From 98abc0e5ac1a1da0fe1802d9ffb623802fbf0b2f Mon Sep 17 00:00:00 2001
From: jmwang66 <wangjiaming.wjm@alibaba-inc.com>
Date: 星期四, 29 六月 2023 16:30:39 +0800
Subject: [PATCH] update setup (#686)
---
funasr/bin/asr_infer.py | 52 +---------------------------------------------------
1 files changed, 1 insertions(+), 51 deletions(-)
diff --git a/funasr/bin/asr_infer.py b/funasr/bin/asr_infer.py
index a537a73..259a286 100644
--- a/funasr/bin/asr_infer.py
+++ b/funasr/bin/asr_infer.py
@@ -22,9 +22,7 @@
import requests
import torch
from packaging.version import parse as V
-from typeguard import check_argument_types
-from typeguard import check_return_type
-from funasr.build_utils.build_model_from_file import build_model_from_file
+from funasr.build_utils.build_model_from_file import build_model_from_file
from funasr.models.e2e_asr_contextual_paraformer import NeatContextualParaformer
from funasr.models.e2e_asr_paraformer import BiCifParaformer, ContextualParaformer
from funasr.models.frontend.wav_frontend import WavFrontend, WavFrontendOnline
@@ -78,7 +76,6 @@
frontend_conf: dict = None,
**kwargs,
):
- assert check_argument_types()
# 1. Build ASR model
scorers = {}
@@ -192,7 +189,6 @@
text, token, token_int, hyp
"""
- assert check_argument_types()
# Input as audio signal
if isinstance(speech, np.ndarray):
@@ -248,7 +244,6 @@
text = None
results.append((text, token, token_int, hyp))
- assert check_return_type(results)
return results
@@ -288,7 +283,6 @@
decoding_ind: int = 0,
**kwargs,
):
- assert check_argument_types()
# 1. Build ASR model
scorers = {}
@@ -413,7 +407,6 @@
text, token, token_int, hyp
"""
- assert check_argument_types()
# Input as audio signal
if isinstance(speech, np.ndarray):
@@ -516,7 +509,6 @@
vad_offset=begin_time)
results.append((text, token, token_int, hyp, timestamp, enc_len_batch_total, lfr_factor))
- # assert check_return_type(results)
return results
def generate_hotwords_list(self, hotword_list_or_file):
@@ -656,7 +648,6 @@
hotword_list_or_file: str = None,
**kwargs,
):
- assert check_argument_types()
# 1. Build ASR model
scorers = {}
@@ -776,7 +767,6 @@
text, token, token_int, hyp
"""
- assert check_argument_types()
results = []
cache_en = cache["encoder"]
if speech.shape[1] < 16 * 60 and cache_en["is_final"]:
@@ -871,7 +861,6 @@
results.append(postprocessed_result)
- # assert check_return_type(results)
return results
@@ -912,7 +901,6 @@
frontend_conf: dict = None,
**kwargs,
):
- assert check_argument_types()
# 1. Build ASR model
scorers = {}
@@ -1036,7 +1024,6 @@
text, token, token_int, hyp
"""
- assert check_argument_types()
# Input as audio signal
if isinstance(speech, np.ndarray):
@@ -1104,7 +1091,6 @@
text = None
results.append((text, token, token_int, hyp))
- assert check_return_type(results)
return results
@@ -1143,7 +1129,6 @@
streaming: bool = False,
**kwargs,
):
- assert check_argument_types()
# 1. Build ASR model
scorers = {}
@@ -1248,7 +1233,6 @@
text, token, token_int, hyp
"""
- assert check_argument_types()
# Input as audio signal
if isinstance(speech, np.ndarray):
speech = torch.tensor(speech)
@@ -1298,7 +1282,6 @@
text = None
results.append((text, token, token_int, hyp))
- assert check_return_type(results)
return results
@@ -1355,7 +1338,6 @@
"""Construct a Speech2Text object."""
super().__init__()
- assert check_argument_types()
asr_model, asr_train_args = build_model_from_file(
asr_train_config, asr_model_file, cmvn_file, device
)
@@ -1534,7 +1516,6 @@
Returns:
nbest_hypothesis: N-best hypothesis.
"""
- assert check_argument_types()
if isinstance(speech, np.ndarray):
speech = torch.tensor(speech)
@@ -1566,7 +1547,6 @@
Returns:
nbest_hypothesis: N-best hypothesis.
"""
- assert check_argument_types()
if isinstance(speech, np.ndarray):
speech = torch.tensor(speech)
@@ -1608,35 +1588,8 @@
text = None
results.append((text, token, token_int, hyp))
- assert check_return_type(results)
return results
-
- @staticmethod
- def from_pretrained(
- model_tag: Optional[str] = None,
- **kwargs: Optional[Any],
- ) -> Speech2Text:
- """Build Speech2Text instance from the pretrained model.
- Args:
- model_tag: Model tag of the pretrained models.
- Return:
- : Speech2Text instance.
- """
- if model_tag is not None:
- try:
- from espnet_model_zoo.downloader import ModelDownloader
-
- except ImportError:
- logging.error(
- "`espnet_model_zoo` is not installed. "
- "Please install via `pip install -U espnet_model_zoo`."
- )
- raise
- d = ModelDownloader()
- kwargs.update(**d.download_and_unpack(model_tag))
-
- return Speech2TextTransducer(**kwargs)
class Speech2TextSAASR:
@@ -1675,7 +1628,6 @@
frontend_conf: dict = None,
**kwargs,
):
- assert check_argument_types()
# 1. Build ASR model
scorers = {}
@@ -1793,7 +1745,6 @@
text, text_id, token, token_int, hyp
"""
- assert check_argument_types()
# Input as audio signal
if isinstance(speech, np.ndarray):
@@ -1886,5 +1837,4 @@
results.append((text, text_id, token, token_int, hyp))
- assert check_return_type(results)
return results
--
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