| | |
|---|
| | | **kwargs, |
|---|
| | | ): |
|---|
| | | assert check_argument_types() |
|---|
| | | |
|---|
| | | ncpu = kwargs.get("ncpu", 1) |
|---|
| | | torch.set_num_threads(ncpu) |
|---|
| | | |
|---|
| | | if word_lm_train_config is not None: |
|---|
| | | raise NotImplementedError("Word LM is not implemented") |
|---|
| | | if ngpu > 1: |
|---|
| | |
|---|
| | | export_mode = param_dict.get("export_mode", False) |
|---|
| | | else: |
|---|
| | | hotword_list_or_file = None |
|---|
| | | |
|---|
| | | |
|---|
| | | if kwargs.get("device", None) == "cpu": |
|---|
| | | ngpu = 0 |
|---|
| | | if ngpu >= 1 and torch.cuda.is_available(): |
|---|
| | | device = "cuda" |
|---|
| | | else: |
|---|
| | |
|---|
| | | finish_count += 1 |
|---|
| | | # asr_utils.print_progress(finish_count / file_count) |
|---|
| | | if writer is not None: |
|---|
| | | ibest_writer["text"][key] = text_postprocessed |
|---|
| | | ibest_writer["text"][key] = " ".join(word_lists) |
|---|
| | | |
|---|
| | | logging.info("decoding, utt: {}, predictions: {}".format(key, text)) |
|---|
| | | rtf_avg = "decoding, feature length total: {}, forward_time total: {:.4f}, rtf avg: {:.4f}".format(length_total, forward_time_total, 100 * forward_time_total / (length_total * lfr_factor)) |
|---|
