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fix_pylint_for_CI (#1119)

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* fix_pylint_for_CI

* reformat_with_black

* fix_pylint_C3001

* fix_flake8_error
This commit is contained in:
Linlang
2022-06-09 16:12:33 +08:00
committed by GitHub
parent 1a4114b683
commit 1ef8e61abd
11 changed files with 40 additions and 15 deletions
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5
qlib/contrib/model/highfreq_gdbt_model.py
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@@ -92,7 +92,10 @@ class HFLGBModel(ModelFT, LightGBMFInt):
# Convert label into alpha
df_train["label"][l_name] = df_train["label"][l_name] - df_train["label"][l_name].mean(level=0)
df_valid["label"][l_name] = df_valid["label"][l_name] - df_valid["label"][l_name].mean(level=0)
mapping_fn = lambda x: 0 if x < 0 else 1
def mapping_fn(x):
return 0 if x < 0 else 1
df_train["label_c"] = df_train["label"][l_name].apply(mapping_fn)
df_valid["label_c"] = df_valid["label"][l_name].apply(mapping_fn)
x_train, y_train = df_train["feature"], df_train["label_c"].values

4
qlib/contrib/model/pytorch_hist.py
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@@ -292,7 +292,9 @@ class HIST(Model):
pretrained_model.load_state_dict(torch.load(self.model_path))
model_dict = self.HIST_model.state_dict()
pretrained_dict = {k: v for k, v in pretrained_model.state_dict().items() if k in model_dict}
pretrained_dict = {
k: v for k, v in pretrained_model.state_dict().items() if k in model_dict # pylint: disable=E1135
}
model_dict.update(pretrained_dict)
self.HIST_model.load_state_dict(model_dict)
self.logger.info("Loading pretrained model Done...")

4
qlib/contrib/model/pytorch_tra.py
View File

@@ -167,8 +167,8 @@ class TRAModel(Model):
for param in self.tra.predictors.parameters():
param.requires_grad_(False)
self.logger.info("# model params: %d" % sum([p.numel() for p in self.model.parameters() if p.requires_grad]))
self.logger.info("# tra params: %d" % sum([p.numel() for p in self.tra.parameters() if p.requires_grad]))
self.logger.info("# model params: %d" % sum(p.numel() for p in self.model.parameters() if p.requires_grad))
self.logger.info("# tra params: %d" % sum(p.numel() for p in self.tra.parameters() if p.requires_grad))
self.optimizer = optim.Adam(list(self.model.parameters()) + list(self.tra.parameters()), lr=self.lr)