class, value_range, time_range, optimizer=None)[source]

Trainer extension to change an optimizer attribute linearly.

This extension changes an optimizer attribute from the first value to the last value linearly within a specified duration. The typical use case is warming up of the momentum coefficient.

For example, suppose that this extension is called at every iteration, and value_range == (x, y) and time_range == (i, j). Then, this extension keeps the attribute to be x up to the i-th iteration, linearly shifts the value to y by the j-th iteration, and then keeps the value to be y after the j-th iteration.

This extension is also called before the training loop starts by default.

  • attr (str) – Name of the optimizer attribute to adjust.
  • value_range (tuple of float) – The first and the last values of the attribute.
  • time_range (tuple of ints) – The first and last counts of calls in which the attribute is adjusted.
  • optimizer (Optimizer) – Target optimizer object. If it is None, the main optimizer of the trainer is used.



Finalizes the extension.

This method is called at the end of the training loop.




Default name of the extension.

It is the name of the class by default. Implementation can override this property, or provide a class attribute to hide it.

priority = 100
trigger = (1, 'iteration')