Method name_scope

tensorflow/python/framework/ops.py:4051–4161

Returns a context manager that creates hierarchical names for operations. A graph maintains a stack of name scopes. A `with name_scope(...):` statement pushes a new name onto the stack for the lifetime of the context. The `name` argument will be interpreted as follows: * A string

(self, name)

  # pylint: disable=g-doc-return-or-yield,line-too-long
  @tf_contextlib.contextmanager
  def name_scope(self, name):
    """Returns a context manager that creates hierarchical names for operations.

    A graph maintains a stack of name scopes. A `with name_scope(...):`
    statement pushes a new name onto the stack for the lifetime of the context.

    The `name` argument will be interpreted as follows:

    * A string (not ending with '/') will create a new name scope, in which
      `name` is appended to the prefix of all operations created in the
      context. If `name` has been used before, it will be made unique by
      calling `self.unique_name(name)`.
    * A scope previously captured from a `with g.name_scope(...) as
      scope:` statement will be treated as an "absolute" name scope, which
      makes it possible to re-enter existing scopes.
    * A value of `None` or the empty string will reset the current name scope
      to the top-level (empty) name scope.

    For example:

    ```python
    with tf.Graph().as_default() as g:
      c = tf.constant(5.0, name="c")
      assert c.op.name == "c"
      c_1 = tf.constant(6.0, name="c")
      assert c_1.op.name == "c_1"

      # Creates a scope called "nested"
      with g.name_scope("nested") as scope:
        nested_c = tf.constant(10.0, name="c")
        assert nested_c.op.name == "nested/c"

        # Creates a nested scope called "inner".
        with g.name_scope("inner"):
          nested_inner_c = tf.constant(20.0, name="c")
          assert nested_inner_c.op.name == "nested/inner/c"

        # Create a nested scope called "inner_1".
        with g.name_scope("inner"):
          nested_inner_1_c = tf.constant(30.0, name="c")
          assert nested_inner_1_c.op.name == "nested/inner_1/c"

          # Treats `scope` as an absolute name scope, and
          # switches to the "nested/" scope.
          with g.name_scope(scope):
            nested_d = tf.constant(40.0, name="d")
            assert nested_d.op.name == "nested/d"

            with g.name_scope(""):
              e = tf.constant(50.0, name="e")
              assert e.op.name == "e"
    ```

    The name of the scope itself can be captured by `with
    g.name_scope(...) as scope:`, which stores the name of the scope
    in the variable `scope`. This value can be used to name an
    operation that represents the overall result of executing the ops
    in a scope. For example: