SVDecomposition
- class trainsum.svdecomposition.SVDecomposition(*, max_rank=50, cutoff=0.0)
Singular value decomposition. The number of singular values to keep is determined by max_rank and cutoff. All singular values below cutoff are discarded, and at most max_rank singular values are kept.
- Parameters:
max_rank (int)
cutoff (float)
- right(mat)
Calculate \(U \Sigma V^H\) and return \(U \Sigma\) and \(V^H\).
- Parameters:
mat (T)
- Return type:
- left(mat)
Calculate \(U \Sigma V^H\) and return \(U\) and \(\Sigma V^H\).
- Parameters:
mat (T)
- Return type:
- left_shape(shape)
Calculate the shape of the left function.
- Parameters:
shape (tuple[int, int])
- Return type:
tuple[tuple[int, int], tuple[int, int]]
- right_shape(shape)
Calculate the shape of the right function.
- Parameters:
shape (tuple[int, int])
- Return type:
tuple[tuple[int, int], tuple[int, int]]