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+### `tf.variable_op_scope(values, name_or_scope, default_name=None, initializer=None, regularizer=None, caching_device=None, partitioner=None, reuse=None)` {#variable_op_scope}
+
+Returns a context manager for defining an op that creates variables.
+
+This context manager validates that the given `values` are from the
+same graph, ensures that graph is the default graph, and pushes a
+name scope and a variable scope.
+
+If `name_or_scope` is not None, it is used as is in the variable scope. If
+`scope` is None, then `default_name` is used.  In that case, if the same name
+has been previously used in the same scope, it will made unique be appending
+`_N` to it.
+
+This is intended to be used when defining generic ops and so reuse is always
+inherited.
+
+For example, to define a new Python op called `my_op_with_vars`:
+
+```python
+def my_op_with_vars(a, b, scope=None):
+  with tf.variable_op_scope([a, b], scope, "MyOp") as scope:
+    a = tf.convert_to_tensor(a, name="a")
+    b = tf.convert_to_tensor(b, name="b")
+    c = tf.get_variable('c')
+    # Define some computation that uses `a`, `b`, and `c`.
+    return foo_op(..., name=scope)
+```
+
+##### Args:
+
+
+*  <b>`values`</b>: The list of `Tensor` arguments that are passed to the op function.
+*  <b>`name_or_scope`</b>: The name argument that is passed to the op function,
+    this name_or_scope is not uniquified in the variable scope.
+*  <b>`default_name`</b>: The default name to use if the `name_or_scope` argument is
+    `None`, this name will be uniquified. If name_or_scope is provided it
+    won't be used and therefore it is not required and can be None.
+*  <b>`initializer`</b>: The default initializer to pass to variable scope.
+*  <b>`regularizer`</b>: The default regularizer for variables within this scope.
+*  <b>`caching_device`</b>: The default caching device for variables within this scope.
+*  <b>`partitioner`</b>: The default partitioner for variables within this scope.
+*  <b>`reuse`</b>: `True` or `None`; if `True`, we go into reuse mode for this scope as
+    well as all sub-scopes; if `None`, we just inherit the parent scope reuse.
+
+
+##### Returns:
+
+  A context manager for use in defining a Python op.
+
+##### Raises:
+
+
+*  <b>`ValueError`</b>: when trying to reuse within a create scope, or create within
+    a reuse scope, or if reuse is not `None` or `True`.
+*  <b>`TypeError`</b>: when the types of some arguments are not appropriate.
+