tf.linalg.qr

Computes the QR decompositions of one or more matrices.

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.linalg.qr, tf.compat.v1.qr

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)

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.