tltorch
.FactorizedTensor¶

class
tltorch.
FactorizedTensor
(*args, **kwargs)[source]¶ Tensor Factorization
Important
All tensor factorization must have an order parameter
Methods
dim
()Order of the tensor
forward
([indices])To use a tensor factorization within a network, use
tensor.forward
, or, equivalently,tensor()
from_tensor
(tensor, shape, rank[, factorization])Create a factorized tensor by decomposing a full tensor
new
(shape, rank[, factorization])Main way to create a factorized tensor
normal_
([mean, std])Inialize the factors of the factorization such that the reconstruction follows a Gaussian distribution
size
([index])shape of the tensor
Reconstruct the full tensor from its factorized form

classmethod
new
(shape, rank, factorization='CP', **kwargs)[source]¶ Main way to create a factorized tensor
 Parameters
 shapetuple[int]
shape of the factorized tensor to create
 rankint, ‘same’ or float
rank of the decomposition
 factorization{‘CP’, ‘TT’, ‘Tucker’}, optional
Tensor factorization to use to decompose the tensor, by default ‘CP’
 Returns
 TensorFactorization
Tensor in Factorized form.
 Raises
 ValueError
If the factorization given does not exist.

classmethod
from_tensor
(tensor, shape, rank, factorization='CP', **kwargs)[source]¶ Create a factorized tensor by decomposing a full tensor
 Parameters
 tensortorch.tensor
tensor to factorize
 shapetuple[int]
shape of the factorized tensor to create
 rankint, ‘same’ or float
rank of the decomposition
 factorization{‘CP’, ‘TT’, ‘Tucker’}, optional
Tensor factorization to use to decompose the tensor, by default ‘CP’
 Returns
 TensorFactorization
Tensor in Factorized form.
 Raises
 ValueError
If the factorization given does not exist.

forward
(indices=None, **kwargs)[source]¶ To use a tensor factorization within a network, use
tensor.forward
, or, equivalently,tensor()
 Parameters
 indicesint or tuple[int], optional
use to index the tensor during the forward pass, by default None
 Returns
 TensorFactorization
tensor[indices]

size
(index=None)[source]¶ shape of the tensor
 Parameters
 indexint, or tuple, default is None
if not None, returns tensor.shape[index]
See also
shape

normal_
(mean=0, std=1)[source]¶ Inialize the factors of the factorization such that the reconstruction follows a Gaussian distribution
 Parameters
 meanfloat, currently only 0 is supported
 stdfloat
standard deviation
 Returns
 self

property
name
¶ Factorization name (‘tucker’, ‘tt’, ‘cp’, …)

classmethod