Open Lihanyiyi opened 4 months ago
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Thank you for your advice!
On Tue, May 21, 2024 at 14:18 you-n-g @.***> wrote:
@.**** commented on this pull request.
In qlib/contrib/model/pytorch_alstm.py https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_microsoft_qlib_pull_1790-23discussion-5Fr1607702639&d=DwMFaQ&c=slrrB7dE8n7gBJbeO0g-IQ&r=Asg7UDKmphyKDarHgt07bA&m=yZtQD8t6HHI3IMa_JPBKEyrIDiHuxFHxIlU39LMX1_dh76y6UOyR24_2m6VacDdT&s=jNrM4GGN9G9XTXKJh7FGNHIv9id64CiiiEu9bg6w9jk&e= :
@@ -148,7 +148,7 @@ def loss_fn(self, pred, label): def metric_fn(self, pred, label): mask = torch.isfinite(label)
- if self.metric in ("", "loss"):
- if self.metric in ("", "loss","mse"): return -self.loss_fn(pred[mask], label[mask])
You should use mse instead of loss_fn to support extending more losses in the future.
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Description
Motivation and Context
How Has This Been Tested?
pytest qlib/tests/test_all_pipeline.py
under upper directory ofqlib
.Screenshots of Test Results (if appropriate):
Types of changes