():
"""Test for tucker_to_unfolded
Notes
-----
Assumes that tucker_to_tensor is properly tested
"""
G = T.tensor(np.random.random((4, 3, 5, 2)))
ranks = [2, 2, 3, 4]
U = [T.tensor(np.random.random((ranks[i], G.shape[i]))) for i in range(T.ndim(G))]
full_tensor = tucker_to_tensor(G, U)
for mode in range(T.ndim(G)):
T.assert_array_almost_equal(tucker_to_unfolded(G, U, mode), unfold(full_tensor, mode))
T.assert_array_almost_equal(tucker_to_unfolded(G, U, mode),
T.dot(T.dot(U[mode], unfold(G, mode)), T.transpose(kronecker(U, skip_matrix=mode))),
decimal=5)
def test_tucker_to_vec():
"""Test for tucker_to_vec
Notes
-----
Assumes that tucker_to_tensor works correctly
"""
G = T.tensor(np.random.random((4, 3, 5, 2)))
ranks = [2, 2, 3, 4]
U = [T.tensor(np.random.random((ranks[i], G.shape[i]))) for i in range(T.ndim(G))]
vec = tensor_to_vec(tucker_to_tensor(G, U))
T.assert_array_almost_equal(tucker_to_vec(G, U), vec)
T.assert_array_almost_equal(tucker_to_vec(G, U), T.dot(kronecker(U), tensor_to_vec(G)), decimal=5)