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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 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.
Inside a 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 MyOp_1/a, etc.
Args | |
|---|---|
name | The prefix to use on all names created within the name scope. |
Raises | |
|---|---|
ValueError | If name is not a string. |
Attributes | |
|---|---|
name | |
Methods
__enter__
__enter__() Start the scope block.
| Returns | |
|---|---|
| The scope name. |
__exit__
__exit__( type_arg, value_arg, traceback_arg )
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