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[Bugfix] Fix data memory #317

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merged 2 commits into from
Dec 9, 2021
Merged

[Bugfix] Fix data memory #317

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82e89d5
Fix data memory
cenyk1230 Dec 9, 2021
842da97
Fix data memory
cenyk1230 Dec 9, 2021
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26 changes: 16 additions & 10 deletions cogdl/trainer/trainer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -187,6 +187,12 @@ def run(self, model_w: ModelWrapper, dataset_w: DataWrapper):
return best_model_w.model

final_test = self.evaluate(best_model_w, dataset_w)

# clear the GPU memory
dataset = dataset_w.get_dataset()
if isinstance(dataset.data, Graph):
dataset.data.to("cpu")

return final_test

def evaluate(self, model_w: ModelWrapper, dataset_w: DataWrapper, cpu=False):
Expand Down Expand Up @@ -244,16 +250,16 @@ def build_optimizer(self, model_w):
opt_wrap = model_w.setup_optimizer()
if isinstance(opt_wrap, list) or isinstance(opt_wrap, tuple):
assert len(opt_wrap) == 2
optimizers, lr_schedulars = opt_wrap
optimizers, lr_schedulers = opt_wrap
else:
optimizers = opt_wrap
lr_schedulars = None
lr_schedulers = None

if not isinstance(optimizers, list):
optimizers = [optimizers]
if lr_schedulars and not isinstance(lr_schedulars, list):
lr_schedulars = [lr_schedulars]
return optimizers, lr_schedulars
if lr_schedulers and not isinstance(lr_schedulers, list):
lr_schedulers = [lr_schedulers]
return optimizers, lr_schedulers

def initialize(self, model_w, rank=0, master_addr: str = "localhost", master_port: int = 10008):
if self.distributed_training:
Expand All @@ -274,7 +280,7 @@ def train(self, rank, model_w, dataset_w):
self.data_controller.prepare_data_wrapper(dataset_w, rank)
self.eval_data_back_to_cpu = dataset_w.data_back_to_cpu

optimizers, lr_schedulars = self.build_optimizer(model_w)
optimizers, lr_schedulers = self.build_optimizer(model_w)
if optimizers[0] is None:
return

Expand Down Expand Up @@ -315,7 +321,7 @@ def train(self, rank, model_w, dataset_w):
# inductive setting ..
dataset_w.train()
train_loader = dataset_w.on_train_wrapper()
training_loss = self.training_step(model_w, train_loader, optimizers, lr_schedulars, rank)
training_loss = self.training_step(model_w, train_loader, optimizers, lr_schedulers, rank)

print_str_dict["Epoch"] = epoch
print_str_dict["train_loss"] = training_loss
Expand Down Expand Up @@ -428,7 +434,7 @@ def distributed_test(self, model_w: ModelWrapper, loader, rank, fn):
dist.broadcast_object_list(object_list, src=0)
return object_list[0]

def training_step(self, model_w, train_loader, optimizers, lr_schedulars, device):
def training_step(self, model_w, train_loader, optimizers, lr_schedulers, device):
model_w.train()
losses = []

Expand All @@ -449,8 +455,8 @@ def training_step(self, model_w, train_loader, optimizers, lr_schedulars, device
optimizer.step()

losses.append(loss.item())
if lr_schedulars is not None:
for lr_schedular in lr_schedulars:
if lr_schedulers is not None:
for lr_schedular in lr_schedulers:
lr_schedular.step()
return np.mean(losses)

Expand Down