From 33d3d2084403fd34b79c835d2f2fe04f6cd8f738 Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期三, 13 九月 2023 09:33:54 +0800
Subject: [PATCH] Merge branch 'main' of github.com:alibaba-damo-academy/FunASR add
---
funasr/bin/vad_inference_launch.py | 94 +++++++++++++++++-----------------------------
1 files changed, 35 insertions(+), 59 deletions(-)
diff --git a/funasr/bin/vad_inference_launch.py b/funasr/bin/vad_inference_launch.py
index 2ccc716..0cde570 100644
--- a/funasr/bin/vad_inference_launch.py
+++ b/funasr/bin/vad_inference_launch.py
@@ -1,56 +1,33 @@
#!/usr/bin/env python3
-# Copyright ESPnet (https://github.com/espnet/espnet). All Rights Reserved.
-# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
+# -*- 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,
@@ -69,10 +46,8 @@
num_workers: int = 1,
**kwargs,
):
- assert check_argument_types()
if batch_size > 1:
raise NotImplementedError("batch decoding is not implemented")
-
logging.basicConfig(
level=log_level,
@@ -110,16 +85,14 @@
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
@@ -150,10 +123,11 @@
vad_results.append(item)
if writer is not None:
ibest_writer["text"][keys[i]] = "{}".format(results[i])
-
+ torch.cuda.empty_cache()
return vad_results
return _forward
+
def inference_vad_online(
batch_size: int,
@@ -172,8 +146,6 @@
num_workers: int = 1,
**kwargs,
):
- assert check_argument_types()
-
logging.basicConfig(
level=log_level,
@@ -212,16 +184,14 @@
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
@@ -237,9 +207,13 @@
ibest_writer = None
vad_results = []
- batch_in_cache = param_dict['in_cache'] if param_dict is not None else dict()
- is_final = param_dict.get('is_final', False) if param_dict is not None else False
- max_end_sil = param_dict.get('max_end_sil', 800) if param_dict is not None else 800
+ if param_dict is None:
+ param_dict = dict()
+ param_dict['in_cache'] = dict()
+ param_dict['is_final'] = True
+ batch_in_cache = param_dict.get('in_cache', dict())
+ is_final = param_dict.get('is_final', False)
+ max_end_sil = param_dict.get('max_end_sil', 800)
for keys, batch in loader:
assert isinstance(batch, dict), type(batch)
assert all(isinstance(s, str) for s in keys), keys
@@ -265,6 +239,16 @@
return vad_results
return _forward
+
+
+def inference_launch(mode, **kwargs):
+ if mode == "offline":
+ return inference_vad(**kwargs)
+ elif mode == "online":
+ return inference_vad_online(**kwargs)
+ else:
+ logging.info("Unknown decoding mode: {}".format(mode))
+ return None
def get_parser():
@@ -358,15 +342,6 @@
return parser
-def inference_launch(mode, **kwargs):
- if mode == "offline":
- return inference_vad(**kwargs)
- elif mode == "online":
- return inference_vad_online(**kwargs)
- else:
- logging.info("Unknown decoding mode: {}".format(mode))
- return None
-
def main(cmd=None):
print(get_commandline_args(), file=sys.stderr)
parser = get_parser()
@@ -397,5 +372,6 @@
inference_pipeline = inference_launch(**kwargs)
return inference_pipeline(kwargs["data_path_and_name_and_type"])
+
if __name__ == "__main__":
main()
--
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