class_docstr: Apply a series of mutators on our model, sequentially.
  
  This could be generalized to a DAG indicating the dependencies between mutators,
  but we don't have a use case for that yet.
class_docstr_tok: ["Apply","a","series","of","mutators","on","our","model",",","sequentially",".","This","could","be","generalized","to","a","DAG","indicating","the","dependencies","between","mutators",",","but","we","do","n't","have","a","use","case","for","that","yet","."]
docstr: Bind the model to a list of mutators.
  The model (as well as its successors) will be bounded to the mutators one by one.
  The model will be unbinded after the context.
  
  Examples
  --------
  >>> with mutator_list.bind_model(model):
  ...     mutator_list.freeze(samplers)
code: def bind_model(
      self, model: GraphModelSpace
  ) -> Iterator[MutatorSequence]:
      """Bind the model to a list of mutators.
      The model (as well as its successors) will be bounded to the mutators one by one.
      The model will be unbinded after the context.
  
      Examples
      --------
      >>> with mutator_list.bind_model(model):
      ...     mutator_list.freeze(samplers)
      """
      try:
          self.model = model
          yield self
      finally:
          self.model = None
  
imports: from __future__ import annotations
  from contextlib import contextmanager
  from typing import Any, Callable, Iterable, List, Optional, TYPE_CHECKING, Iterator
  from numpy.random import RandomState
  from nni.mutable import LabeledMutable, MutableList, MutableDict, Categorical, Mutable, SampleValidationError, Sample, SampleMissingError, label_scope, auto_label, frozen_context
  from .space import ModelStatus
label_desc: Use image node_id 2 for calling the MutatorSequence obj's underlying member method code with example usage: obj.bind_model(model) without return types