From c3442d9566f5a2011c95b0d2998958a1b5348564 Mon Sep 17 00:00:00 2001
From: shixian.shi <shixian.shi@alibaba-inc.com>
Date: 星期五, 12 一月 2024 18:04:42 +0800
Subject: [PATCH] update device

---
 funasr/models/monotonic_aligner/model.py |   27 ++++++++++++---------------
 1 files changed, 12 insertions(+), 15 deletions(-)

diff --git a/funasr/models/monotonic_aligner/model.py b/funasr/models/monotonic_aligner/model.py
index ece319d..584b692 100644
--- a/funasr/models/monotonic_aligner/model.py
+++ b/funasr/models/monotonic_aligner/model.py
@@ -5,17 +5,15 @@
 from typing import Union, Dict, List, Tuple, Optional
 
 from funasr.models.paraformer.cif_predictor import mae_loss
-from funasr.models.transformer.utils.add_sos_eos import add_sos_eos
-from funasr.models.transformer.utils.nets_utils import make_pad_mask, pad_list
-from funasr.metrics.compute_acc import th_accuracy
 from funasr.train_utils.device_funcs import force_gatherable
+from funasr.models.transformer.utils.add_sos_eos import add_sos_eos
+from funasr.models.transformer.utils.nets_utils import make_pad_mask
 from funasr.utils.timestamp_tools import ts_prediction_lfr6_standard
 from funasr.utils import postprocess_utils
 from funasr.utils.datadir_writer import DatadirWriter
 from funasr.register import tables
 from funasr.models.ctc.ctc import CTC
-from funasr.utils.load_utils import load_audio_and_text_image_video, extract_fbank
-
+from funasr.utils.load_utils import load_audio_text_image_video, extract_fbank
 
 
 @tables.register("model_classes", "monotonicaligner")
@@ -25,7 +23,6 @@
     Achieving timestamp prediction while recognizing with non-autoregressive end-to-end ASR model
     https://arxiv.org/abs/2301.12343
     """
-
     def __init__(
         self,
         input_size: int = 80,
@@ -41,7 +38,6 @@
         length_normalized_loss: bool = False,
         **kwargs,
     ):
-
         super().__init__()
 
         if specaug is not None:
@@ -155,11 +151,10 @@
              frontend=None,
              **kwargs,
              ):
-        
         meta_data = {}
         # extract fbank feats
         time1 = time.perf_counter()
-        audio_list, text_token_int_list = load_audio_and_text_image_video(data_in, 
+        audio_list, text_token_int_list = load_audio_text_image_video(data_in, 
                                                                             fs=frontend.fs, 
                                                                             audio_fs=kwargs.get("fs", 16000), 
                                                                             data_type=kwargs.get("data_type", "sound"), 
@@ -190,13 +185,15 @@
             timestamp_str, timestamp = ts_prediction_lfr6_standard(us_alpha[:encoder_out_lens[i] * 3],
                                                                    us_peak[:encoder_out_lens[i] * 3],
                                                                    copy.copy(token))
-            text_postprocessed, time_stamp_postprocessed, word_lists = postprocess_utils.sentence_postprocess(
-                token, timestamp)
+            text_postprocessed, time_stamp_postprocessed, _ = postprocess_utils.sentence_postprocess(token, timestamp)
             result_i = {"key": key[i], "text": text_postprocessed,
                                 "timestamp": time_stamp_postprocessed,
-                                }    
-            # ibest_writer["token"][key[i]] = " ".join(token)
-            ibest_writer["timestamp_list"][key[i]] = time_stamp_postprocessed
-            ibest_writer["timestamp_str"][key[i]] = timestamp_str
+                                }
             results.append(result_i)
+
+            if ibest_writer:
+                # ibest_writer["token"][key[i]] = " ".join(token)
+                ibest_writer["timestamp_list"][key[i]] = time_stamp_postprocessed
+                ibest_writer["timestamp_str"][key[i]] = timestamp_str
+            
         return results, meta_data
\ No newline at end of file

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