'da':64,
'r':4,
'dropout':0.25,
}
args.cuda=torch.cuda.is_available()
if(args.cuda==False):sys.exit("GPU is not available")
torch.manual_seed(args.seed);torch.cuda.manual_seed(args.seed)
# load dataset
featrootdir=r'/home/liuzongming/feature_alstm_unnorm'
cvtxtrootdir='../../../CV/folds'
normfile=r'../temp1/ms{}.npy'.format(args.cvnum)
dataset_train=AudioFeatureDataset(featrootdir=featrootdir, \
cvtxtrootdir=cvtxtrootdir,feattype='npy', \
cvnum=args.cvnum,mode='train',normflag=1,\
normfile=normfile)
dataset_eva=AudioFeatureDataset(featrootdir=featrootdir, \
cvtxtrootdir=cvtxtrootdir,feattype='npy', \
cvnum=args.cvnum,mode='eva',normflag=0,\
normfile=normfile)
dataset_test=AudioFeatureDataset(featrootdir=featrootdir, \
cvtxtrootdir=cvtxtrootdir,feattype='npy', \
cvnum=args.cvnum,mode='test',normflag=0,\
normfile=normfile)
print("shuffling dataset_train")
'dropout': 0.0,
'da': 128,
'r': 4,
}
penaltyWeight = 0.01
emotion_labels = ('neu', 'hap', 'ang', 'sad')
args.cuda = torch.cuda.is_available()
if (args.cuda == False): sys.exit("GPU is not available")
torch.manual_seed(args.seed)
torch.cuda.manual_seed(args.seed)
# load dataset
dataset_train=AudioFeatureDataset(featrootdir=r'/mnt/c/chenhangting/Project/iemocap/chenhangting/features/basicfbank', \
cvtxtrootdir='/mnt/c/chenhangting/Project/iemocap/chenhangting/CV/folds',feattype='npy', \
cvnum=args.cvnum,mode='train',normflag=1,\
normfile=r'/mnt/c/chenhangting/Project/iemocap/chenhangting/features/basicfbank/ms{}.npy'.format(args.cvnum))
dataset_eva=AudioFeatureDataset(featrootdir=r'/mnt/c/chenhangting/Project/iemocap/chenhangting/features/basicfbank', \
cvtxtrootdir='/mnt/c/chenhangting/Project/iemocap/chenhangting/CV/folds',feattype='npy', \
cvnum=args.cvnum,mode='eva',normflag=0,\
normfile=r'/mnt/c/chenhangting/Project/iemocap/chenhangting/features/basicfbank/ms{}.npy'.format(args.cvnum))
dataset_test=AudioFeatureDataset(featrootdir=r'/mnt/c/chenhangting/Project/iemocap/chenhangting/features/basicfbank', \
cvtxtrootdir='/mnt/c/chenhangting/Project/iemocap/chenhangting/CV/folds',feattype='npy', \
cvnum=args.cvnum,mode='test',normflag=0,\
normfile=r'/mnt/c/chenhangting/Project/iemocap/chenhangting/features/basicfbank/ms{}.npy'.format(args.cvnum))
print("shuffling dataset_train")
train_loader=torch.utils.data.DataLoader(dataset_train, \
