Missed TensorFlow World? Check out the recap. Learn more

tfp.math.matrix_rank

Compute the matrix rank; the number of non-zero SVD singular values. (deprecated)

tfp.math.matrix_rank(
    *args,
    **kwargs
)

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.