add trainer.stop and fix a bug for train_by_parallel_executor

[jacquesqiao]

fix: #10754

[sidgoyal78]

Is this step for epoch? Or is it more like for iterations (different mini-batches across epochs)?
(Because we have epoch_id and step_id in the trainer code)

[jacquesqiao]

Paddle/python/paddle/fluid/trainer.py

Lines 289 to 302 in 54ae8e4

	for epoch_id in range(num_epochs):
	event_handler(BeginEpochEvent(epoch_id))
	for step_id, data in enumerate(reader()):
	begin_event = BeginStepEvent(epoch_id, step_id)
	event_handler(begin_event)
	if begin_event.fetch_metrics:
	metrics = exe.run(feed=data,
	fetch_list=[
	var.name
	for var in self.train_func_outputs
	])
	else:
	metrics = exe.run(feed=data, fetch_list=[])
	event_handler(EndStepEvent(epoch_id, step_id, metrics))

From the code we can see that step_id is independent for each epoch, but we can also get epoch id from EndStepEvent.epoch_id

[sidgoyal78]

Yeah, actually I was just confused about the naming. I was thinking that event.step should represent iterations. Probably, iterations should never counter back to 0. But in this case, we have event.step based on step_id.

However, the step_id is from 0 to number of mini-batches. And after each epoch the step_id is reset to 0.

So basically the point was that could be have a separate naming convention :)

[daming-lu]

So what is the reason of getting rid of the for loop? Just curious 😁

[jacquesqiao]

This is a bug, we will do iterate on num_epoches in _train_by_any_executor

Paddle/python/paddle/fluid/trainer.py

Lines 288 to 291 in 54ae8e4

	def _train_by_any_executor(self, event_handler, exe, num_epochs, reader):
	for epoch_id in range(num_epochs):
	event_handler(BeginEpochEvent(epoch_id))
	for step_id, data in enumerate(reader()):

[daming-lu]

👍