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 name argument is None.
 | 
values
 | 
The list of Tensor arguments that are passed to the op function.
 | 
Raises | 
TypeError
 | 
if default_name is passed in but not a string.
 | 
Methods
__enter__
View source
__enter__()
__exit__
View source
__exit__(
    *exc_info
)