From f57b68121a526baea43b2e93f4540d8a2995f633 Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期一, 29 四月 2024 15:15:24 +0800
Subject: [PATCH] batch

---
 funasr/auto/auto_frontend.py |   41 ++++++++++++++++++++++-------------------
 1 files changed, 22 insertions(+), 19 deletions(-)

diff --git a/funasr/auto/auto_frontend.py b/funasr/auto/auto_frontend.py
index b802b83..b8fa7e0 100644
--- a/funasr/auto/auto_frontend.py
+++ b/funasr/auto/auto_frontend.py
@@ -33,7 +33,7 @@
         if "model_conf" not in kwargs:
             logging.info("download models from model hub: {}".format(kwargs.get("hub", "ms")))
             kwargs = download_model(**kwargs)
-        
+
         # build frontend
         frontend = kwargs.get("frontend", None)
         if frontend is not None:
@@ -45,25 +45,23 @@
             del kwargs["frontend"]
         self.kwargs = kwargs
 
-    
     def __call__(self, input, input_len=None, kwargs=None, **cfg):
-        
+
         kwargs = self.kwargs if kwargs is None else kwargs
         kwargs.update(cfg)
-
 
         key_list, data_list = prepare_data_iterator(input, input_len=input_len)
         batch_size = kwargs.get("batch_size", 1)
         device = kwargs.get("device", "cpu")
         if device == "cpu":
             batch_size = 1
-        
+
         meta_data = {}
-        
+
         result_list = []
         num_samples = len(data_list)
         pbar = tqdm(colour="blue", total=num_samples + 1, dynamic_ncols=True)
-        
+
         time0 = time.perf_counter()
         for beg_idx in range(0, num_samples, batch_size):
             end_idx = min(num_samples, beg_idx + batch_size)
@@ -72,27 +70,32 @@
 
             # extract fbank feats
             time1 = time.perf_counter()
-            audio_sample_list = load_audio_text_image_video(data_batch, fs=self.frontend.fs, audio_fs=kwargs.get("fs", 16000))
+            audio_sample_list = load_audio_text_image_video(
+                data_batch, fs=self.frontend.fs, audio_fs=kwargs.get("fs", 16000)
+            )
             time2 = time.perf_counter()
             meta_data["load_data"] = f"{time2 - time1:0.3f}"
-            speech, speech_lengths = extract_fbank(audio_sample_list, data_type=kwargs.get("data_type", "sound"),
-                                                   frontend=self.frontend, **kwargs)
+            speech, speech_lengths = extract_fbank(
+                audio_sample_list,
+                data_type=kwargs.get("data_type", "sound"),
+                frontend=self.frontend,
+                **kwargs,
+            )
             time3 = time.perf_counter()
             meta_data["extract_feat"] = f"{time3 - time2:0.3f}"
-            meta_data["batch_data_time"] = speech_lengths.sum().item() * self.frontend.frame_shift * self.frontend.lfr_n / 1000
-            
+            meta_data["batch_data_time"] = (
+                speech_lengths.sum().item() * self.frontend.frame_shift * self.frontend.lfr_n / 1000
+            )
+
             speech.to(device=device), speech_lengths.to(device=device)
             batch = {"input": speech, "input_len": speech_lengths, "key": key_batch}
             result_list.append(batch)
-            
+
             pbar.update(1)
-            description = (
-                f"{meta_data}, "
-            )
+            description = f"{meta_data}, "
             pbar.set_description(description)
-        
+
         time_end = time.perf_counter()
         pbar.set_description(f"time escaped total: {time_end - time0:0.3f}")
-        
-        return result_list
 
+        return result_list

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