# tf.linalg.qr

### Aliases:

• `tf.linalg.qr`
• `tf.qr`
``````tf.linalg.qr(
input,
full_matrices=False,
name=None
)
``````

Defined in generated file: `tensorflow/python/ops/gen_linalg_ops.py`.

See the guide: Math > Matrix Math Functions

Computes the QR decompositions of one or more matrices.

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

``````# 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)
``````

#### Args:

• `input`: A `Tensor`. Must be one of the following types: `float64`, `float32`, `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).

#### Returns:

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`.