self._iteration_pl = tf.placeholder( tf.int64, shape=None, name='iteration')

This line of code creates a placeholder in TensorFlow for an integer value of type int64 (64-bit integer). The placeholder is named 'iteration' and has no fixed shape, meaning it can accept input of any size.

Placeholders are used in TensorFlow to define the inputs to a computational graph. They allow the user to specify the type and shape of the input data, but defer actually supplying the data until later, when the graph is executed.

In this case, it appears that the placeholder is intended to be used to specify the current iteration number of some kind of training loop or optimization algorithm. The value of the placeholder will likely be updated at each iteration of the loop, and used to control the behavior of the graph.