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fix: use semantic version comparison for PyTorch scheduler compatibility (#2094)

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Linlang
2026-01-21 15:09:34 +08:00
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parent 50c32ac15f
commit 4e0f5d5ec9
1 changed files with 2 additions and 1 deletions
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qlib/contrib/model/pytorch_nn.py
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@@ -10,6 +10,7 @@ import os
import gc
import numpy as np
import pandas as pd
from packaging import version
from typing import Callable, Optional, Text, Union
from sklearn.metrics import roc_auc_score, mean_squared_error
@@ -148,7 +149,7 @@ class DNNModelPytorch(Model):
if scheduler == "default":
# In torch version 2.7.0, the verbose parameter has been removed. Reference Link:
# https://github.com/pytorch/pytorch/pull/147301/files#diff-036a7470d5307f13c9a6a51c3a65dd014f00ca02f476c545488cd856bea9bcf2L1313
if str(torch.__version__).split("+", maxsplit=1)[0] <= "2.6.0":
if version.parse(str(torch.__version__).split("+", maxsplit=1)[0]) <= version.parse("2.6.0"):
# Reduce learning rate when loss has stopped decrease
self.scheduler = torch.optim.lr_scheduler.ReduceLROnPlateau( # pylint: disable=E1123
self.train_optimizer,