import math
def train_model(hp, model, train_loader, writer, logger):
model.net.train()
for input_, target in train_loader:
model.feed_data(input=input_, GT=target)
model.optimize_parameters()
loss = model.log.loss_v
model.step += 1
if logger is not None and (loss > 1e8 or math.isnan(loss)):
logger.error("Loss exploded to %.02f at step %d!" % (loss, model.step))
raise Exception("Loss exploded")
if model.step % hp.log.summary_interval == 0:
if writer is not None:
writer.logging_with_step(loss, model.step, "train_loss")
if logger is not None:
logger.info("Train Loss %.04f at step %d" % (loss, model.step))
