tf.linalg.matrix_rank

Compute the matrix rank of one or more matrices.

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.linalg.matrix_rank, `tf.compat.v2.linalg.matrix_rank`

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

Arguments
`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.

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Last updated 2020-10-01 UTC.

Arguments