espnet.lm.chainer_backend.lm.LMEvaluator

source

class espnet.lm.chainer_backend.lm.LMEvaluator(val_iter, eval_model, device)

Bases: BaseEvaluator

A custom evaluator for a chainer LM

:param chainer.dataset.Iterator val_iter : The validation iterator :param eval_model : The model to evaluate :param int device : The device id to use

evaluate()

Evaluates the model and returns a result dictionary.

This method runs the evaluation loop over the validation dataset. It accumulates the reported values to DictSummary and returns a dictionary whose values are means computed by the summary.

Note that this function assumes that the main iterator raises StopIteration or code in the evaluation loop raises an exception. So, if this assumption is not held, the function could be caught in an infinite loop.

Users can override this method to customize the evaluation routine.

NOTE

This method encloses eval_func calls with function.no_backprop_mode() context, so all calculations using FunctionNodes inside eval_func do not make computational graphs. It is for reducing the memory consumption.

• Returns: Result dictionary. This dictionary is further reported via report() without specifying any observer.
• Return type: dict