From 3cd3473bf7a3b41484baa86d9092248d78e7af39 Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期五, 21 四月 2023 17:17:37 +0800
Subject: [PATCH] docs
---
funasr/bin/tp_inference.py | 11 +++++++----
1 files changed, 7 insertions(+), 4 deletions(-)
diff --git a/funasr/bin/tp_inference.py b/funasr/bin/tp_inference.py
index 8c9c0f3..df029fd 100644
--- a/funasr/bin/tp_inference.py
+++ b/funasr/bin/tp_inference.py
@@ -18,7 +18,7 @@
from funasr.fileio.datadir_writer import DatadirWriter
from funasr.datasets.preprocessor import LMPreprocessor
-from funasr.tasks.asr import ASRTaskAligner_temp as ASRTask
+from funasr.tasks.asr import ASRTaskAligner as ASRTask
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
@@ -54,7 +54,7 @@
assert check_argument_types()
# 1. Build ASR model
tp_model, tp_train_args = ASRTask.build_model_from_file(
- timestamp_infer_config, timestamp_model_file, device
+ timestamp_infer_config, timestamp_model_file, device=device
)
if 'cuda' in device:
tp_model = tp_model.cuda() # force model to cuda
@@ -116,8 +116,8 @@
enc = enc[0]
# c. Forward Predictor
- _, _, us_alphas, us_cif_peak = self.tp_model.calc_predictor_timestamp(enc, enc_len, text_lengths.to(self.device)+1)
- return us_alphas, us_cif_peak
+ _, _, us_alphas, us_peaks = self.tp_model.calc_predictor_timestamp(enc, enc_len, text_lengths.to(self.device)+1)
+ return us_alphas, us_peaks
def inference(
@@ -179,6 +179,9 @@
**kwargs,
):
assert check_argument_types()
+ ncpu = kwargs.get("ncpu", 1)
+ torch.set_num_threads(ncpu)
+
if batch_size > 1:
raise NotImplementedError("batch decoding is not implemented")
if ngpu > 1:
--
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