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fix some typo in doc/comments (#1389)

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* fix typo in docstrings

* fix typo

* fix typo

* fix black lint

* fix black lint
This commit is contained in:
YQ Tsui
2022-12-11 14:29:16 +08:00
committed by GitHub
parent 57f9813f85
commit 5e3924d7a6
6 changed files with 25 additions and 21 deletions
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22
qlib/contrib/model/pytorch_adarnn.py
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@@ -56,7 +56,7 @@ class ADARNN(Model):
n_splits=2,
GPU=0,
seed=None,
**kwargs
**_
):
# Set logger.
self.logger = get_module_logger("ADARNN")
@@ -81,7 +81,7 @@ class ADARNN(Model):
self.optimizer = optimizer.lower()
self.loss = loss
self.n_splits = n_splits
self.device = torch.device("cuda:%d" % (GPU) if torch.cuda.is_available() and GPU >= 0 else "cpu")
self.device = torch.device("cuda:%d" % GPU if torch.cuda.is_available() and GPU >= 0 else "cpu")
self.seed = seed
self.logger.info(
@@ -213,7 +213,8 @@ class ADARNN(Model):
weight_mat = self.transform_type(out_weight_list)
return weight_mat, None
def calc_all_metrics(self, pred):
@staticmethod
def calc_all_metrics(pred):
"""pred is a pandas dataframe that has two attributes: score (pred) and label (real)"""
res = {}
ic = pred.groupby(level="datetime").apply(lambda x: x.label.corr(x.score))
@@ -259,8 +260,6 @@ class ADARNN(Model):
save_path = get_or_create_path(save_path)
stop_steps = 0
best_score = -np.inf
best_epoch = 0
evals_result["train"] = []
evals_result["valid"] = []
@@ -400,7 +399,7 @@ class AdaRNN(nn.Module):
self.model_type = model_type
self.trans_loss = trans_loss
self.len_seq = len_seq
self.device = torch.device("cuda:%d" % (GPU) if torch.cuda.is_available() and GPU >= 0 else "cpu")
self.device = torch.device("cuda:%d" % GPU if torch.cuda.is_available() and GPU >= 0 else "cpu")
in_size = self.n_input
features = nn.ModuleList()
@@ -499,7 +498,8 @@ class AdaRNN(nn.Module):
res = self.softmax(weight).squeeze()
return res
def get_features(self, output_list):
@staticmethod
def get_features(output_list):
fea_list_src, fea_list_tar = [], []
for fea in output_list:
fea_list_src.append(fea[0 : fea.size(0) // 2])
@@ -561,7 +561,7 @@ class TransferLoss:
"""
self.loss_type = loss_type
self.input_dim = input_dim
self.device = torch.device("cuda:%d" % (GPU) if torch.cuda.is_available() and GPU >= 0 else "cpu")
self.device = torch.device("cuda:%d" % GPU if torch.cuda.is_available() and GPU >= 0 else "cpu")
def compute(self, X, Y):
"""Compute adaptation loss
@@ -676,7 +676,8 @@ class MMD_loss(nn.Module):
self.fix_sigma = None
self.kernel_type = kernel_type
def guassian_kernel(self, source, target, kernel_mul=2.0, kernel_num=5, fix_sigma=None):
@staticmethod
def guassian_kernel(source, target, kernel_mul=2.0, kernel_num=5, fix_sigma=None):
n_samples = int(source.size()[0]) + int(target.size()[0])
total = torch.cat([source, target], dim=0)
total0 = total.unsqueeze(0).expand(int(total.size(0)), int(total.size(0)), int(total.size(1)))
@@ -691,7 +692,8 @@ class MMD_loss(nn.Module):
kernel_val = [torch.exp(-L2_distance / bandwidth_temp) for bandwidth_temp in bandwidth_list]
return sum(kernel_val)
def linear_mmd(self, X, Y):
@staticmethod
def linear_mmd(X, Y):
delta = X.mean(axis=0) - Y.mean(axis=0)
loss = delta.dot(delta.T)
return loss