veri_dir = ScriptTestDataset(dir=args.train_dir,
loader=file_loader,
transform=transform_T,
return_uid=True)
veri_dir.partition(args.sample_utt)
test_dir = ScriptTestDataset(dir=args.test_dir,
loader=file_loader,
transform=transform_T,
return_uid=True)
test_dir.partition(args.sample_utt)
valid_dir = ScriptValidDataset(valid_set=train_dir.valid_set,
spk_to_idx=train_dir.spk_to_idx,
valid_uid2feat=train_dir.valid_uid2feat,
valid_utt2spk_dict=train_dir.valid_utt2spk_dict,
loader=file_loader,
transform=transform,
return_uid=True)
indices = list(range(len(valid_dir)))
random.shuffle(indices)
indices = indices[:args.sample_utt]
valid_part = torch.utils.data.Subset(valid_dir, indices)
# sitw_test_dir = SitwTestDataset(sitw_dir=args.sitw_dir, sitw_set='eval', transform=transform_T, return_uid=False)
# indices = list(range(len(sitw_test_dir)))
# random.shuffle(indices)
# indices = indices[:args.sample_utt]
# sitw_test_part = torch.utils.data.Subset(sitw_test_dir, indices)
#
# sitw_dev_dir = SitwTestDataset(sitw_dir=args.sitw_dir, sitw_set='dev', transform=transform_T, return_uid=False)
transform = ConcateNumInput(num_frames=args.num_frames, remove_vad=args.remove_vad)
if args.feat_format == 'npy':
file_loader = np.load
elif args.feat_format in ['kaldi', 'klfb']:
file_loader = kaldi_io.read_mat
train_dir = ScriptTrainDataset(dir=args.data_dir, samples_per_speaker=args.input_per_spks, loader=file_loader,
transform=transform, num_valid=args.num_valid, domain=args.domain)
# train_dir = LoadScriptDataset(dir=args.data_dir, samples_per_speaker=args.input_per_spks, loader=file_loader,
# transform=transform, num_valid=args.num_valid, domain=args.domain)
>>>>>>> Server/Server
valid_dir = ScriptValidDataset(valid_set=train_dir.valid_set, loader=file_loader, spk_to_idx=train_dir.spk_to_idx,
dom_to_idx=train_dir.dom_to_idx, valid_utt2dom_dict=train_dir.valid_utt2dom_dict,
valid_uid2feat=train_dir.valid_uid2feat, valid_utt2spk_dict=train_dir.valid_utt2spk_dict,
transform=transform, domain=args.domain)
if __name__ == "__main__":
np.random.seed(args.seed)
torch.manual_seed(args.seed)
random.seed(args.seed)
<<<<<<< HEAD
=======
>>>>>>> Server/Server
nj = args.nj
data_dir = args.data_dir
out_dir = os.path.join(args.out_dir, args.out_set)
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