Dev gzf exp (#1707)

zhifu gao

2024-05-08 4adb76a6edbca93aae7caa83382e764d7b058f07

 funasr/auto/auto_model.py

@@ -364,7 +364,6 @@
            if len(sorted_data) > 0 and len(sorted_data[0]) > 0:
                batch_size = max(batch_size, sorted_data[0][0][1] - sorted_data[0][0][0])

            batch_size_ms_cum = 0
            beg_idx = 0
            beg_asr_total = time.time()
            time_speech_total_per_sample = speech_lengths / 16000
@@ -373,19 +372,22 @@
            # pbar_sample = tqdm(colour="blue", total=n, dynamic_ncols=True)

            all_segments = []
            max_len_in_batch = 0
            end_idx = 1
            for j, _ in enumerate(range(0, n)):
                # pbar_sample.update(1)
                batch_size_ms_cum += sorted_data[j][0][1] - sorted_data[j][0][0]
                sample_length = sorted_data[j][0][1] - sorted_data[j][0][0]
                potential_batch_length = max(max_len_in_batch, sample_length) * (j + 1 - beg_idx)
                # batch_size_ms_cum += sorted_data[j][0][1] - sorted_data[j][0][0]
                if (
                    j < n - 1
                    and (batch_size_ms_cum + sorted_data[j + 1][0][1] - sorted_data[j + 1][0][0])
                    < batch_size
                    and (sorted_data[j + 1][0][1] - sorted_data[j + 1][0][0])
                    < batch_size_threshold_ms
                    and sample_length < batch_size_threshold_ms
                    and potential_batch_length < batch_size
                ):
                    max_len_in_batch = max(max_len_in_batch, sample_length)
                    end_idx += 1
                    continue
                batch_size_ms_cum = 0
                end_idx = j + 1

                speech_j, speech_lengths_j = slice_padding_audio_samples(
                    speech, speech_lengths, sorted_data[beg_idx:end_idx]
                )
@@ -410,6 +412,8 @@
                        )
                        results[_b]["spk_embedding"] = spk_res[0]["spk_embedding"]
                beg_idx = end_idx
                end_idx += 1
                max_len_in_batch = sample_length
                if len(results) < 1:
                    continue
                results_sorted.extend(results)