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Follow PyTorch Guide of updating Learning Rate #1101

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Follow PyTorch Guide of updating Learning Rate #1101

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8 changes: 7 additions & 1 deletion train.py
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Expand Up @@ -40,7 +40,13 @@
iter_data_time = time.time() # timer for data loading per iteration
epoch_iter = 0 # the number of training iterations in current epoch, reset to 0 every epoch
visualizer.reset() # reset the visualizer: make sure it saves the results to HTML at least once every epoch
model.update_learning_rate() # update learning rates in the beginning of every epoch.

# update learning rates in the beginning of every epoch.
if epoch != opt.epoch_count:
model.update_learning_rate()
else:
print('learning rate %.7f' % model.optimizers[0].param_groups[0]['lr'])

for i, data in enumerate(dataset): # inner loop within one epoch
iter_start_time = time.time() # timer for computation per iteration
if total_iters % opt.print_freq == 0:
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