Format code (#188)

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

config.py

@@ -68,21 +68,39 @@ gpu_mem=None
 if device not in ["cpu", "mps"]:
     i_device = int(device.split(":")[-1])
     gpu_name = torch.cuda.get_device_name(i_device)
-    if "16" in gpu_name or "P40"in gpu_name.upper() or "1070"in gpu_name or "1080"in gpu_name:
+    if (
+        "16" in gpu_name
+        or "P40" in gpu_name.upper()
+        or "1070" in gpu_name
+        or "1080" in gpu_name
+    ):
         print("16系显卡强制单精度")
         is_half = False
-        with open("configs/32k.json","r")as f:strr=f.read().replace("true","false")
+        with open("configs/32k.json", "r") as f:
-        with open("configs/32k.json","w")as f:f.write(strr)
+            strr = f.read().replace("true", "false")
-        with open("configs/40k.json","r")as f:strr=f.read().replace("true","false")
+        with open("configs/32k.json", "w") as f:
-        with open("configs/40k.json","w")as f:f.write(strr)
+            f.write(strr)
-        with open("configs/48k.json","r")as f:strr=f.read().replace("true","false")
+        with open("configs/40k.json", "r") as f:
-        with open("configs/48k.json","w")as f:f.write(strr)
+            strr = f.read().replace("true", "false")
-        with open("trainset_preprocess_pipeline_print.py","r")as f:strr=f.read().replace("3.7","3.0")
+        with open("configs/40k.json", "w") as f:
-        with open("trainset_preprocess_pipeline_print.py","w")as f:f.write(strr)
+            f.write(strr)
-    gpu_mem=int(torch.cuda.get_device_properties(i_device).total_memory/1024/1024/1024+0.4)
+        with open("configs/48k.json", "r") as f:
-    if(gpu_mem<=4):
+            strr = f.read().replace("true", "false")
-        with open("trainset_preprocess_pipeline_print.py","r")as f:strr=f.read().replace("3.7","3.0")
+        with open("configs/48k.json", "w") as f:
-        with open("trainset_preprocess_pipeline_print.py","w")as f:f.write(strr)
+            f.write(strr)
+        with open("trainset_preprocess_pipeline_print.py", "r") as f:
+            strr = f.read().replace("3.7", "3.0")
+        with open("trainset_preprocess_pipeline_print.py", "w") as f:
+            f.write(strr)
+    gpu_mem = int(
+        torch.cuda.get_device_properties(i_device).total_memory / 1024 / 1024 / 1024
+        + 0.4
+    )
+    if gpu_mem <= 4:
+        with open("trainset_preprocess_pipeline_print.py", "r") as f:
+            strr = f.read().replace("3.7", "3.0")
+        with open("trainset_preprocess_pipeline_print.py", "w") as f:
+            f.write(strr)
 from multiprocessing import cpu_count
 
 if n_cpu == 0:
@@ -99,7 +117,7 @@ else:
     x_query = 6
     x_center = 38
     x_max = 41
-if(gpu_mem!=None and gpu_mem<=4):
+if gpu_mem != None and gpu_mem <= 4:
     x_pad = 1
     x_query = 5
     x_center = 30

gui.py

@@ -375,9 +375,7 @@ class GUI:
         self.crossfade_frame = int(self.config.crossfade_time * self.config.samplerate)
         self.sola_search_frame = int(0.012 * self.config.samplerate)
         self.delay_frame = int(0.01 * self.config.samplerate)  # 往前预留0.02s
-        self.extra_frame = int(
+        self.extra_frame = int(self.config.extra_time * self.config.samplerate)
-            self.config.extra_time * self.config.samplerate
-        )  
         self.rvc = None
         self.rvc = RVC(
             self.config.pitch,
@@ -408,7 +406,9 @@ class GUI:
             orig_freq=self.config.samplerate, new_freq=16000, dtype=torch.float32
         )
         self.resampler2 = tat.Resample(
-            orig_freq=self.rvc.tgt_sr, new_freq=self.config.samplerate, dtype=torch.float32
+            orig_freq=self.rvc.tgt_sr,
+            new_freq=self.config.samplerate,
+            dtype=torch.float32,
         )
         thread_vc = threading.Thread(target=self.soundinput)
         thread_vc.start()

infer-web.py

@@ -6,6 +6,7 @@ from time import sleep
 import torch, os, traceback, sys, warnings, shutil, numpy as np
 import faiss
 from random import shuffle
+
 now_dir = os.getcwd()
 sys.path.append(now_dir)
 tmp = os.path.join(now_dir, "TEMP")
@@ -50,7 +51,15 @@ else:
         ):  # A10#A100#V100#A40#P40#M40#K80#A4500
             if_gpu_ok = True  # 至少有一张能用的N卡
             gpu_infos.append("%s\t%s" % (i, gpu_name))
-            mem.append(int(torch.cuda.get_device_properties(i).total_memory/1024/1024/1024+0.4))
+            mem.append(
+                int(
+                    torch.cuda.get_device_properties(i).total_memory
+                    / 1024
+                    / 1024
+                    / 1024
+                    + 0.4
+                )
+            )
 if if_gpu_ok == True and len(gpu_infos) > 0:
     gpu_info = "\n".join(gpu_infos)
     default_batch_size = min(mem) // 2
@@ -262,19 +271,26 @@ def uvr(model_name, inp_root, save_root_vocal, paths, save_root_ins,agg):
             done = 0
             try:
                 info = ffmpeg.probe(inp_path, cmd="ffprobe")
-                if(info["streams"][0]["channels"]==2 and info["streams"][0]["sample_rate"]=="44100"):
+                if (
+                    info["streams"][0]["channels"] == 2
+                    and info["streams"][0]["sample_rate"] == "44100"
+                ):
                     need_reformat = 0
                     pre_fun._path_audio_(inp_path, save_root_ins, save_root_vocal)
                     done = 1
             except:
                 need_reformat = 1
                 traceback.print_exc()
-            if(need_reformat==1):
+            if need_reformat == 1:
                 tmp_path = "%s/%s.reformatted.wav" % (tmp, os.path.basename(inp_path))
-                os.system("ffmpeg -i %s -vn -acodec pcm_s16le -ac 2 -ar 44100 %s -y"%(inp_path,tmp_path))
+                os.system(
+                    "ffmpeg -i %s -vn -acodec pcm_s16le -ac 2 -ar 44100 %s -y"
+                    % (inp_path, tmp_path)
+                )
                 inp_path = tmp_path
             try:
-                if(done==0):pre_fun._path_audio_(inp_path, save_root_ins, save_root_vocal)
+                if done == 0:
+                    pre_fun._path_audio_(inp_path, save_root_ins, save_root_vocal)
                 infos.append("%s->Success" % (os.path.basename(inp_path)))
                 yield "\n".join(infos)
             except:
@@ -672,12 +688,18 @@ def train_index(exp_dir1):
     # index_ivf.nprobe = int(np.power(n_ivf,0.3))
     index_ivf.nprobe = 1
     index.train(big_npy)
-    faiss.write_index(index, '%s/trained_IVF%s_Flat_nprobe_%s.index'%(exp_dir,n_ivf,index_ivf.nprobe))
+    faiss.write_index(
+        index,
+        "%s/trained_IVF%s_Flat_nprobe_%s.index" % (exp_dir, n_ivf, index_ivf.nprobe),
+    )
     # faiss.write_index(index, '%s/trained_IVF%s_Flat_FastScan.index'%(exp_dir,n_ivf))
     infos.append("adding")
     yield "\n".join(infos)
     index.add(big_npy)
-    faiss.write_index(index, '%s/added_IVF%s_Flat_nprobe_%s.index'%(exp_dir,n_ivf,index_ivf.nprobe))
+    faiss.write_index(
+        index,
+        "%s/added_IVF%s_Flat_nprobe_%s.index" % (exp_dir, n_ivf, index_ivf.nprobe),
+    )
     infos.append("成功构建索引，added_IVF%s_Flat_nprobe_%s.index" % (n_ivf, index_ivf.nprobe))
     # faiss.write_index(index, '%s/added_IVF%s_Flat_FastScan.index'%(exp_dir,n_ivf))
     # infos.append("成功构建索引，added_IVF%s_Flat_FastScan.index"%(n_ivf))
@@ -1171,7 +1193,7 @@ with gr.Blocks() as app:
                             label="人声提取激进程度",
                             value=10,
                             interactive=True,
-                            visible=False#先不开放调整
+                            visible=False,  # 先不开放调整
                         )
                         opt_vocal_root = gr.Textbox(
                             label=i18n("指定输出人声文件夹"), value="opt"
@@ -1187,7 +1209,7 @@ with gr.Blocks() as app:
                             opt_vocal_root,
                             wav_inputs,
                             opt_ins_root,
-                            agg
+                            agg,
                         ],
                         [vc_output4],
                     )

infer_uvr5.py

@@ -139,7 +139,9 @@ class _audio_pre_:
                 wav_instrument = spec_utils.cmb_spectrogram_to_wave(y_spec_m, self.mp)
             print("%s instruments done" % name)
             wavfile.write(
-                os.path.join(ins_root, "instrument_{}_{}.wav".format(name,self.data["agg"])),
+                os.path.join(
+                    ins_root, "instrument_{}_{}.wav".format(name, self.data["agg"])
+                ),
                 self.mp.param["sr"],
                 (np.array(wav_instrument) * 32768).astype("int16"),
             )  #
@@ -155,7 +157,9 @@ class _audio_pre_:
                 wav_vocals = spec_utils.cmb_spectrogram_to_wave(v_spec_m, self.mp)
             print("%s vocals done" % name)
             wavfile.write(
-                os.path.join(vocal_root, "vocal_{}_{}.wav".format(name,self.data["agg"])),
+                os.path.join(
+                    vocal_root, "vocal_{}_{}.wav".format(name, self.data["agg"])
+                ),
                 self.mp.param["sr"],
                 (np.array(wav_vocals) * 32768).astype("int16"),
             )