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Add torch.no_grad for evaluation

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D-X-Y
2021-03-12 02:46:04 +00:00
parent 67fbdafe76
commit db59713d36
5 changed files with 35 additions and 37 deletions
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16
qlib/contrib/model/pytorch_alstm.py
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@@ -208,12 +208,13 @@ class ALSTM(Model):
feature = torch.from_numpy(x_values[indices[i : i + self.batch_size]]).float().to(self.device)
label = torch.from_numpy(y_values[indices[i : i + self.batch_size]]).float().to(self.device)
pred = self.ALSTM_model(feature)
loss = self.loss_fn(pred, label)
losses.append(loss.item())
with torch.no_grad():
pred = self.ALSTM_model(feature)
loss = self.loss_fn(pred, label)
losses.append(loss.item())
score = self.metric_fn(pred, label)
scores.append(score.item())
score = self.metric_fn(pred, label)
scores.append(score.item())
return np.mean(losses), np.mean(scores)
@@ -295,10 +296,7 @@ class ALSTM(Model):
x_batch = torch.from_numpy(x_values[begin:end]).float().to(self.device)
with torch.no_grad():
if self.use_gpu:
pred = self.ALSTM_model(x_batch).detach().cpu().numpy()
else:
pred = self.ALSTM_model(x_batch).detach().numpy()
pred = self.ALSTM_model(x_batch).detach().cpu().numpy()
preds.append(pred)