| | |
| | | output_writer = open("{}/result.txt".format(output_path), "w") |
| | | result_list = [] |
| | | for keys, batch in loader: |
| | | logger.info("keys: {}".format(keys)) |
| | | logger.info("batch: {}".format(batch)) |
| | | assert isinstance(batch, dict), type(batch) |
| | | assert all(isinstance(s, str) for s in keys), keys |
| | | _bs = len(next(iter(batch.values()))) |
| | |
| | | import funasr.models.frontend.eend_ola_feature as eend_ola_feature |
| | | from funasr.models.frontend.abs_frontend import AbsFrontend |
| | | |
| | | from modelscope.utils.logger import get_logger |
| | | logger = get_logger() |
| | | |
| | | def load_cmvn(cmvn_file): |
| | | with open(cmvn_file, 'r', encoding='utf-8') as f: |
| | |
| | | batch_size = input.size(0) |
| | | feats = [] |
| | | feats_lens = [] |
| | | logger.info("batch_size: {}".format(batch_size)) |
| | | logger.info("input: {}".format(input)) |
| | | logger.info("input_lengths: {}".format(input_lengths)) |
| | | for i in range(batch_size): |
| | | waveform_length = input_lengths[i] |
| | | waveform = input[i][:waveform_length] |