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mirror of https://github.com/microsoft/qlib.git synced 2026-06-30 17:41:18 +08:00

Add return for use_gpu..

This commit is contained in:
D-X-Y
2021-03-11 19:28:00 -08:00
parent 593553f573
commit 1d435248e2
11 changed files with 31 additions and 28 deletions

View File

@@ -93,7 +93,7 @@ class ALSTM(Model):
"\nearly_stop : {}"
"\noptimizer : {}"
"\nloss_type : {}"
"\nvisible_GPU : {}"
"\ndevice : {}"
"\nuse_GPU : {}"
"\nseed : {}".format(
d_feat,
@@ -107,7 +107,7 @@ class ALSTM(Model):
early_stop,
optimizer.lower(),
loss,
GPU,
self.device,
self.use_gpu,
seed,
)
@@ -138,7 +138,7 @@ class ALSTM(Model):
@property
def use_gpu(self):
self.device != torch.device("cpu")
return self.device != torch.device("cpu")
def mse(self, pred, label):
loss = (pred - label) ** 2

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

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

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

View File

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

View File

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

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

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

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

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

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@@ -86,8 +86,8 @@ class TabnetModel(Model):
"TabNet:"
"\nbatch_size : {}"
"\nvirtual bs : {}"
"\nGPU : {}"
"\npretrain: {}".format(self.batch_size, vbs, GPU, pretrain)
"\ndevice : {}"
"\npretrain: {}".format(self.batch_size, vbs, self.device, self.pretrain)
)
self.fitted = False
np.random.seed(self.seed)
@@ -118,7 +118,7 @@ class TabnetModel(Model):
@property
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"):
get_or_create_path(pretrain_file)