tf.linalg.lu(
input,
output_idx_type=tf.dtypes.int32,
name=None
)
Defined in generated file: tensorflow/python/ops/gen_linalg_ops.py.
Computes the LU decomposition of one or more square matrices.
The input is a tensor of shape [..., M, M] whose inner-most 2 dimensions
form square matrices.
The input has to be invertible.
The output consists of two tensors LU and P containing the LU decomposition
of all input submatrices [..., :, :]. LU encodes the lower triangular and
upper triangular factors.
For each input submatrix of shape [M, M], L is a lower triangular matrix of
shape [M, M] with unit diagonal whose entries correspond to the strictly lower
triangular part of LU. U is a upper triangular matrix of shape [M, M] whose
entries correspond to the upper triangular part, including the diagonal, of LU.
P represents a permutation matrix encoded as a list of indices each between 0
and M-1, inclusive. If P_mat denotes the permutation matrix corresponding to
P, then the L, U and P satisfies P_mat * input = L * U.
Args:
input: ATensor. Must be one of the following types:float64,float32,complex64,complex128. A tensor of shape[..., M, M]whose inner-most 2 dimensions form matrices of size[M, M].output_idx_type: An optionaltf.DTypefrom:tf.int32, tf.int64. Defaults totf.int32.name: A name for the operation (optional).
Returns:
A tuple of Tensor objects (lu, p).
lu: ATensor. Has the same type asinput.p: ATensorof typeoutput_idx_type.