How can you re-use a variable scope in tensorflow without a new scope being created by default?

Question

I have created a variable scope in one part of my graph, and later in another part of the graph I want to add OPs to an existing scope. That equates to this distilled exampl

Answer 1

Answer mentioned by kmario23 is correct but there is a tricky case with variables created by tf.get_variable:

with tf.variable_scope('myscope'):
    print(tf.get_variable('var1', shape=[3]))

with tf.variable_scope('myscope/'):
    print(tf.get_variable('var2', shape=[3]))

This snippet will output:

It seems that tensorflow has not provided a formal way to handle this circumstance yet. The only possible method I found is to manually assign the correct name (Warning: The correctness is not guaranteed):

with tf.variable_scope('myscope'):
    print(tf.get_variable('var1', shape=[3]))

with tf.variable_scope('myscope/') as scope:
    scope._name = 'myscope'
    print(tf.get_variable('var2', shape=[3]))

And then we can get the correct names: