Computes the QR decompositions of one or more matrices.

tf.raw_ops.Qr( input, full_matrices=False, name=None )

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)

Args | |
---|---|

`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). |

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` . |

© 2020 The TensorFlow Authors. All rights reserved.

Licensed under the Creative Commons Attribution License 3.0.

Code samples licensed under the Apache 2.0 License.

https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/raw_ops/Qr