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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
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
c, will have names
tf.function, 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
| ||The prefix to use on all names created within the name scope.|
| ||If name is not a string.|
Start the scope block.
|The scope name.|
__exit__( type_arg, value_arg, traceback_arg )
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.