class_docstr: Context manager to automatically add control dependencies.
  
  Code under this context manager will act as if a sensible set of control
  dependencies were present. More specifically:
    1. All stateful ops in the scope will execute (with the exception of ops in
       ASYNC_STATEFUL_OPS and LEGACY_RANDOM_OPS)
    2. Stateful ops which modify the same resource will execute in program order
  
  Note: creating variables in an automatic control dependencies context is not
  supported (the value of the variables will never change as they will keep
  getting reinitialized).
  
  NOT THREAD SAFE
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docstr: Marks the given op as independent.
  
  Overrides any other rule for the op.
  
  Independent ops are guaranteed to execute before the return values, but
  are allowed to run in parallel with everything else. Use in programs which
  can guarantee that an op has side effects that don't affect any other op.
  
  Args:
    op: An operation
docstr_tok: ["Marks","the","given","op","as","independent",".","Overrides","any","other","rule","for","the","op",".","Independent","ops","are","guaranteed","to","execute","before","the","return","values",",","but","are","allowed","to","run","in","parallel","with","everything","else",".","Use","in","programs","which","can","guarantee","that","an","op","has","side","effects","that","do","n't","affect","any","other","op",".","Args",":","op",":","An","operation"]
code: def run_independently(self, op):
      """Marks the given op as independent.
  
      Overrides any other rule for the op.
  
      Independent ops are guaranteed to execute before the return values, but
      are allowed to run in parallel with everything else. Use in programs which
      can guarantee that an op has side effects that don't affect any other op.
  
      Args:
        op: An operation
      """
      self._independent_ops.append(op)
      op._set_attr(
          "_independent_side_effects", attr_value_pb2.AttrValue(b=True)
      )
  
imports: import collections
  import enum
  from tensorflow.core.framework import attr_value_pb2
  from tensorflow.python.eager import context
  from tensorflow.python.framework import auto_control_deps_utils
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import indexed_slices
  from tensorflow.python.framework import op_def_registry
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import registry
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import control_flow_util
  from tensorflow.python.ops import tensor_array_ops
  from tensorflow.python.util import nest
  from tensorflow.python.util import object_identity
  from tensorflow.python.util import tf_decorator
label_desc: Use image node_id 3 for calling the AutomaticControlDependencies obj's underlying member method code with example usage: obj.run_independently(op) without return types