| | |
| | | import torch |
| | | import torch.nn.functional as F |
| | | from torch import nn |
| | | |
| | | from modelscope.utils.logger import get_logger |
| | | logger = get_logger() |
| | | |
| | | class EncoderDecoderAttractor(nn.Module): |
| | | |
| | |
| | | self.n_units = n_units |
| | | |
| | | def forward_core(self, xs, zeros): |
| | | logger.info("xs: ".format(xs)) |
| | | ilens = torch.from_numpy(np.array([x.shape[0] for x in xs])).to(torch.float32).to(xs[0].device) |
| | | logger.info("ilens: ".format(ilens)) |
| | | xs = [self.enc0_dropout(x) for x in xs] |
| | | xs = nn.utils.rnn.pad_sequence(xs, batch_first=True, padding_value=-1) |
| | | xs = nn.utils.rnn.pack_padded_sequence(xs, ilens, batch_first=True, enforce_sorted=False) |