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import os
import time
import numpy as np
# Helper class that keeps track of training iterations
class IterationCounter():
def __init__(self, opt, dataset_size):
self.opt = opt
self.dataset_size = dataset_size
self.first_epoch = 1
self.total_epochs = opt.niter + opt.niter_decay
self.epoch_iter = 0 # iter number within each epoch
self.iter_record_path = os.path.join(self.opt.checkpoints_dir, self.opt.name, 'iter.txt')
if opt.isTrain and opt.continue_train:
try:
self.first_epoch, self.epoch_iter = np.loadtxt(
self.iter_record_path, delimiter=',', dtype=int)
print('Resuming from epoch %d at iteration %d' % (self.first_epoch, self.epoch_iter))
except:
print('Could not load iteration record at %s. Starting from beginning.' %
self.iter_record_path)
self.total_steps_so_far = (self.first_epoch - 1) * dataset_size + self.epoch_iter
# return the iterator of epochs for the training
def training_epochs(self):
return range(self.first_epoch, self.total_epochs + 1)
def record_epoch_start(self, epoch):
self.epoch_start_time = time.time()
self.epoch_iter = 0
self.last_iter_time = time.time()
self.current_epoch = epoch
def record_one_iteration(self):
current_time = time.time()
# the last remaining batch is dropped (see data/__init__.py),
# so we can assume batch size is always opt.batchSize
self.time_per_iter = (current_time - self.last_iter_time) / self.opt.batchSize
self.last_iter_time = current_time
self.total_steps_so_far += self.opt.batchSize
self.epoch_iter += self.opt.batchSize
def record_epoch_end(self):
current_time = time.time()
self.time_per_epoch = current_time - self.epoch_start_time
print('End of epoch %d / %d \t Time Taken: %d sec' %
(self.current_epoch, self.total_epochs, self.time_per_epoch))
if self.current_epoch % self.opt.save_epoch_freq == 0:
np.savetxt(self.iter_record_path, (self.current_epoch + 1, 0),
delimiter=',', fmt='%d')
print('Saved current iteration count at %s.' % self.iter_record_path)
def record_current_iter(self):
np.savetxt(self.iter_record_path, (self.current_epoch, self.epoch_iter),
delimiter=',', fmt='%d')
print('Saved current iteration count at %s.' % self.iter_record_path)
def needs_saving(self):
return (self.total_steps_so_far % self.opt.save_latest_freq) < self.opt.batchSize
def needs_printing(self):
return (self.total_steps_so_far % self.opt.print_freq) < self.opt.batchSize
def needs_displaying(self):
return (self.total_steps_so_far % self.opt.display_freq) < self.opt.batchSize
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