def train_iterations(self):
"""Train model for the 'self.epochs' number of batches."""
self.model.train()
pbar = ProgressBar(target=self.epochs, width=8)
iterator = InfiniteDataLoader(self.train_loader)
correct = 0
processed = 0
for iteration in range(self.epochs):
# Train a batch
data, target = iterator.get_batch()
loss = self.train_batch(data, target)
# Update Progress Bar
accuracy = 100 * self.train_correct / self.train_processed
pbar.update(iteration,
values=[('loss', round(loss, 2)),
('accuracy', round(accuracy, 2))])
# Update training history
self.update_training_history(loss, accuracy)
pbar.add(1,
values=[('loss', round(loss, 2)),
('accuracy', round(accuracy, 2))])
def train_iterations(self):
"""Train model for the 'self.epochs' number of batches."""
self.model.train()
pbar = ProgressBar(target=self.epochs, width=8)
iterator = InfiniteDataLoader(self.train_loader)
for iteration in range(self.epochs):
# Train a batch
loss = self.train_batch(iterator.get_batch())
# Update Progress Bar
pbar_values = self._get_pbar_values(loss)
pbar.update(iteration, values=pbar_values)
# Update training history
self.update_training_history(loss)
pbar.add(1, values=pbar_values)