class_docstr: Wrap estimator which will not expose `sample_weight`.
  
  Parameters
  ----------
  est : estimator, default=None
      The estimator to wrap.
code: def __init__(self, est=None):
      self.est = est
  
imports: import numpy
  from ..base import BaseEstimator, ClassifierMixin
  from ..utils._metadata_requests import RequestMethod
  from .metaestimators import available_if
  from .validation import _check_sample_weight, _num_samples, check_array, check_is_fitted
label_desc: Use image node_id 1 to create a new NoSampleWeightWrapper object from inherited base classes: BaseEstimator with example: obj = NoSampleWeightWrapper(est)