def __init__(self, net, idim, hdim, K, n_layers, dropout, lamb):
super(Model, self).__init__()
self.net = eval(net)(idim, hdim, n_layers, dropout=dropout)
if net in ['BLSTM', 'BLSTMN', 'VGGBLSTM']:
self.linear = nn.Linear(hdim * 2, K)
else:
self.linear = nn.Linear(hdim, K)
self.loss_fn = CTC_CRF_LOSS(lamb=lamb)
def __init__(self, idim, hdim, K, dropout, lamb, reg_weight, use_ctc_crf=False):
super(CAT_Chunk_Model, self).__init__()
self.net = ChunkBLSTM_with_Context(idim, hdim, context=10, dropout=0.5)
self.linear = nn.Linear(hdim*2, K)
self.reg_weight = reg_weight
self.criterion = nn.MSELoss(size_average=False)
if use_ctc_crf:
self.loss_fn = CTC_CRF_LOSS(lamb=lamb)
else:
self.loss_fn = WARP_CTC_LOSS()
def __init__(self, net, idim, hdim, K, n_layers, dropout, lamb, use_ctc_crf=False):
super(CAT_Model, self).__init__()
self.net = eval(net)(idim, hdim, n_layers, dropout=dropout)
if net in ['BLSTM', 'BLSTMN']:
self.linear = nn.Linear(hdim * 2, K)
else:
self.linear = nn.Linear(hdim, K)
if use_ctc_crf:
self.loss_fn = CTC_CRF_LOSS(lamb=lamb)
else:
self.loss_fn = WARP_CTC_LOSS()
def __init__(self, idim, hdim, K, n_layers, dropout, lamb):
super(Model, self).__init__()
self.net = BLSTM(idim, hdim, n_layers, dropout=dropout)
self.linear = nn.Linear(hdim * 2, K)
self.loss_fn = CTC_CRF_LOSS(lamb=lamb)