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exp() preidction scores after logsoftmax

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htaustin
2017-03-27 22:48:35 -04:00
parent c0f34a687e
commit 46d913392b
1 changed files with 12 additions and 10 deletions
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sm-model/train.py
+12 -10
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@@ -131,23 +131,25 @@ class Trainer(object):
y = batch_labels[0]
pred = self.model(xq, xa, x_ext_feats)
pred = torch.exp(pred)
loss = self.criterion(pred, y)
total_loss += loss
total_correct += self.pred_equals_y(pred, y)
p_score, p_class = pred.max(1)
logger.debug('pred {}'.format(pred))
logger.debug('pred.max {} {}'.format(p_score, p_class))
logger.debug('score {}'.format(p_score.squeeze()))
logger.debug('score {}'.format(p_score.squeeze()[0]))
y_pred[ypc] = p_score.data.squeeze()[0]
# p_score, p_class = pred.max(1)
# logger.debug('pred {}'.format(pred))
# logger.debug('pred.max {} {}'.format(p_score, p_class))
# logger.debug('score {}'.format(p_score.squeeze()))
# logger.debug('score {}'.format(p_score.squeeze()[0]))
# y_pred[ypc] = p_score.data.squeeze()[0]
y_pred[ypc] = pred.data.squeeze()[1]
ypc += 1
logger.info('{}_correct {}'.format(set_folder, total_correct))
logger.info('{}_loss {}'.format(set_folder, total_loss.data[0]))
logger.info('{} total {}'.format(set_folder, len(labels)))
logger.info('{}_loss = {:.4f}, acc = {:.4f}'.format( set_folder, total_loss.data[0]/len(labels), float(total_correct)/len(labels) ))
# logger.info('{}_correct {}'.format(set_folder, total_correct))
# logger.info('{}_loss {}'.format(set_folder, total_loss.data[0]))
# logger.info('{} total {}'.format(set_folder, len(labels)))
# logger.info('{}_loss = {:.4f}, acc = {:.4f}'.format( set_folder, total_loss.data[0]/len(labels), float(total_correct)/len(labels) ))
return float(total_correct)/len(labels), y_pred