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Fix GPU

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Jactus
2020-12-02 13:25:29 +08:00
parent d109d3d44e
commit 7f385345bb
5 changed files with 37 additions and 112 deletions
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29
qlib/contrib/model/pytorch_lstm.py
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@@ -76,7 +76,7 @@ class LSTM(Model):
self.early_stop = early_stop
self.optimizer = optimizer.lower()
self.loss = loss
self.visible_GPU = GPU
self.device = "cuda:%d" % (GPU) if torch.cuda.is_available() else "cpu"
self.use_gpu = torch.cuda.is_available()
self.seed = seed
@@ -131,11 +131,7 @@ class LSTM(Model):
raise NotImplementedError("optimizer {} is not supported!".format(optimizer))
self._fitted = False
if self.use_gpu:
self.lstm_model.cuda()
# set the visible GPU
if self.visible_GPU:
os.environ["CUDA_VISIBLE_DEVICES"] = str(self.visible_GPU)
self.lstm_model.to(self.device)
def mse(self, pred, label):
loss = (pred - label) ** 2
@@ -173,12 +169,8 @@ class LSTM(Model):
if len(indices) - i < self.batch_size:
break
feature = torch.from_numpy(x_train_values[indices[i : i + self.batch_size]]).float()
label = torch.from_numpy(y_train_values[indices[i : i + self.batch_size]]).float()
if self.use_gpu:
feature = feature.cuda()
label = label.cuda()
feature = torch.from_numpy(x_train_values[indices[i : i + self.batch_size]]).float().to(self.device)
label = torch.from_numpy(y_train_values[indices[i : i + self.batch_size]]).float().to(self.device)
pred = self.lstm_model(feature)
loss = self.loss_fn(pred, label)
@@ -206,12 +198,8 @@ class LSTM(Model):
if len(indices) - i < self.batch_size:
break
feature = torch.from_numpy(x_values[indices[i : i + self.batch_size]]).float()
label = torch.from_numpy(y_values[indices[i : i + self.batch_size]]).float()
if self.use_gpu:
feature = feature.cuda()
label = label.cuda()
feature = torch.from_numpy(x_values[indices[i : i + self.batch_size]]).float().to(self.device)
label = torch.from_numpy(y_values[indices[i : i + self.batch_size]]).float().to(self.device)
pred = self.lstm_model(feature)
loss = self.loss_fn(pred, label)
@@ -299,10 +287,7 @@ class LSTM(Model):
else:
end = begin + self.batch_size
x_batch = torch.from_numpy(x_values[begin:end]).float()
if self.use_gpu:
x_batch = x_batch.cuda()
x_batch = torch.from_numpy(x_values[begin:end]).float().to(self.device)
with torch.no_grad():
if self.use_gpu: