From eee72548d7cab4124d6292fdb5038ad420344394 Mon Sep 17 00:00:00 2001
From: 嘉渊 <wangjiaming.wjm@alibaba-inc.com>
Date: 星期四, 15 六月 2023 17:25:46 +0800
Subject: [PATCH] update repo
---
funasr/bin/vad_inference_launch.py | 59 +++++++----------------------
funasr/build_utils/build_streaming_iterator.py | 4 +-
funasr/bin/vad_infer.py | 40 +++++---------------
3 files changed, 27 insertions(+), 76 deletions(-)
diff --git a/funasr/bin/vad_infer.py b/funasr/bin/vad_infer.py
index e1698d0..a511239 100644
--- a/funasr/bin/vad_infer.py
+++ b/funasr/bin/vad_infer.py
@@ -1,42 +1,23 @@
-# -*- encoding: utf-8 -*-
#!/usr/bin/env python3
+# -*- encoding: utf-8 -*-
# Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
# MIT License (https://opensource.org/licenses/MIT)
-import argparse
import logging
-import os
-import sys
-import json
+import math
from pathlib import Path
-from typing import Any
+from typing import Dict
from typing import List
-from typing import Optional
-from typing import Sequence
from typing import Tuple
from typing import Union
-from typing import Dict
-import math
import numpy as np
import torch
from typeguard import check_argument_types
-from typeguard import check_return_type
-from funasr.fileio.datadir_writer import DatadirWriter
-from funasr.modules.scorers.scorer_interface import BatchScorerInterface
-from funasr.modules.subsampling import TooShortUttError
-from funasr.tasks.vad import VADTask
-from funasr.torch_utils.device_funcs import to_device
-from funasr.torch_utils.set_all_random_seed import set_all_random_seed
-from funasr.utils import config_argparse
-from funasr.utils.cli_utils import get_commandline_args
-from funasr.utils.types import str2bool
-from funasr.utils.types import str2triple_str
-from funasr.utils.types import str_or_none
-from funasr.utils import asr_utils, wav_utils, postprocess_utils
+from funasr.build_utils.build_model_from_file import build_model_from_file
from funasr.models.frontend.wav_frontend import WavFrontend, WavFrontendOnline
-
+from funasr.torch_utils.device_funcs import to_device
class Speech2VadSegment:
@@ -64,8 +45,8 @@
assert check_argument_types()
# 1. Build vad model
- vad_model, vad_infer_args = VADTask.build_model_from_file(
- vad_infer_config, vad_model_file, device
+ vad_model, vad_infer_args = build_model_from_file(
+ vad_infer_config, vad_model_file, "None", device, task_name="vad"
)
frontend = None
if vad_infer_args.frontend is not None:
@@ -128,12 +109,13 @@
"in_cache": in_cache
}
# a. To device
- #batch = to_device(batch, device=self.device)
+ # batch = to_device(batch, device=self.device)
segments_part, in_cache = self.vad_model(**batch)
if segments_part:
for batch_num in range(0, self.batch_size):
segments[batch_num] += segments_part[batch_num]
return fbanks, segments
+
class Speech2VadSegmentOnline(Speech2VadSegment):
"""Speech2VadSegmentOnline class
@@ -146,13 +128,13 @@
[[10, 230], [245, 450], ...]
"""
+
def __init__(self, **kwargs):
super(Speech2VadSegmentOnline, self).__init__(**kwargs)
vad_cmvn_file = kwargs.get('vad_cmvn_file', None)
self.frontend = None
if self.vad_infer_args.frontend is not None:
self.frontend = WavFrontendOnline(cmvn_file=vad_cmvn_file, **self.vad_infer_args.frontend_conf)
-
@torch.no_grad()
def __call__(
@@ -198,5 +180,3 @@
# in_cache.update(batch['in_cache'])
# in_cache = {key: value for key, value in batch['in_cache'].items()}
return fbanks, segments, in_cache
-
-
diff --git a/funasr/bin/vad_inference_launch.py b/funasr/bin/vad_inference_launch.py
index b17d058..829f157 100644
--- a/funasr/bin/vad_inference_launch.py
+++ b/funasr/bin/vad_inference_launch.py
@@ -1,58 +1,34 @@
-# -*- encoding: utf-8 -*-
#!/usr/bin/env python3
+# -*- encoding: utf-8 -*-
# Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
# MIT License (https://opensource.org/licenses/MIT)
import torch
+
torch.set_num_threads(1)
import argparse
import logging
import os
import sys
-from typing import Union, Dict, Any
-
-from funasr.utils import config_argparse
-from funasr.utils.cli_utils import get_commandline_args
-from funasr.utils.types import str2bool
-from funasr.utils.types import str2triple_str
-from funasr.utils.types import str_or_none
-
-import argparse
-import logging
-import os
-import sys
import json
-from pathlib import Path
-from typing import Any
-from typing import List
from typing import Optional
-from typing import Sequence
-from typing import Tuple
from typing import Union
-from typing import Dict
-import math
import numpy as np
import torch
from typeguard import check_argument_types
-from typeguard import check_return_type
-
+from funasr.build_utils.build_streaming_iterator import build_streaming_iterator
from funasr.fileio.datadir_writer import DatadirWriter
-from funasr.modules.scorers.scorer_interface import BatchScorerInterface
-from funasr.modules.subsampling import TooShortUttError
-from funasr.tasks.vad import VADTask
-from funasr.torch_utils.device_funcs import to_device
from funasr.torch_utils.set_all_random_seed import set_all_random_seed
from funasr.utils import config_argparse
from funasr.utils.cli_utils import get_commandline_args
from funasr.utils.types import str2bool
from funasr.utils.types import str2triple_str
from funasr.utils.types import str_or_none
-from funasr.utils import asr_utils, wav_utils, postprocess_utils
-from funasr.models.frontend.wav_frontend import WavFrontend, WavFrontendOnline
from funasr.bin.vad_infer import Speech2VadSegment, Speech2VadSegmentOnline
+
def inference_vad(
batch_size: int,
@@ -74,7 +50,6 @@
assert check_argument_types()
if batch_size > 1:
raise NotImplementedError("batch decoding is not implemented")
-
logging.basicConfig(
level=log_level,
@@ -112,16 +87,14 @@
if isinstance(raw_inputs, torch.Tensor):
raw_inputs = raw_inputs.numpy()
data_path_and_name_and_type = [raw_inputs, "speech", "waveform"]
- loader = VADTask.build_streaming_iterator(
- data_path_and_name_and_type,
+ loader = build_streaming_iterator(
+ task_name="vad",
+ preprocess_args=None,
+ data_path_and_name_and_type=data_path_and_name_and_type,
dtype=dtype,
batch_size=batch_size,
key_file=key_file,
num_workers=num_workers,
- preprocess_fn=VADTask.build_preprocess_fn(speech2vadsegment.vad_infer_args, False),
- collate_fn=VADTask.build_collate_fn(speech2vadsegment.vad_infer_args, False),
- allow_variable_data_keys=allow_variable_data_keys,
- inference=True,
)
finish_count = 0
@@ -157,6 +130,7 @@
return _forward
+
def inference_vad_online(
batch_size: int,
ngpu: int,
@@ -175,7 +149,6 @@
**kwargs,
):
assert check_argument_types()
-
logging.basicConfig(
level=log_level,
@@ -214,16 +187,14 @@
if isinstance(raw_inputs, torch.Tensor):
raw_inputs = raw_inputs.numpy()
data_path_and_name_and_type = [raw_inputs, "speech", "waveform"]
- loader = VADTask.build_streaming_iterator(
- data_path_and_name_and_type,
+ loader = build_streaming_iterator(
+ task_name="vad",
+ preprocess_args=None,
+ data_path_and_name_and_type=data_path_and_name_and_type,
dtype=dtype,
batch_size=batch_size,
key_file=key_file,
num_workers=num_workers,
- preprocess_fn=VADTask.build_preprocess_fn(speech2vadsegment.vad_infer_args, False),
- collate_fn=VADTask.build_collate_fn(speech2vadsegment.vad_infer_args, False),
- allow_variable_data_keys=allow_variable_data_keys,
- inference=True,
)
finish_count = 0
@@ -273,8 +244,6 @@
return _forward
-
-
def inference_launch(mode, **kwargs):
if mode == "offline":
return inference_vad(**kwargs)
@@ -283,6 +252,7 @@
else:
logging.info("Unknown decoding mode: {}".format(mode))
return None
+
def get_parser():
parser = config_argparse.ArgumentParser(
@@ -405,5 +375,6 @@
inference_pipeline = inference_launch(**kwargs)
return inference_pipeline(kwargs["data_path_and_name_and_type"])
+
if __name__ == "__main__":
main()
diff --git a/funasr/build_utils/build_streaming_iterator.py b/funasr/build_utils/build_streaming_iterator.py
index 8c5f7fc..1b16cf4 100644
--- a/funasr/build_utils/build_streaming_iterator.py
+++ b/funasr/build_utils/build_streaming_iterator.py
@@ -5,7 +5,7 @@
from funasr.datasets.iterable_dataset import IterableESPnetDataset
from funasr.datasets.small_datasets.collate_fn import CommonCollateFn
from funasr.datasets.small_datasets.preprocessor import build_preprocess
-from funasr.build_utils.build_model_from_file import build_model_from_file
+
def build_streaming_iterator(
task_name,
@@ -20,7 +20,7 @@
use_collate_fn: bool = True,
preprocess_fn=None,
ngpu: int = 0,
- train: bool=False,
+ train: bool = False,
) -> DataLoader:
"""Build DataLoader using iterable dataset"""
assert check_argument_types()
--
Gitblit v1.9.1