Help protect the Great Barrier Reef with TensorFlow on Kaggle

tf.linalg.lu

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.

input A Tensor. Must be one of the following types: float64, float32, half, complex64, complex128. A tensor of shape [..., M, M] whose inner-most 2 dimensions form matrices of size [M, M].
output_idx_type An optional tf.DType from: tf.int32, tf.int64. Defaults to tf.int32.
name A name for the operation (optional).

A tuple of Tensor objects (lu, p).
lu A Tensor. Has the same type as input.
p A Tensor of type output_idx_type.

[{ "type": "thumb-down", "id": "missingTheInformationINeed", "label":"Missing the information I need" },{ "type": "thumb-down", "id": "tooComplicatedTooManySteps", "label":"Too complicated / too many steps" },{ "type": "thumb-down", "id": "outOfDate", "label":"Out of date" },{ "type": "thumb-down", "id": "samplesCodeIssue", "label":"Samples / code issue" },{ "type": "thumb-down", "id": "otherDown", "label":"Other" }]
[{ "type": "thumb-up", "id": "easyToUnderstand", "label":"Easy to understand" },{ "type": "thumb-up", "id": "solvedMyProblem", "label":"Solved my problem" },{ "type": "thumb-up", "id": "otherUp", "label":"Other" }]