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[..., :,:])
# 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 | |
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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 | |
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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 . |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/raw_ops/Qr