| | |
| | | . ./path.sh || exit 1; |
| | | |
| | | # machines configuration |
| | | CUDA_VISIBLE_DEVICES="0,1" |
| | | gpu_num=2 |
| | | CUDA_VISIBLE_DEVICES="0" |
| | | gpu_num=1 |
| | | count=1 |
| | | gpu_inference=true # Whether to perform gpu decoding, set false for cpu decoding |
| | | # for gpu decoding, inference_nj=ngpu*njob; for cpu decoding, inference_nj=njob |
| New file |
| | |
| | | from abc import ABC |
| | | from abc import abstractmethod |
| | | from typing import Tuple |
| | | |
| | | import torch |
| | | |
| | | |
| | | class AbsNormalize(torch.nn.Module, ABC): |
| | | @abstractmethod |
| | | def forward( |
| | | self, input: torch.Tensor, input_lengths: torch.Tensor = None |
| | | ) -> Tuple[torch.Tensor, torch.Tensor]: |
| | | # return output, output_lengths |
| | | raise NotImplementedError |