U.timeCheck('s', stime)
saved_examples = U.getSavedExamples('BILINEAR0016pre-3MTEST_testdata.p')
DataManager = DS.NewsDataset(saved_examples, Vocab, True)
U.timeCheck('e', stime)
if True:
# Define Model
print('before calling model allocated (dictionary): ', end=' ')
print(torch.cuda.memory_allocated(1))
print("Calling Model .... ", end='')
U.timeCheck('s', stime)
if 'SCORE' in Args.args.model_name:
NET = Model.ScoringNetwork(Vocab).to(torch.device(Args.args.device))
print('ScoreNet Created')
elif 'BILINEAR' in Args.args.model_name:
NET = Model.BiLinearNetwork(Vocab).to(torch.device(Args.args.device))
print('BiLinearNet Created')
print("Done !!!", end=' ')
U.timeCheck('e', stime)
if True:
# Training Model
print("Training Model .... ")
U.timeCheck('s', stime)
print('memory allocated (dictionary): ', end=' ')
print(torch.cuda.memory_allocated(1))
trainloader = DataManager.get_trainloader(DataManager, 'train',
Args.args.batch_size)
referenced_id['trained'] = Train.Train(trainloader, NET)
print("Done Training !!!", end=' ')
U.timeCheck('e', stime)
