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fix fillna bug (#1914)

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* fix fillna bug

* fix flake8 error

* fix pylint error

* update ubuntu version for action

* fix pytest error

* fix pylint error

* fix black error

* fix pylint error

* add Fillna test

* fix black error

* add  instruments

* remove code
This commit is contained in:
Linlang
2025-04-25 11:18:09 +08:00
committed by GitHub
parent e7a1b5ea1f
commit 320bd65e19
7 changed files with 42 additions and 28 deletions
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41
qlib/contrib/model/pytorch_nn.py
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@@ -146,19 +146,34 @@ class DNNModelPytorch(Model):
raise NotImplementedError("optimizer {} is not supported!".format(optimizer))
if scheduler == "default":
# Reduce learning rate when loss has stopped decrease
self.scheduler = torch.optim.lr_scheduler.ReduceLROnPlateau(
self.train_optimizer,
mode="min",
factor=0.5,
patience=10,
verbose=True,
threshold=0.0001,
threshold_mode="rel",
cooldown=0,
min_lr=0.00001,
eps=1e-08,
)
# 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":
# Reduce learning rate when loss has stopped decrease
self.scheduler = torch.optim.lr_scheduler.ReduceLROnPlateau( # pylint: disable=E1123
self.train_optimizer,
mode="min",
factor=0.5,
patience=10,
verbose=True,
threshold=0.0001,
threshold_mode="rel",
cooldown=0,
min_lr=0.00001,
eps=1e-08,
)
else:
self.scheduler = torch.optim.lr_scheduler.ReduceLROnPlateau(
self.train_optimizer,
mode="min",
factor=0.5,
patience=10,
threshold=0.0001,
threshold_mode="rel",
cooldown=0,
min_lr=0.00001,
eps=1e-08,
)
elif scheduler is None:
self.scheduler = None
else: