name_scope
tf.keras.backend.name_scope
tf.name_scope
Defined in tensorflow/python/framework/ops.py.
See the guide: Building Graphs > Utility functions
A context manager for use when defining a Python op.
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)
name__init____init__(
name,
default_name=None,
values=None
)
Initialize the context manager.
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.__enter____enter__()
Start the scope block.
The scope name.
ValueError: if neither name nor default_name is provided but values are.__exit____exit__(
type_arg,
value_arg,
traceback_arg
)
© 2018 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/api_docs/python/tf/name_scope