| | |
|---|
| | | from funasr.utils.timestamp_tools import ts_prediction_lfr6_standard |
|---|
| | | from funasr.models.transformer.utils.nets_utils import make_pad_mask, pad_list |
|---|
| | | from funasr.utils.load_utils import load_audio_text_image_video, extract_fbank |
|---|
| | | |
|---|
| | | from funasr.train_utils.device_funcs import to_device |
|---|
| | | |
|---|
| | | if LooseVersion(torch.__version__) >= LooseVersion("1.6.0"): |
|---|
| | | from torch.cuda.amp import autocast |
|---|
| | |
|---|
| | | result_i = {"key": key[i], "token_int": token_int} |
|---|
| | | results.append(result_i) |
|---|
| | | |
|---|
| | | return results, meta_data |
|---|
| | | return results, meta_data |
|---|
| | | |
|---|
| | | def export(self, **kwargs): |
|---|
| | | from .export_meta import export_rebuild_model |
|---|
| | | if 'max_seq_len' not in kwargs: |
|---|
| | | kwargs['max_seq_len'] = 512 |
|---|
| | | models = export_rebuild_model(model=self, **kwargs) |
|---|
| | | return models |
|---|
