| | |
| | | rescale_line = line_item[3:(len(line_item) - 1)] |
| | | vars_list = list(rescale_line) |
| | | continue |
| | | import pdb;pdb.set_trace() |
| | | means = np.array(means_list).astype(np.float32) |
| | | vars = np.array(vars_list).astype(np.float32) |
| | | cmvn = np.array([means, vars]) |
| | |
| | | return feats_pad, feats_lens, lfr_splice_frame_idxs |
| | | |
| | | def forward( |
| | | self, input: torch.Tensor, input_lengths: torch.Tensor, cache: dict = {}, **kwargs |
| | | self, input: torch.Tensor, input_lengths: torch.Tensor, **kwargs |
| | | ): |
| | | is_final = kwargs.get("is_final", False) |
| | | cache = kwargs.get("cache", {}) |
| | | if len(cache) == 0: |
| | | self.init_cache(cache) |
| | | |