bar.draw(value=data.get_count())
t = time.time() - now
acc, loss = net.get_record()
loss_avg = np.array(loss).mean()
loss_diff = loss_avg - loss_cache
loss_cache = loss_avg
print 'Acc: ', np.array(acc).mean()
print 'Loss: ', loss_avg
print 'Time: ', t
f, b = net.get_profile()
net.clear_record()
bar_t = Bar(max_value=nt)
bar_t.cursor.clear_lines(2) # Make some room
bar_t.cursor.save() # Mark starting line
for _ in xrange(data.batch_run_test()):
net.input(data.next_batch_test())
net.forward()
bar_t.cursor.restore() # Return cursor to start
bar_t.draw(value=data.get_count_test())
acc, loss = net.get_record()
print 'Val: ', np.array(acc).mean()
print 'Loss: ', np.array(loss).mean()
net.clear_record()
lr *= gamma
print lr, loss_diff
print
# Profile
print 'Forward Time: ', sum(f)
print f
