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Add return for use_gpu..

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D-X-Y
2021-03-11 19:28:00 -08:00
parent 593553f573
commit 1d435248e2
11 changed files with 31 additions and 28 deletions
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6
qlib/contrib/model/pytorch_alstm.py
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@@ -93,7 +93,7 @@ class ALSTM(Model):
"\nearly_stop : {}" "\nearly_stop : {}"
"\noptimizer : {}" "\noptimizer : {}"
"\nloss_type : {}" "\nloss_type : {}"
"\nvisible_GPU : {}" "\ndevice : {}"
"\nuse_GPU : {}" "\nuse_GPU : {}"
"\nseed : {}".format( "\nseed : {}".format(
d_feat, d_feat,
@@ -107,7 +107,7 @@ class ALSTM(Model):
early_stop, early_stop,
optimizer.lower(), optimizer.lower(),
loss, loss,
GPU, self.device,
self.use_gpu, self.use_gpu,
seed, seed,
) )
@@ -138,7 +138,7 @@ class ALSTM(Model):
@property @property
def use_gpu(self): def use_gpu(self):
self.device != torch.device("cpu") return self.device != torch.device("cpu")
def mse(self, pred, label): def mse(self, pred, label):
loss = (pred - label) ** 2 loss = (pred - label) ** 2

6
qlib/contrib/model/pytorch_alstm_ts.py
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@@ -96,7 +96,7 @@ class ALSTM(Model):
"\nearly_stop : {}" "\nearly_stop : {}"
"\noptimizer : {}" "\noptimizer : {}"
"\nloss_type : {}" "\nloss_type : {}"
"\nvisible_GPU : {}" "\ndevice : {}"
"\nn_jobs : {}" "\nn_jobs : {}"
"\nuse_GPU : {}" "\nuse_GPU : {}"
"\nseed : {}".format( "\nseed : {}".format(
@@ -111,7 +111,7 @@ class ALSTM(Model):
early_stop, early_stop,
optimizer.lower(), optimizer.lower(),
loss, loss,
GPU, self.device,
n_jobs, n_jobs,
self.use_gpu, self.use_gpu,
seed, seed,
@@ -143,7 +143,7 @@ class ALSTM(Model):
@property @property
def use_gpu(self): def use_gpu(self):
self.device != torch.device("cpu") return self.device != torch.device("cpu")
def mse(self, pred, label): def mse(self, pred, label):
loss = (pred - label) ** 2 loss = (pred - label) ** 2

6
qlib/contrib/model/pytorch_gats.py
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@@ -103,7 +103,7 @@ class GATs(Model):
"\nbase_model : {}" "\nbase_model : {}"
"\nwith_pretrain : {}" "\nwith_pretrain : {}"
"\nmodel_path : {}" "\nmodel_path : {}"
"\nvisible_GPU : {}" "\ndevice : {}"
"\nuse_GPU : {}" "\nuse_GPU : {}"
"\nseed : {}".format( "\nseed : {}".format(
d_feat, d_feat,
@@ -119,7 +119,7 @@ class GATs(Model):
base_model, base_model,
with_pretrain, with_pretrain,
model_path, model_path,
GPU, self.device,
self.use_gpu, self.use_gpu,
seed, seed,
) )
@@ -151,7 +151,7 @@ class GATs(Model):
@property @property
def use_gpu(self): def use_gpu(self):
self.device != torch.device("cpu") return self.device != torch.device("cpu")
def mse(self, pred, label): def mse(self, pred, label):
loss = (pred - label) ** 2 loss = (pred - label) ** 2

2
qlib/contrib/model/pytorch_gats_ts.py
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@@ -172,7 +172,7 @@ class GATs(Model):
@property @property
def use_gpu(self): def use_gpu(self):
self.device != torch.device("cpu") return self.device != torch.device("cpu")
def mse(self, pred, label): def mse(self, pred, label):
loss = (pred - label) ** 2 loss = (pred - label) ** 2

2
qlib/contrib/model/pytorch_gru.py
View File

@@ -138,7 +138,7 @@ class GRU(Model):
@property @property
def use_gpu(self): def use_gpu(self):
self.device != torch.device("cpu") return self.device != torch.device("cpu")
def mse(self, pred, label): def mse(self, pred, label):
loss = (pred - label) ** 2 loss = (pred - label) ** 2

6
qlib/contrib/model/pytorch_gru_ts.py
View File

@@ -96,7 +96,7 @@ class GRU(Model):
"\nearly_stop : {}" "\nearly_stop : {}"
"\noptimizer : {}" "\noptimizer : {}"
"\nloss_type : {}" "\nloss_type : {}"
"\nvisible_GPU : {}" "\ndevice : {}"
"\nn_jobs : {}" "\nn_jobs : {}"
"\nuse_GPU : {}" "\nuse_GPU : {}"
"\nseed : {}".format( "\nseed : {}".format(
@@ -111,7 +111,7 @@ class GRU(Model):
early_stop, early_stop,
optimizer.lower(), optimizer.lower(),
loss, loss,
GPU, self.device,
n_jobs, n_jobs,
self.use_gpu, self.use_gpu,
seed, seed,
@@ -143,7 +143,7 @@ class GRU(Model):
@property @property
def use_gpu(self): def use_gpu(self):
self.device != torch.device("cpu") return self.device != torch.device("cpu")
def mse(self, pred, label): def mse(self, pred, label):
loss = (pred - label) ** 2 loss = (pred - label) ** 2

2
qlib/contrib/model/pytorch_lstm.py
View File

@@ -134,7 +134,7 @@ class LSTM(Model):
@property @property
def use_gpu(self): def use_gpu(self):
self.device != torch.device("cpu") return self.device != torch.device("cpu")
def mse(self, pred, label): def mse(self, pred, label):
loss = (pred - label) ** 2 loss = (pred - label) ** 2

6
qlib/contrib/model/pytorch_lstm_ts.py
View File

@@ -95,7 +95,7 @@ class LSTM(Model):
"\nearly_stop : {}" "\nearly_stop : {}"
"\noptimizer : {}" "\noptimizer : {}"
"\nloss_type : {}" "\nloss_type : {}"
"\nvisible_GPU : {}" "\ndevice : {}"
"\nn_jobs : {}" "\nn_jobs : {}"
"\nuse_GPU : {}" "\nuse_GPU : {}"
"\nseed : {}".format( "\nseed : {}".format(
@@ -110,7 +110,7 @@ class LSTM(Model):
early_stop, early_stop,
optimizer.lower(), optimizer.lower(),
loss, loss,
GPU, self.device,
n_jobs, n_jobs,
self.use_gpu, self.use_gpu,
seed, seed,
@@ -139,7 +139,7 @@ class LSTM(Model):
@property @property
def use_gpu(self): def use_gpu(self):
self.device != torch.device("cpu") return self.device != torch.device("cpu")
def mse(self, pred, label): def mse(self, pred, label):
loss = (pred - label) ** 2 loss = (pred - label) ** 2

8
qlib/contrib/model/pytorch_nn.py
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@@ -99,8 +99,8 @@ class DNNModelPytorch(Model):
"\nloss_type : {}" "\nloss_type : {}"
"\neval_steps : {}" "\neval_steps : {}"
"\nseed : {}" "\nseed : {}"
"\nvisible_GPU : {}" "\ndevice : {}"
"\nuse_gpu : {}" "\nuse_GPU : {}"
"\nweight_decay : {}".format( "\nweight_decay : {}".format(
layers, layers,
lr, lr,
@@ -114,7 +114,7 @@ class DNNModelPytorch(Model):
loss, loss,
eval_steps, eval_steps,
seed, seed,
GPU, self.device,
self.use_gpu, self.use_gpu,
weight_decay, weight_decay,
) )
@@ -158,7 +158,7 @@ class DNNModelPytorch(Model):
@property @property
def use_gpu(self): def use_gpu(self):
self.device != torch.device("cpu") return self.device != torch.device("cpu")
def fit( def fit(
self, self,

9
qlib/contrib/model/pytorch_sfm.py
View File

@@ -241,7 +241,6 @@ class SFM(Model):
self.optimizer = optimizer.lower() self.optimizer = optimizer.lower()
self.loss = loss self.loss = loss
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.use_gpu = torch.cuda.is_available()
self.seed = seed self.seed = seed
self.logger.info( self.logger.info(
@@ -260,7 +259,7 @@ class SFM(Model):
"\neval_steps : {}" "\neval_steps : {}"
"\noptimizer : {}" "\noptimizer : {}"
"\nloss_type : {}" "\nloss_type : {}"
"\nvisible_GPU : {}" "\ndevice : {}"
"\nuse_GPU : {}" "\nuse_GPU : {}"
"\nseed : {}".format( "\nseed : {}".format(
d_feat, d_feat,
@@ -277,7 +276,7 @@ class SFM(Model):
eval_steps, eval_steps,
optimizer.lower(), optimizer.lower(),
loss, loss,
GPU, self.device,
self.use_gpu, self.use_gpu,
seed, seed,
) )
@@ -309,6 +308,10 @@ class SFM(Model):
self.fitted = False self.fitted = False
self.sfm_model.to(self.device) self.sfm_model.to(self.device)
@property
def use_gpu(self):
return self.device != torch.device("cpu")
def test_epoch(self, data_x, data_y): def test_epoch(self, data_x, data_y):
# prepare training data # prepare training data

6
qlib/contrib/model/pytorch_tabnet.py
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@@ -86,8 +86,8 @@ class TabnetModel(Model):
"TabNet:" "TabNet:"
"\nbatch_size : {}" "\nbatch_size : {}"
"\nvirtual bs : {}" "\nvirtual bs : {}"
"\nGPU : {}" "\ndevice : {}"
"\npretrain: {}".format(self.batch_size, vbs, GPU, pretrain) "\npretrain: {}".format(self.batch_size, vbs, self.device, self.pretrain)
) )
self.fitted = False self.fitted = False
np.random.seed(self.seed) np.random.seed(self.seed)
@@ -118,7 +118,7 @@ class TabnetModel(Model):
@property @property
def use_gpu(self): def use_gpu(self):
self.device != torch.device("cpu") return self.device != torch.device("cpu")
def pretrain_fn(self, dataset=DatasetH, pretrain_file="./pretrain/best.model"): def pretrain_fn(self, dataset=DatasetH, pretrain_file="./pretrain/best.model"):
get_or_create_path(pretrain_file) get_or_create_path(pretrain_file)