What is the purpose of tf.global_variables_initializer?

I would like to understand what tf.global_variables_initializer does in a bit more detail. A sparse description is given here:

> Returns an Op that initializes global variables.

But that doesn't really help me. I know that the op is necessary to initialize the graph, but what does that actually mean? Is this the step where the graph is complied?

A more complete description is given here.

Only after running tf.global_variables_initializer() in a session will your variables hold the values you told them to hold when you declare them (tf.Variable(tf.zeros(...)), tf.Variable(tf.random_normal(...)),...).

From the TF doc :

> Calling tf.Variable() adds several ops to the graph: > > * A variable op that holds the variable value. > * An initializer op that sets the variable to its initial value. This is actually a tf.assign op. > * The ops for the initial value, such as the zeros op for the biases variable in the example are also added to the graph.

And also:

> Variable initializers must be run explicitly before other ops in your > model can be run. The easiest way to do that is to add an op that runs > all the variable initializers, and run that op before using the model.