class_docstr: Base class for feature flag settings with global scope.
  The default is set via the `_default` class attribute.
class_docstr_tok: ["Base","class","for","feature","flag","settings","with","global","scope",".","The","default","is","set","via","the","`","_default","`","class","attribute","."]
code: def on(cls):
      if cls.is_default():
          return cls._default
      return cls._state
  
imports: import torch
  from linear_operator.settings import _linalg_dtype_cholesky, _linalg_dtype_symeig, cg_tolerance, cholesky_jitter, cholesky_max_tries, ciq_samples, deterministic_probes, fast_computations, linalg_dtypes, max_cg_iterations, max_cholesky_size, max_lanczos_quadrature_iterations, max_preconditioner_size, max_root_decomposition_size, min_preconditioning_size, minres_tolerance, num_contour_quadrature, num_trace_samples, preconditioner_tolerance, skip_logdet_forward, terminate_cg_by_size, tridiagonal_jitter, use_toeplitz, verbose_linalg
  from torch import Tensor
label_desc: Use image node_id 2 for calling the _feature_flag obj's underlying member method code with example usage: obj.on(cls) and returns: cls, cls