From f0fdc051fbddc2a941b303730dba87df6658f9dd Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期五, 14 四月 2023 10:24:13 +0800
Subject: [PATCH] Author
---
funasr/runtime/python/onnxruntime/setup.py | 2
funasr/models/e2e_tp.py | 2
funasr/runtime/python/onnxruntime/funasr_onnx/vad_bin.py | 128 +++++++++++++++++++++
funasr/export/models/e2e_asr_paraformer.py | 4
funasr/models/e2e_asr_paraformer.py | 4
funasr/models/decoder/contextual_decoder.py | 2
funasr/models/encoder/sanm_encoder.py | 6
funasr/models/decoder/sanm_decoder.py | 4
funasr/models/encoder/opennmt_encoders/self_attention_encoder.py | 2
funasr/runtime/python/onnxruntime/funasr_onnx/punc_bin.py | 4
funasr/modules/streaming_utils/chunk_utilis.py | 2
funasr/models/vad_realtime_transformer.py | 2
funasr/export/models/CT_Transformer.py | 4
funasr/runtime/python/onnxruntime/demo_vad_online.py | 4
/dev/null | 134 ----------------------
funasr/models/decoder/transformer_decoder.py | 2
funasr/models/target_delay_transformer.py | 2
funasr/models/e2e_vad.py | 25 ++++
funasr/models/e2e_uni_asr.py | 2
funasr/models/encoder/opennmt_encoders/conv_encoder.py | 2
funasr/runtime/python/onnxruntime/funasr_onnx/__init__.py | 1
funasr/runtime/python/onnxruntime/demo_vad_offline.py | 2
22 files changed, 179 insertions(+), 161 deletions(-)
diff --git a/funasr/export/models/CT_Transformer.py b/funasr/export/models/CT_Transformer.py
index ea6ff4f..932e3af 100644
--- a/funasr/export/models/CT_Transformer.py
+++ b/funasr/export/models/CT_Transformer.py
@@ -10,7 +10,7 @@
class CT_Transformer(nn.Module):
"""
- Author: Speech Lab, Alibaba Group, China
+ Author: Speech Lab of DAMO Academy, Alibaba Group
CT-Transformer: Controllable time-delay transformer for real-time punctuation prediction and disfluency detection
https://arxiv.org/pdf/2003.01309.pdf
"""
@@ -81,7 +81,7 @@
class CT_Transformer_VadRealtime(nn.Module):
"""
- Author: Speech Lab, Alibaba Group, China
+ Author: Speech Lab of DAMO Academy, Alibaba Group
CT-Transformer: Controllable time-delay transformer for real-time punctuation prediction and disfluency detection
https://arxiv.org/pdf/2003.01309.pdf
"""
diff --git a/funasr/export/models/e2e_asr_paraformer.py b/funasr/export/models/e2e_asr_paraformer.py
index 0db61e0..52ad320 100644
--- a/funasr/export/models/e2e_asr_paraformer.py
+++ b/funasr/export/models/e2e_asr_paraformer.py
@@ -19,7 +19,7 @@
class Paraformer(nn.Module):
"""
- Author: Speech Lab, Alibaba Group, China
+ Author: Speech Lab of DAMO Academy, Alibaba Group
Paraformer: Fast and Accurate Parallel Transformer for Non-autoregressive End-to-End Speech Recognition
https://arxiv.org/abs/2206.08317
"""
@@ -112,7 +112,7 @@
class BiCifParaformer(nn.Module):
"""
- Author: Speech Lab, Alibaba Group, China
+ Author: Speech Lab of DAMO Academy, Alibaba Group
Paraformer: Fast and Accurate Parallel Transformer for Non-autoregressive End-to-End Speech Recognition
https://arxiv.org/abs/2206.08317
"""
diff --git a/funasr/models/decoder/contextual_decoder.py b/funasr/models/decoder/contextual_decoder.py
index 3b462e7..78105ab 100644
--- a/funasr/models/decoder/contextual_decoder.py
+++ b/funasr/models/decoder/contextual_decoder.py
@@ -102,7 +102,7 @@
class ContextualParaformerDecoder(ParaformerSANMDecoder):
"""
- author: Speech Lab, Alibaba Group, China
+ Author: Speech Lab of DAMO Academy, Alibaba Group
Paraformer: Fast and Accurate Parallel Transformer for Non-autoregressive End-to-End Speech Recognition
https://arxiv.org/abs/2006.01713
"""
diff --git a/funasr/models/decoder/sanm_decoder.py b/funasr/models/decoder/sanm_decoder.py
index 463918a..18cd343 100644
--- a/funasr/models/decoder/sanm_decoder.py
+++ b/funasr/models/decoder/sanm_decoder.py
@@ -151,7 +151,7 @@
class FsmnDecoderSCAMAOpt(BaseTransformerDecoder):
"""
- author: Speech Lab, Alibaba Group, China
+ Author: Speech Lab of DAMO Academy, Alibaba Group
SCAMA: Streaming chunk-aware multihead attention for online end-to-end speech recognition
https://arxiv.org/abs/2006.01713
@@ -812,7 +812,7 @@
class ParaformerSANMDecoder(BaseTransformerDecoder):
"""
- author: Speech Lab, Alibaba Group, China
+ Author: Speech Lab of DAMO Academy, Alibaba Group
Paraformer: Fast and Accurate Parallel Transformer for Non-autoregressive End-to-End Speech Recognition
https://arxiv.org/abs/2006.01713
"""
diff --git a/funasr/models/decoder/transformer_decoder.py b/funasr/models/decoder/transformer_decoder.py
index 5f1bb24..aed7f20 100644
--- a/funasr/models/decoder/transformer_decoder.py
+++ b/funasr/models/decoder/transformer_decoder.py
@@ -405,7 +405,7 @@
class ParaformerDecoderSAN(BaseTransformerDecoder):
"""
- author: Speech Lab, Alibaba Group, China
+ Author: Speech Lab of DAMO Academy, Alibaba Group
Paraformer: Fast and Accurate Parallel Transformer for Non-autoregressive End-to-End Speech Recognition
https://arxiv.org/abs/2006.01713
"""
diff --git a/funasr/models/e2e_asr_paraformer.py b/funasr/models/e2e_asr_paraformer.py
index f1bb2bf..5c8560d 100644
--- a/funasr/models/e2e_asr_paraformer.py
+++ b/funasr/models/e2e_asr_paraformer.py
@@ -44,7 +44,7 @@
class Paraformer(AbsESPnetModel):
"""
- Author: Speech Lab, Alibaba Group, China
+ Author: Speech Lab of DAMO Academy, Alibaba Group
Paraformer: Fast and Accurate Parallel Transformer for Non-autoregressive End-to-End Speech Recognition
https://arxiv.org/abs/2206.08317
"""
@@ -612,7 +612,7 @@
class ParaformerBert(Paraformer):
"""
- Author: Speech Lab, Alibaba Group, China
+ Author: Speech Lab of DAMO Academy, Alibaba Group
Paraformer2: advanced paraformer with LFMMI and bert for non-autoregressive end-to-end speech recognition
"""
diff --git a/funasr/models/e2e_tp.py b/funasr/models/e2e_tp.py
index 887439c..d1367ab 100644
--- a/funasr/models/e2e_tp.py
+++ b/funasr/models/e2e_tp.py
@@ -32,7 +32,7 @@
class TimestampPredictor(AbsESPnetModel):
"""
- Author: Speech Lab, Alibaba Group, China
+ Author: Speech Lab of DAMO Academy, Alibaba Group
"""
def __init__(
diff --git a/funasr/models/e2e_uni_asr.py b/funasr/models/e2e_uni_asr.py
index ac4db32..ca76244 100644
--- a/funasr/models/e2e_uni_asr.py
+++ b/funasr/models/e2e_uni_asr.py
@@ -40,7 +40,7 @@
class UniASR(AbsESPnetModel):
"""
- Author: Speech Lab, Alibaba Group, China
+ Author: Speech Lab of DAMO Academy, Alibaba Group
"""
def __init__(
diff --git a/funasr/models/e2e_vad.py b/funasr/models/e2e_vad.py
index 440a049..50ec475 100644
--- a/funasr/models/e2e_vad.py
+++ b/funasr/models/e2e_vad.py
@@ -35,6 +35,11 @@
class VADXOptions:
+ """
+ Author: Speech Lab of DAMO Academy, Alibaba Group
+ Deep-FSMN for Large Vocabulary Continuous Speech Recognition
+ https://arxiv.org/abs/1803.05030
+ """
def __init__(
self,
sample_rate: int = 16000,
@@ -99,6 +104,11 @@
class E2EVadSpeechBufWithDoa(object):
+ """
+ Author: Speech Lab of DAMO Academy, Alibaba Group
+ Deep-FSMN for Large Vocabulary Continuous Speech Recognition
+ https://arxiv.org/abs/1803.05030
+ """
def __init__(self):
self.start_ms = 0
self.end_ms = 0
@@ -117,6 +127,11 @@
class E2EVadFrameProb(object):
+ """
+ Author: Speech Lab of DAMO Academy, Alibaba Group
+ Deep-FSMN for Large Vocabulary Continuous Speech Recognition
+ https://arxiv.org/abs/1803.05030
+ """
def __init__(self):
self.noise_prob = 0.0
self.speech_prob = 0.0
@@ -126,6 +141,11 @@
class WindowDetector(object):
+ """
+ Author: Speech Lab of DAMO Academy, Alibaba Group
+ Deep-FSMN for Large Vocabulary Continuous Speech Recognition
+ https://arxiv.org/abs/1803.05030
+ """
def __init__(self, window_size_ms: int, sil_to_speech_time: int,
speech_to_sil_time: int, frame_size_ms: int):
self.window_size_ms = window_size_ms
@@ -192,6 +212,11 @@
class E2EVadModel(nn.Module):
+ """
+ Author: Speech Lab of DAMO Academy, Alibaba Group
+ Deep-FSMN for Large Vocabulary Continuous Speech Recognition
+ https://arxiv.org/abs/1803.05030
+ """
def __init__(self, encoder: FSMN, vad_post_args: Dict[str, Any], frontend=None):
super(E2EVadModel, self).__init__()
self.vad_opts = VADXOptions(**vad_post_args)
diff --git a/funasr/models/encoder/opennmt_encoders/conv_encoder.py b/funasr/models/encoder/opennmt_encoders/conv_encoder.py
index a33e0b7..eec854f 100644
--- a/funasr/models/encoder/opennmt_encoders/conv_encoder.py
+++ b/funasr/models/encoder/opennmt_encoders/conv_encoder.py
@@ -67,7 +67,7 @@
class ConvEncoder(AbsEncoder):
"""
- author: Speech Lab, Alibaba Group, China
+ Author: Speech Lab of DAMO Academy, Alibaba Group
Convolution encoder in OpenNMT framework
"""
diff --git a/funasr/models/encoder/opennmt_encoders/self_attention_encoder.py b/funasr/models/encoder/opennmt_encoders/self_attention_encoder.py
index cf77bce..db30f08 100644
--- a/funasr/models/encoder/opennmt_encoders/self_attention_encoder.py
+++ b/funasr/models/encoder/opennmt_encoders/self_attention_encoder.py
@@ -117,7 +117,7 @@
class SelfAttentionEncoder(AbsEncoder):
"""
- author: Speech Lab, Alibaba Group, China
+ Author: Speech Lab of DAMO Academy, Alibaba Group
Self attention encoder in OpenNMT framework
"""
diff --git a/funasr/models/encoder/sanm_encoder.py b/funasr/models/encoder/sanm_encoder.py
index 2a3a353..7ac9121 100644
--- a/funasr/models/encoder/sanm_encoder.py
+++ b/funasr/models/encoder/sanm_encoder.py
@@ -117,7 +117,7 @@
class SANMEncoder(AbsEncoder):
"""
- author: Speech Lab, Alibaba Group, China
+ Author: Speech Lab of DAMO Academy, Alibaba Group
San-m: Memory equipped self-attention for end-to-end speech recognition
https://arxiv.org/abs/2006.01713
@@ -549,7 +549,7 @@
class SANMEncoderChunkOpt(AbsEncoder):
"""
- author: Speech Lab, Alibaba Group, China
+ Author: Speech Lab of DAMO Academy, Alibaba Group
SCAMA: Streaming chunk-aware multihead attention for online end-to-end speech recognition
https://arxiv.org/abs/2006.01713
@@ -962,7 +962,7 @@
class SANMVadEncoder(AbsEncoder):
"""
- author: Speech Lab, Alibaba Group, China
+ Author: Speech Lab of DAMO Academy, Alibaba Group
"""
diff --git a/funasr/models/target_delay_transformer.py b/funasr/models/target_delay_transformer.py
index 8cd4357..e893c65 100644
--- a/funasr/models/target_delay_transformer.py
+++ b/funasr/models/target_delay_transformer.py
@@ -14,7 +14,7 @@
class TargetDelayTransformer(AbsPunctuation):
"""
- Author: Speech Lab, Alibaba Group, China
+ Author: Speech Lab of DAMO Academy, Alibaba Group
CT-Transformer: Controllable time-delay transformer for real-time punctuation prediction and disfluency detection
https://arxiv.org/pdf/2003.01309.pdf
"""
diff --git a/funasr/models/vad_realtime_transformer.py b/funasr/models/vad_realtime_transformer.py
index 3810672..fe298ce 100644
--- a/funasr/models/vad_realtime_transformer.py
+++ b/funasr/models/vad_realtime_transformer.py
@@ -12,7 +12,7 @@
class VadRealtimeTransformer(AbsPunctuation):
"""
- Author: Speech Lab, Alibaba Group, China
+ Author: Speech Lab of DAMO Academy, Alibaba Group
CT-Transformer: Controllable time-delay transformer for real-time punctuation prediction and disfluency detection
https://arxiv.org/pdf/2003.01309.pdf
"""
diff --git a/funasr/modules/streaming_utils/chunk_utilis.py b/funasr/modules/streaming_utils/chunk_utilis.py
index ea37c68..ed8b31e 100644
--- a/funasr/modules/streaming_utils/chunk_utilis.py
+++ b/funasr/modules/streaming_utils/chunk_utilis.py
@@ -11,7 +11,7 @@
class overlap_chunk():
"""
- author: Speech Lab, Alibaba Group, China
+ Author: Speech Lab of DAMO Academy, Alibaba Group
San-m: Memory equipped self-attention for end-to-end speech recognition
https://arxiv.org/abs/2006.01713
diff --git a/funasr/runtime/python/onnxruntime/demo_vad_offline.py b/funasr/runtime/python/onnxruntime/demo_vad_offline.py
index 69ca945..ea76ec3 100644
--- a/funasr/runtime/python/onnxruntime/demo_vad_offline.py
+++ b/funasr/runtime/python/onnxruntime/demo_vad_offline.py
@@ -1,5 +1,5 @@
import soundfile
-from funasr_onnx.vad_bin import Fsmn_vad
+from funasr_onnx import Fsmn_vad
model_dir = "/mnt/ailsa.zly/tfbase/espnet_work/FunASR_dev_zly/export/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch"
diff --git a/funasr/runtime/python/onnxruntime/demo_vad_online.py b/funasr/runtime/python/onnxruntime/demo_vad_online.py
index 15e62da..1ab4d9d 100644
--- a/funasr/runtime/python/onnxruntime/demo_vad_online.py
+++ b/funasr/runtime/python/onnxruntime/demo_vad_online.py
@@ -1,10 +1,10 @@
import soundfile
-from funasr_onnx.vad_online_bin import Fsmn_vad
+from funasr_onnx import Fsmn_vad_online
model_dir = "/mnt/ailsa.zly/tfbase/espnet_work/FunASR_dev_zly/export/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch"
wav_path = "/mnt/ailsa.zly/tfbase/espnet_work/FunASR_dev_zly/egs_modelscope/vad/speech_fsmn_vad_zh-cn-16k-common/vad_example_16k.wav"
-model = Fsmn_vad(model_dir)
+model = Fsmn_vad_online(model_dir)
##online vad
diff --git a/funasr/runtime/python/onnxruntime/funasr_onnx/__init__.py b/funasr/runtime/python/onnxruntime/funasr_onnx/__init__.py
index 86f0e8e..7d8d662 100644
--- a/funasr/runtime/python/onnxruntime/funasr_onnx/__init__.py
+++ b/funasr/runtime/python/onnxruntime/funasr_onnx/__init__.py
@@ -1,5 +1,6 @@
# -*- encoding: utf-8 -*-
from .paraformer_bin import Paraformer
from .vad_bin import Fsmn_vad
+from .vad_bin import Fsmn_vad_online
from .punc_bin import CT_Transformer
from .punc_bin import CT_Transformer_VadRealtime
diff --git a/funasr/runtime/python/onnxruntime/funasr_onnx/punc_bin.py b/funasr/runtime/python/onnxruntime/funasr_onnx/punc_bin.py
index 2f1b3b7..bbbb913 100644
--- a/funasr/runtime/python/onnxruntime/funasr_onnx/punc_bin.py
+++ b/funasr/runtime/python/onnxruntime/funasr_onnx/punc_bin.py
@@ -14,7 +14,7 @@
class CT_Transformer():
"""
- Author: Speech Lab, Alibaba Group, China
+ Author: Speech Lab of DAMO Academy, Alibaba Group
CT-Transformer: Controllable time-delay transformer for real-time punctuation prediction and disfluency detection
https://arxiv.org/pdf/2003.01309.pdf
"""
@@ -125,7 +125,7 @@
class CT_Transformer_VadRealtime(CT_Transformer):
"""
- Author: Speech Lab, Alibaba Group, China
+ Author: Speech Lab of DAMO Academy, Alibaba Group
CT-Transformer: Controllable time-delay transformer for real-time punctuation prediction and disfluency detection
https://arxiv.org/pdf/2003.01309.pdf
"""
diff --git a/funasr/runtime/python/onnxruntime/funasr_onnx/vad_bin.py b/funasr/runtime/python/onnxruntime/funasr_onnx/vad_bin.py
index 5ad4266..ab8f041 100644
--- a/funasr/runtime/python/onnxruntime/funasr_onnx/vad_bin.py
+++ b/funasr/runtime/python/onnxruntime/funasr_onnx/vad_bin.py
@@ -11,13 +11,18 @@
from .utils.utils import (ONNXRuntimeError,
OrtInferSession, get_logger,
read_yaml)
-from .utils.frontend import WavFrontend
+from .utils.frontend import WavFrontend, WavFrontendOnline
from .utils.e2e_vad import E2EVadModel
logging = get_logger()
class Fsmn_vad():
+ """
+ Author: Speech Lab of DAMO Academy, Alibaba Group
+ Deep-FSMN for Large Vocabulary Continuous Speech Recognition
+ https://arxiv.org/abs/1803.05030
+ """
def __init__(self, model_dir: Union[str, Path] = None,
batch_size: int = 1,
device_id: Union[str, int] = "-1",
@@ -151,4 +156,125 @@
outputs = self.ort_infer(feats)
scores, out_caches = outputs[0], outputs[1:]
return scores, out_caches
+
+
+class Fsmn_vad_online():
+ """
+ Author: Speech Lab of DAMO Academy, Alibaba Group
+ Deep-FSMN for Large Vocabulary Continuous Speech Recognition
+ https://arxiv.org/abs/1803.05030
+ """
+ def __init__(self, model_dir: Union[str, Path] = None,
+ batch_size: int = 1,
+ device_id: Union[str, int] = "-1",
+ quantize: bool = False,
+ intra_op_num_threads: int = 4,
+ max_end_sil: int = None,
+ ):
+
+ if not Path(model_dir).exists():
+ raise FileNotFoundError(f'{model_dir} does not exist.')
+
+ model_file = os.path.join(model_dir, 'model.onnx')
+ if quantize:
+ model_file = os.path.join(model_dir, 'model_quant.onnx')
+ config_file = os.path.join(model_dir, 'vad.yaml')
+ cmvn_file = os.path.join(model_dir, 'vad.mvn')
+ config = read_yaml(config_file)
+
+ self.frontend = WavFrontendOnline(
+ cmvn_file=cmvn_file,
+ **config['frontend_conf']
+ )
+ self.ort_infer = OrtInferSession(model_file, device_id, intra_op_num_threads=intra_op_num_threads)
+ self.batch_size = batch_size
+ self.vad_scorer = E2EVadModel(config["vad_post_conf"])
+ self.max_end_sil = max_end_sil if max_end_sil is not None else config["vad_post_conf"]["max_end_silence_time"]
+ self.encoder_conf = config["encoder_conf"]
+ def prepare_cache(self, in_cache: list = []):
+ if len(in_cache) > 0:
+ return in_cache
+ fsmn_layers = self.encoder_conf["fsmn_layers"]
+ proj_dim = self.encoder_conf["proj_dim"]
+ lorder = self.encoder_conf["lorder"]
+ for i in range(fsmn_layers):
+ cache = np.zeros((1, proj_dim, lorder - 1, 1)).astype(np.float32)
+ in_cache.append(cache)
+ return in_cache
+
+ def __call__(self, audio_in: np.ndarray, **kwargs) -> List:
+ waveforms = np.expand_dims(audio_in, axis=0)
+
+ param_dict = kwargs.get('param_dict', dict())
+ is_final = param_dict.get('is_final', False)
+ feats, feats_len = self.extract_feat(waveforms, is_final)
+ segments = []
+ if feats.size != 0:
+ in_cache = param_dict.get('in_cache', list())
+ in_cache = self.prepare_cache(in_cache)
+ try:
+ inputs = [feats]
+ inputs.extend(in_cache)
+ scores, out_caches = self.infer(inputs)
+ param_dict['in_cache'] = out_caches
+ waveforms = self.frontend.get_waveforms()
+ segments = self.vad_scorer(scores, waveforms, is_final=is_final, max_end_sil=self.max_end_sil,
+ online=True)
+
+
+ except ONNXRuntimeError:
+ # logging.warning(traceback.format_exc())
+ logging.warning("input wav is silence or noise")
+ segments = []
+ return segments
+
+ def load_data(self,
+ wav_content: Union[str, np.ndarray, List[str]], fs: int = None) -> List:
+ def load_wav(path: str) -> np.ndarray:
+ waveform, _ = librosa.load(path, sr=fs)
+ return waveform
+
+ if isinstance(wav_content, np.ndarray):
+ return [wav_content]
+
+ if isinstance(wav_content, str):
+ return [load_wav(wav_content)]
+
+ if isinstance(wav_content, list):
+ return [load_wav(path) for path in wav_content]
+
+ raise TypeError(
+ f'The type of {wav_content} is not in [str, np.ndarray, list]')
+
+ def extract_feat(self,
+ waveforms: np.ndarray, is_final: bool = False
+ ) -> Tuple[np.ndarray, np.ndarray]:
+ waveforms_lens = np.zeros(waveforms.shape[0]).astype(np.int32)
+ for idx, waveform in enumerate(waveforms):
+ waveforms_lens[idx] = waveform.shape[-1]
+
+ feats, feats_len = self.frontend.extract_fbank(waveforms, waveforms_lens, is_final)
+ # feats.append(feat)
+ # feats_len.append(feat_len)
+
+ # feats = self.pad_feats(feats, np.max(feats_len))
+ # feats_len = np.array(feats_len).astype(np.int32)
+ return feats.astype(np.float32), feats_len.astype(np.int32)
+
+ @staticmethod
+ def pad_feats(feats: List[np.ndarray], max_feat_len: int) -> np.ndarray:
+ def pad_feat(feat: np.ndarray, cur_len: int) -> np.ndarray:
+ pad_width = ((0, max_feat_len - cur_len), (0, 0))
+ return np.pad(feat, pad_width, 'constant', constant_values=0)
+
+ feat_res = [pad_feat(feat, feat.shape[0]) for feat in feats]
+ feats = np.array(feat_res).astype(np.float32)
+ return feats
+
+ def infer(self, feats: List) -> Tuple[np.ndarray, np.ndarray]:
+
+ outputs = self.ort_infer(feats)
+ scores, out_caches = outputs[0], outputs[1:]
+ return scores, out_caches
+
diff --git a/funasr/runtime/python/onnxruntime/funasr_onnx/vad_online_bin.py b/funasr/runtime/python/onnxruntime/funasr_onnx/vad_online_bin.py
deleted file mode 100644
index 83e9420..0000000
--- a/funasr/runtime/python/onnxruntime/funasr_onnx/vad_online_bin.py
+++ /dev/null
@@ -1,134 +0,0 @@
-# -*- encoding: utf-8 -*-
-
-import os.path
-from pathlib import Path
-from typing import List, Union, Tuple
-
-import copy
-import librosa
-import numpy as np
-
-from .utils.utils import (ONNXRuntimeError,
- OrtInferSession, get_logger,
- read_yaml)
-from .utils.frontend import WavFrontendOnline
-from .utils.e2e_vad import E2EVadModel
-
-logging = get_logger()
-
-
-class Fsmn_vad():
- def __init__(self, model_dir: Union[str, Path] = None,
- batch_size: int = 1,
- device_id: Union[str, int] = "-1",
- quantize: bool = False,
- intra_op_num_threads: int = 4,
- max_end_sil: int = None,
- ):
-
- if not Path(model_dir).exists():
- raise FileNotFoundError(f'{model_dir} does not exist.')
-
- model_file = os.path.join(model_dir, 'model.onnx')
- if quantize:
- model_file = os.path.join(model_dir, 'model_quant.onnx')
- config_file = os.path.join(model_dir, 'vad.yaml')
- cmvn_file = os.path.join(model_dir, 'vad.mvn')
- config = read_yaml(config_file)
-
- self.frontend = WavFrontendOnline(
- cmvn_file=cmvn_file,
- **config['frontend_conf']
- )
- self.ort_infer = OrtInferSession(model_file, device_id, intra_op_num_threads=intra_op_num_threads)
- self.batch_size = batch_size
- self.vad_scorer = E2EVadModel(config["vad_post_conf"])
- self.max_end_sil = max_end_sil if max_end_sil is not None else config["vad_post_conf"]["max_end_silence_time"]
- self.encoder_conf = config["encoder_conf"]
-
- def prepare_cache(self, in_cache: list = []):
- if len(in_cache) > 0:
- return in_cache
- fsmn_layers = self.encoder_conf["fsmn_layers"]
- proj_dim = self.encoder_conf["proj_dim"]
- lorder = self.encoder_conf["lorder"]
- for i in range(fsmn_layers):
- cache = np.zeros((1, proj_dim, lorder-1, 1)).astype(np.float32)
- in_cache.append(cache)
- return in_cache
-
-
- def __call__(self, audio_in: np.ndarray, **kwargs) -> List:
- waveforms = np.expand_dims(audio_in, axis=0)
-
- param_dict = kwargs.get('param_dict', dict())
- is_final = param_dict.get('is_final', False)
- feats, feats_len = self.extract_feat(waveforms, is_final)
- segments = []
- if feats.size != 0:
- in_cache = param_dict.get('in_cache', list())
- in_cache = self.prepare_cache(in_cache)
- try:
- inputs = [feats]
- inputs.extend(in_cache)
- scores, out_caches = self.infer(inputs)
- param_dict['in_cache'] = out_caches
- waveforms = self.frontend.get_waveforms()
- segments = self.vad_scorer(scores, waveforms, is_final=is_final, max_end_sil=self.max_end_sil, online=True)
-
-
- except ONNXRuntimeError:
- logging.warning(traceback.format_exc())
- logging.warning("input wav is silence or noise")
- segments = []
- return segments
-
- def load_data(self,
- wav_content: Union[str, np.ndarray, List[str]], fs: int = None) -> List:
- def load_wav(path: str) -> np.ndarray:
- waveform, _ = librosa.load(path, sr=fs)
- return waveform
-
- if isinstance(wav_content, np.ndarray):
- return [wav_content]
-
- if isinstance(wav_content, str):
- return [load_wav(wav_content)]
-
- if isinstance(wav_content, list):
- return [load_wav(path) for path in wav_content]
-
- raise TypeError(
- f'The type of {wav_content} is not in [str, np.ndarray, list]')
-
- def extract_feat(self,
- waveforms: np.ndarray, is_final: bool = False
- ) -> Tuple[np.ndarray, np.ndarray]:
- waveforms_lens = np.zeros(waveforms.shape[0]).astype(np.int32)
- for idx, waveform in enumerate(waveforms):
- waveforms_lens[idx] = waveform.shape[-1]
-
- feats, feats_len = self.frontend.extract_fbank(waveforms, waveforms_lens, is_final)
- # feats.append(feat)
- # feats_len.append(feat_len)
-
- # feats = self.pad_feats(feats, np.max(feats_len))
- # feats_len = np.array(feats_len).astype(np.int32)
- return feats.astype(np.float32), feats_len.astype(np.int32)
-
- @staticmethod
- def pad_feats(feats: List[np.ndarray], max_feat_len: int) -> np.ndarray:
- def pad_feat(feat: np.ndarray, cur_len: int) -> np.ndarray:
- pad_width = ((0, max_feat_len - cur_len), (0, 0))
- return np.pad(feat, pad_width, 'constant', constant_values=0)
-
- feat_res = [pad_feat(feat, feat.shape[0]) for feat in feats]
- feats = np.array(feat_res).astype(np.float32)
- return feats
-
- def infer(self, feats: List) -> Tuple[np.ndarray, np.ndarray]:
-
- outputs = self.ort_infer(feats)
- scores, out_caches = outputs[0], outputs[1:]
- return scores, out_caches
-
diff --git a/funasr/runtime/python/onnxruntime/setup.py b/funasr/runtime/python/onnxruntime/setup.py
index 1a8ed7b..1e1c6b1 100644
--- a/funasr/runtime/python/onnxruntime/setup.py
+++ b/funasr/runtime/python/onnxruntime/setup.py
@@ -13,7 +13,7 @@
MODULE_NAME = 'funasr_onnx'
-VERSION_NUM = '0.0.3'
+VERSION_NUM = '0.0.4'
setuptools.setup(
name=MODULE_NAME,
--
Gitblit v1.9.1