tf.linalg.matrix_rank

Compute the matrix rank of one or more matrices.

Compat aliases for migration

tf.compat.v1.linalg.matrix_rank

tf.linalg.matrix_rank(
    a, tol=None, validate_args=False, name=None
)

Args
`a`	(Batch of) `float`-like matrix-shaped `Tensor`(s) which are to be pseudo-inverted.
`tol`	Threshold below which the singular value is counted as 'zero'. Default value: `None` (i.e., `eps * max(rows, cols) * max(singular_val)`).
`validate_args`	When `True`, additional assertions might be embedded in the graph. Default value: `False` (i.e., no graph assertions are added).
`name`	Python `str` prefixed to ops created by this function. Default value: 'matrix_rank'.

Returns
`matrix_rank`	(Batch of) `int32` scalars representing the number of non-zero singular values.

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.

Last updated 2023-03-23 UTC.

Args