a5bd6a5eb3b78fe02c34de7db53efe253e85ecb9,tensorly/decomposition/_tucker.py,,non_negative_tucker,#Any#Any#Any#Any#Any#Any#Any#,125

Before Change

    for iteration in range(n_iter_max):
        for mode in range(tensor.ndim):
            B = tucker_to_tensor(nn_core, nn_factors, skip_factor=mode)
            B = unfold(B, mode).T

            numerator = T.dot(unfold(tensor, mode), B)
            numerator = T.clip(numerator, a_min=epsilon, a_max=None)
            denominator = T.dot(nn_factors[mode], T.dot(B.T, B))
            denominator = T.clip(denominator, a_min=epsilon, a_max=None)
            nn_factors[mode] *= numerator / denominator

        numerator = tucker_to_tensor(tensor, nn_factors, transpose_factors=True)
        numerator = T.clip(numerator, a_min=epsilon, a_max=None)

After Change

    for iteration in range(n_iter_max):
        for mode in range(T.ndim(tensor)):
            B = tucker_to_tensor(nn_core, nn_factors, skip_factor=mode)
            B = T.transpose(unfold(B, mode))

            numerator = T.dot(unfold(tensor, mode), B)
            numerator = T.clip(numerator, a_min=epsilon, a_max=None)
            denominator = T.dot(nn_factors[mode], T.dot(T.transpose(B), B))
            denominator = T.clip(denominator, a_min=epsilon, a_max=None)
            nn_factors[mode] *= numerator / denominator

        numerator = tucker_to_tensor(tensor, nn_factors, transpose_factors=True)
        numerator = T.clip(numerator, a_min=epsilon, a_max=None)

Instances