update readme, fix seaco bug

shixian.shi

2024-01-15 55c09aeaa25b4bb88a50e09ba68fa6ff00a6d676

 funasr/models/bicif_paraformer/model.py

@@ -3,34 +3,36 @@
# Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
#  MIT License  (https://opensource.org/licenses/MIT)

import logging
from typing import Dict
from typing import List
from typing import Optional
from typing import Tuple
import copy
import torch
import torch.nn as nn
import random
import numpy as np
import time
import torch
import logging
from contextlib import contextmanager
from distutils.version import LooseVersion
from typing import Dict, List, Optional, Tuple

from funasr.models.transformer.utils.add_sos_eos import add_sos_eos
from funasr.models.transformer.utils.nets_utils import make_pad_mask, pad_list
from funasr.metrics.compute_acc import th_accuracy
from funasr.train_utils.device_funcs import force_gatherable

from funasr.models.paraformer.search import Hypothesis

from funasr.utils.load_utils import load_audio_text_image_video, extract_fbank
from funasr.utils import postprocess_utils
from funasr.utils.datadir_writer import DatadirWriter
from funasr.utils.timestamp_tools import ts_prediction_lfr6_standard
from funasr.register import tables
from funasr.models.ctc.ctc import CTC


from funasr.utils import postprocess_utils
from funasr.metrics.compute_acc import th_accuracy
from funasr.utils.datadir_writer import DatadirWriter
from funasr.models.paraformer.model import Paraformer
from funasr.models.paraformer.search import Hypothesis
from funasr.train_utils.device_funcs import force_gatherable
from funasr.models.transformer.utils.add_sos_eos import add_sos_eos
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


if LooseVersion(torch.__version__) >= LooseVersion("1.6.0"):
    from torch.cuda.amp import autocast
else:
    # Nothing to do if torch<1.6.0
    @contextmanager
    def autocast(enabled=True):
        yield


@tables.register("model_classes", "BiCifParaformer")
class BiCifParaformer(Paraformer):
@@ -215,7 +217,7 @@
        return loss, stats, weight


    def generate(self,
    def inference(self,
                 data_in,
                 data_lengths=None,
                 key: list = None,