From d80ac2fd2df4e7fb8a28acfa512bb11472b5cc99 Mon Sep 17 00:00:00 2001
From: liugz18 <57401541+liugz18@users.noreply.github.com>
Date: 星期四, 18 七月 2024 21:34:55 +0800
Subject: [PATCH] Rename 'res' in line 514 to avoid with naming conflict with line 365

---
 funasr/auto/auto_model.py |   30 +++++++++++++++++++-----------
 1 files changed, 19 insertions(+), 11 deletions(-)

diff --git a/funasr/auto/auto_model.py b/funasr/auto/auto_model.py
index 01e6aaf..75324dc 100644
--- a/funasr/auto/auto_model.py
+++ b/funasr/auto/auto_model.py
@@ -20,7 +20,7 @@
 from funasr.download.file import download_from_url
 from funasr.utils.timestamp_tools import timestamp_sentence
 from funasr.utils.timestamp_tools import timestamp_sentence_en
-from funasr.download.download_from_hub import download_model
+from funasr.download.download_model_from_hub import download_model
 from funasr.utils.vad_utils import slice_padding_audio_samples
 from funasr.utils.vad_utils import merge_vad
 from funasr.utils.load_utils import load_audio_text_image_video
@@ -121,9 +121,6 @@
         log_level = getattr(logging, kwargs.get("log_level", "INFO").upper())
         logging.basicConfig(level=log_level)
 
-        if not kwargs.get("disable_log", True):
-            tables.print()
-
         model, kwargs = self.build_model(**kwargs)
 
         # if vad_model is not None, build vad model else None
@@ -171,7 +168,8 @@
         self.spk_kwargs = spk_kwargs
         self.model_path = kwargs.get("model_path")
 
-    def build_model(self, **kwargs):
+    @staticmethod
+    def build_model(**kwargs):
         assert "model" in kwargs
         if "model_conf" not in kwargs:
             logging.info("download models from model hub: {}".format(kwargs.get("hub", "ms")))
@@ -217,6 +215,7 @@
         kwargs["frontend"] = frontend
         # build model
         model_class = tables.model_classes.get(kwargs["model"])
+        assert model_class is not None, f'{kwargs["model"]} is not registered'
         model_conf = {}
         deep_update(model_conf, kwargs.get("model_conf", {}))
         deep_update(model_conf, kwargs)
@@ -244,6 +243,10 @@
         elif kwargs.get("bf16", False):
             model.to(torch.bfloat16)
         model.to(device)
+
+        if not kwargs.get("disable_log", True):
+            tables.print()
+
         return model, kwargs
 
     def __call__(self, *args, **cfg):
@@ -312,7 +315,7 @@
             speed_stats["rtf"] = f"{(time_escape) / batch_data_time:0.3f}"
             description = f"{speed_stats}, "
             if pbar:
-                pbar.update(1)
+                pbar.update(end_idx - beg_idx)
                 pbar.set_description(description)
             time_speech_total += batch_data_time
             time_escape_total += time_escape
@@ -336,7 +339,9 @@
         #  FIX(gcf): concat the vad clips for sense vocie model for better aed
         if kwargs.get("merge_vad", False):
             for i in range(len(res)):
-                res[i]["value"] = merge_vad(res[i]["value"], kwargs.get("merge_length", 15000))
+                res[i]["value"] = merge_vad(
+                    res[i]["value"], kwargs.get("merge_length_s", 15) * 1000
+                )
 
         # step.2 compute asr model
         model = self.model
@@ -376,6 +381,9 @@
 
             if len(sorted_data) > 0 and len(sorted_data[0]) > 0:
                 batch_size = max(batch_size, sorted_data[0][0][1] - sorted_data[0][0][0])
+
+            if kwargs["device"] == "cpu":
+                batch_size = 0
 
             beg_idx = 0
             beg_asr_total = time.time()
@@ -503,8 +511,8 @@
                 sv_output = postprocess(all_segments, None, labels, spk_embedding.cpu())
                 if self.spk_mode == "vad_segment":  # recover sentence_list
                     sentence_list = []
-                    for res, vadsegment in zip(restored_data, vadsegments):
-                        if "timestamp" not in res:
+                    for rest, vadsegment in zip(restored_data, vadsegments):
+                        if "timestamp" not in rest:
                             logging.error(
                                 "Only 'iic/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch' \
                                            and 'iic/speech_seaco_paraformer_large_asr_nat-zh-cn-16k-common-vocab8404-pytorch'\
@@ -514,8 +522,8 @@
                             {
                                 "start": vadsegment[0],
                                 "end": vadsegment[1],
-                                "sentence": res["text"],
-                                "timestamp": res["timestamp"],
+                                "sentence": rest["text"],
+                                "timestamp": rest["timestamp"],
                             }
                         )
                 elif self.spk_mode == "punc_segment":

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