# tf.raw_ops.Qr

Computes the QR decompositions of one or more matrices.

Computes the QR decomposition of each inner matrix in `tensor` such that `tensor[..., :, :] = q[..., :, :] * r[..., :,:])`

Currently, the gradient for the QR decomposition is well-defined only when the first `P` columns of the inner matrix are linearly independent, where `P` is the minimum of `M` and `N`, the 2 inner-most dimmensions of `tensor`.

``````# a is a tensor.
# q is a tensor of orthonormal matrices.
# r is a tensor of upper triangular matrices.
q, r = qr(a)
q_full, r_full = qr(a, full_matrices=True)
``````

`input` A `Tensor`. Must be one of the following types: `float64`, `float32`, `half`, `complex64`, `complex128`. A tensor of shape `[..., M, N]` whose inner-most 2 dimensions form matrices of size `[M, N]`. Let `P` be the minimum of `M` and `N`.
`full_matrices` An optional `bool`. Defaults to `False`. If true, compute full-sized `q` and `r`. If false (the default), compute only the leading `P` columns of `q`.
`name` A name for the operation (optional).

A tuple of `Tensor` objects (q, r).
`q` A `Tensor`. Has the same type as `input`.
`r` A `Tensor`. Has the same type as `input`.

[{ "type": "thumb-down", "id": "missingTheInformationINeed", "label":"必要な情報がない" },{ "type": "thumb-down", "id": "tooComplicatedTooManySteps", "label":"複雑すぎる / 手順が多すぎる" },{ "type": "thumb-down", "id": "outOfDate", "label":"最新ではない" },{ "type": "thumb-down", "id": "samplesCodeIssue", "label":"Samples / code issue" },{ "type": "thumb-down", "id": "otherDown", "label":"その他" }]
[{ "type": "thumb-up", "id": "easyToUnderstand", "label":"わかりやすい" },{ "type": "thumb-up", "id": "solvedMyProblem", "label":"問題の解決に役立った" },{ "type": "thumb-up", "id": "otherUp", "label":"その他" }]