What does global_step mean in Tensorflow?

Question

In this is tutorial code from TensorFlow website,

1. could anyone help explain what does global_step mean?

   I found on the Tensorflow website written that global step is used count training steps, but I don't quite get what exactly it means.

2. Also, what does the number 0 mean when setting up global_step?

    def training(loss,learning_rate):         tf.summary.scalar('loss',loss)         optimizer = tf.train.GradientDescentOptimizer(learning_rate)                  # Why 0 as the first parameter of the global_step tf.Variable?         global_step = tf.Variable(0, name='global_step',trainable=False)          train_op = optimizer.minimize(loss, global_step=global_step)              return train_op 

According to Tensorflow doc global_step: increment by one after the variables have been updated. Does that mean after one update global_step becomes 1?

Answer 1

global_step refers to the number of batches seen by the graph. Every time a batch is provided, the weights are updated in the direction that minimizes the loss. global_step just keeps track of the number of batches seen so far. When it is passed in the minimize() argument list, the variable is increased by one. Have a look at optimizer.minimize().

You can get the global_step value using tf.train.global_step(). Also handy are the utility methods tf.train.get_global_step or tf.train.get_or_create_global_step.

0 is the initial value of the global step in this context.