| | |
|---|
| | | # if spk_model is not None, build spk model else None |
|---|
| | | spk_model = kwargs.get("spk_model", None) |
|---|
| | | spk_kwargs = {} if kwargs.get("spk_kwargs", {}) is None else kwargs.get("spk_kwargs", {}) |
|---|
| | | cb_kwargs = {} if spk_kwargs.get("cb_kwargs", {}) is None else spk_kwargs.get("cb_kwargs", {}) |
|---|
| | | cb_kwargs = ( |
|---|
| | | {} if spk_kwargs.get("cb_kwargs", {}) is None else spk_kwargs.get("cb_kwargs", {}) |
|---|
| | | ) |
|---|
| | | if spk_model is not None: |
|---|
| | | logging.info("Building SPK model.") |
|---|
| | | spk_kwargs["model"] = spk_model |
|---|
| | |
|---|
| | | set_all_random_seed(kwargs.get("seed", 0)) |
|---|
| | | |
|---|
| | | device = kwargs.get("device", "cuda") |
|---|
| | | if not torch.cuda.is_available() or kwargs.get("ngpu", 1) == 0: |
|---|
| | | if ((device =="cuda" and not torch.cuda.is_available()) |
|---|
| | | or (device == "xpu" and not torch.xpu.is_available()) |
|---|
| | | or kwargs.get("ngpu", 1) == 0): |
|---|
| | | device = "cpu" |
|---|
| | | kwargs["batch_size"] = 1 |
|---|
| | | kwargs["device"] = device |
|---|
| | |
|---|
| | | if pbar: |
|---|
| | | # pbar.update(1) |
|---|
| | | pbar.set_description(f"rtf_avg: {time_escape_total/time_speech_total:0.3f}") |
|---|
| | | torch.cuda.empty_cache() |
|---|
| | | |
|---|
| | | device = next(model.parameters()).device |
|---|
| | | if device.type == "cuda": |
|---|
| | | with torch.cuda.device(device): |
|---|
| | | torch.cuda.empty_cache() |
|---|
| | | return asr_result_list |
|---|
| | | |
|---|
| | | def inference_with_vad(self, input, input_len=None, **cfg): |
|---|
