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__
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__enter__()
__exit__
View source
__exit__(
*exc_info
)
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