View source on GitHub
|
A context manager for use when defining a Python op.
tf.name_scope(
name
)
This context manager pushes a name scope, which will make the name of all operations added within it have a prefix.
For example, to define a new Python op called my_op:
def my_op(a, b, c, name=None):
with tf.name_scope("MyOp") 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)
When executed, the Tensors a, b, c, will have names MyOp/a, MyOp/b,
and MyOp/c.
If the scope name already exists, the name will be made unique by appending
_n. For example, calling my_op the second time will generate MyOp_1/a,
etc.
name: The prefix to use on all names created within the name scope.nameValueError: If name is None, or not a string.__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
)