tf.name_scope

TensorFlow 1 version 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.

ValueError If name is None, or not a string.

name

Methods

__enter__

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__enter__()

Start the scope block.

Returns
The scope name.

Raises
ValueError if neither name nor default_name is provided but values are.

__exit__

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__exit__(
    type_arg, value_arg, traceback_arg
)