tf.linalg.matrix_rank

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Compute the matrix rank of one or more matrices.

Aliases:

• 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.