Merge pull request #190 from IAHispano/formatter-main

chore(format): run black on main

app.py

@@ -12,6 +12,7 @@
 from tabs.download.download import download_tab
 from tabs.tts.tts import tts_tab
 from assets.discord_presence import rich_presence
+
 rich_presence()
 
 with gr.Blocks(theme="ParityError/Interstellar", title="Applio") as Applio:

assets/discord_presence.py

@@ -2,6 +2,7 @@
 import datetime as dt
 import time
 
+
 def rich_presence():
     client_id = "1144714449563955302"
     RPC = Presence(client_id)
@@ -19,11 +20,12 @@ def rich_presence():
     )
     return RPC
 
+
 if __name__ == "__main__":
     rpc = rich_presence()
 
     try:
         while True:
             time.sleep(15)
     except KeyboardInterrupt:
-        rpc.close()
+        rpc.close()

core.py

@@ -36,7 +36,7 @@ def run_infer_script(
     output_path,
     pth_file,
     index_path,
-    split_audio
+    split_audio,
 ):
     infer_script_path = os.path.join("rvc", "infer", "infer.py")
     command = [
@@ -51,7 +51,7 @@ def run_infer_script(
         output_path,
         pth_file,
         index_path,
-        str(split_audio)
+        str(split_audio),
     ]
     subprocess.run(command)
     return f"File {input_path} inferred successfully.", output_path
@@ -323,6 +323,7 @@ def run_download_script(model_link):
     subprocess.run(command)
     return f"Model downloaded successfully."
 
+
 # Parse arguments
 def parse_arguments():
     parser = argparse.ArgumentParser(
@@ -670,7 +671,7 @@ def main():
                 args.output_path,
                 args.pth_file,
                 args.index_path,
-                args.split_audio
+                args.split_audio,
             )
         elif args.mode == "batch_infer":
             run_batch_infer_script(

rvc/infer/infer.py

@@ -83,7 +83,9 @@ def vc_single(
             result, new_dir_path = process_audio(input_audio_path)
             if result == "Error":
                 return "Error with Split Audio", None
-            dir_path = new_dir_path.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
+            dir_path = (
+                new_dir_path.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
+            )
             if dir_path != "":
                 paths = [
                     os.path.join(root, name)
@@ -108,14 +110,17 @@ def vc_single(
                         path,
                         False,
                     )
-                    #new_dir_path
+                    # new_dir_path
             except Exception as error:
                 print(error)
                 return "Error", None
             print("Finished processing segmented audio, now merging audio...")
-            merge_timestamps_file = os.path.join(os.path.dirname(new_dir_path), f"{os.path.basename(input_audio_path).split('.')[0]}_timestamps.txt")
-            tgt_sr, audio_opt  = merge_audio(merge_timestamps_file)
-
+            merge_timestamps_file = os.path.join(
+                os.path.dirname(new_dir_path),
+                f"{os.path.basename(input_audio_path).split('.')[0]}_timestamps.txt",
+            )
+            tgt_sr, audio_opt = merge_audio(merge_timestamps_file)
+
         else:
             audio_opt = vc.pipeline(
                 hubert_model,
@@ -137,7 +142,6 @@ def vc_single(
                 hop_length,
                 f0_file=f0_file,
             )
-
 
         if output_path is not None:
             sf.write(output_path, audio_opt, tgt_sr, format="WAV")
@@ -243,7 +247,7 @@ def get_vc(weight_root, sid):
         index_rate=index_rate,
         hop_length=hop_length,
         output_path=output_file,
-        split_audio=split_audio
+        split_audio=split_audio,
     )
 
     if os.path.exists(output_file) and os.path.getsize(output_file) > 0:

rvc/train/train.py

@@ -573,7 +573,9 @@ def train_and_evaluate(rank, epoch, hps, nets, optims, scaler, loaders, writers,
             )
 
     if rank == 0:
-        print(f"{hps.name} | epoch={epoch} | step={global_step} | {epoch_recorder.record()} | loss_disc={loss_disc:.3f} | loss_gen={loss_gen:.3f} | loss_fm={loss_fm:.3f} | loss_mel={loss_mel:.3f} | loss_kl={loss_kl:.3f}")
+        print(
+            f"{hps.name} | epoch={epoch} | step={global_step} | {epoch_recorder.record()} | loss_disc={loss_disc:.3f} | loss_gen={loss_gen:.3f} | loss_fm={loss_fm:.3f} | loss_mel={loss_mel:.3f} | loss_kl={loss_kl:.3f}"
+        )
     if epoch >= hps.total_epoch and rank == 0:
         print(
             f"Training has been successfully completed with {epoch} epoch and {global_step} steps."

tabs/inference/inference.py

@@ -58,8 +58,11 @@
     and "_output" not in name
 ]
 
+
 def output_path_fn(input_audio_path):
-    original_name_without_extension = os.path.basename(input_audio_path).rsplit(".", 1)[0]
+    original_name_without_extension = os.path.basename(input_audio_path).rsplit(".", 1)[
+        0
+    ]
     new_name = original_name_without_extension + "_output.wav"
     output_path = os.path.join(os.path.dirname(input_audio_path), new_name)
     return output_path
@@ -248,7 +251,9 @@ def inference_tab():
                 output_path = gr.Textbox(
                     label=i18n("Output Path"),
                     placeholder=i18n("Enter output path"),
-                    value=output_path_fn(audio_paths[0]) if audio_paths else os.path.join(now_dir, "assets", "audios", "output.wav"),
+                    value=output_path_fn(audio_paths[0])
+                    if audio_paths
+                    else os.path.join(now_dir, "assets", "audios", "output.wav"),
                     interactive=True,
                 )
                 split_audio = gr.Checkbox(

tabs/train/train.py

@@ -162,7 +162,9 @@ def train_tab():
                 label=i18n("Save Only Latest"), value=False, interactive=True
             )
             save_every_weights = gr.Checkbox(
-                label=i18n("Save Every Weights"), value=False, visible=False # Working on fix this - Only saving on final epoch
+                label=i18n("Save Every Weights"),
+                value=False,
+                visible=False,  # Working on fix this - Only saving on final epoch
             )
             custom_pretrained = gr.Checkbox(
                 label=i18n("Custom Pretrained"), value=False, interactive=True