feat: tab ui

app.py

@@ -47,10 +47,6 @@ def extract_audio_files(zip_file: str, target_dir: str) -> list[str]:
     return audio_files
 
 
-def train_rvc_model(audio_files: list[str]) -> str:
-    return "model_path"
-
-
 def preprocess(zip_file: str) -> str:
     temp_dir = tempfile.mkdtemp()
     print(f"Using exp dir: {temp_dir}")
@@ -59,7 +55,7 @@ def preprocess(zip_file: str) -> str:
     os.makedirs(data_dir)
     audio_files = extract_audio_files(zip_file, data_dir)
 
-    pp = PreProcess(48000, temp_dir, 3.0, False)
+    pp = PreProcess(40000, temp_dir, 3.0, False)
     pp.pipeline_mp_inp_dir(data_dir, 4)
 
     pp.logfile.seek(0)
@@ -209,55 +205,59 @@ def restore_expdir(zip: str) -> str:
 
 
 with gr.Blocks() as app:
-    with gr.Row():
-        with gr.Column():
-            zip_file = gr.File(
-                label="Upload a zip file containing audio files for training",
-                file_types=["zip"],
-            )
-            exp_dir = gr.Textbox(label="Experiment directory", visible=True)
-            preprocess_btn = gr.Button(value="Preprocess", variant="primary")
-        with gr.Column():
-            preprocess_output = gr.Textbox(label="Preprocessing output", lines=5)
-
-    with gr.Row():
-        restore_zip_file = gr.File(
-            label="Upload the experiment directory zip file",
-            file_types=["zip"],
-        )
-        restore_btn = gr.Button(value="Preprocess")
+    exp_dir = gr.Textbox(label="Experiment directory", visible=True, interactive=False)
+
+    with gr.Tabs():
+        with gr.Tab(label="New / Restore"):
+            with gr.Row():
+                with gr.Column():
+                    zip_file = gr.File(
+                        label="Upload a zip file containing audio files for training",
+                        file_types=["zip"],
+                    )
+                    preprocess_output = gr.Textbox(
+                        label="Preprocessing output", lines=5
+                    )
+                with gr.Column():
+                    preprocess_btn = gr.Button(
+                        value="Start New Experiment", variant="primary"
+                    )
+
+            with gr.Row():
+                restore_zip_file = gr.File(
+                    label="Upload the experiment directory zip file",
+                    file_types=["zip"],
+                )
+                restore_btn = gr.Button(value="Restore Experiment", variant="primary")
 
-    with gr.Row():
-        with gr.Column():
-            extract_features_btn = gr.Button(
-                value="Extract features", variant="primary"
-            )
-        with gr.Column():
-            extract_features_output = gr.Textbox(
-                label="Feature extraction output", lines=5
-            )
+        with gr.Tab(label="Extract features"):
+            with gr.Row():
+                extract_features_btn = gr.Button(
+                    value="Extract features", variant="primary"
+                )
+            with gr.Row():
+                extract_features_output = gr.Textbox(
+                    label="Feature extraction output", lines=10
+                )
 
-    with gr.Row():
-        with gr.Column():
-            train_btn = gr.Button(value="Train", variant="primary")
-        with gr.Column():
-            latest_model = gr.File(label="Latest checkpoint")
+        with gr.Tab(label="Train"):
+            with gr.Row():
+                train_btn = gr.Button(value="Train", variant="primary")
+            with gr.Row():
+                latest_model = gr.File(label="Latest checkpoint")
 
-    with gr.Row():
-        with gr.Column():
-            download_weight_btn = gr.Button(
-                value="Download latest model", variant="primary"
-            )
-        with gr.Column():
-            download_weight_output = gr.File(label="Download latest model")
+        with gr.Tab(label="Download"):
+            with gr.Row():
+                download_weight_btn = gr.Button(
+                    value="Download latest model", variant="primary"
+                )
+                download_weight_output = gr.File(label="Download latest model")
 
-    with gr.Row():
-        with gr.Column():
-            download_expdir_btn = gr.Button(
-                value="Download experiment directory", variant="primary"
-            )
-        with gr.Column():
-            download_expdir_output = gr.File(label="Download experiment directory")
+            with gr.Row():
+                download_expdir_btn = gr.Button(
+                    value="Download experiment directory", variant="primary"
+                )
+                download_expdir_output = gr.File(label="Download experiment directory")
 
     preprocess_btn.click(
         fn=preprocess,

infer/modules/train/train.py

@@ -152,8 +152,8 @@ def run(rank, n_gpus, hps, logger: logging.Logger, state):
         pin_memory=True,
         collate_fn=collate_fn,
         batch_sampler=train_sampler,
-        persistent_workers=True,
-        prefetch_factor=8,
+        # persistent_workers=True,
+        # prefetch_factor=8,
     )
     if hps.if_f0 == 1:
         net_g = RVC_Model_f0(