A context manager for use when defining a Python op.
tf.compat.v1.keras.backend.name_scope(
    name, default_name=None, values=None
)
  This context manager validates that the given values are from the same graph, makes that graph the default graph, and pushes a name scope in that graph (see tf.Graph.name_scope for more details on that).
For example, to define a new Python op called my_op:
def my_op(a, b, c, name=None):
  with tf.name_scope(name, "MyOp", [a, b, c]) as scope:
    a = tf.convert_to_tensor(a, name="a")
    b = tf.convert_to_tensor(b, name="b")
    c = tf.convert_to_tensor(c, name="c")
    # Define some computation that uses `a`, `b`, and `c`.
    return foo_op(..., name=scope)
  
| Args | |
|---|---|
| name | The name argument that is passed to the op function. | 
| default_name | The default name to use if the nameargument isNone. | 
| values | The list of Tensorarguments that are passed to the op function. | 
| Raises | |
|---|---|
| TypeError | if default_nameis passed in but not a string. | 
| Attributes | |
|---|---|
| name | |
__enter____enter__()
__exit__
__exit__(
    *exc_info
)
  
    © 2022 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
    https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/compat/v1/keras/backend/name_scope