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. |
Attributes | |
---|---|
name |
__enter__
__enter__()
__exit__
__exit__( *exc_info )
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/compat/v1/keras/backend/name_scope