add logger

src/f5_tts/train/finetune_gradio.py

@@ -69,6 +69,7 @@ def save_settings(
     tokenizer_type,
     tokenizer_file,
     mixed_precision,
+    logger,
 ):
     path_project = os.path.join(path_project_ckpts, project_name)
     os.makedirs(path_project, exist_ok=True)
@@ -91,6 +92,7 @@ def save_settings(
         "tokenizer_type": tokenizer_type,
         "tokenizer_file": tokenizer_file,
         "mixed_precision": mixed_precision,
+        "logger": logger,
     }
     with open(file_setting, "w") as f:
         json.dump(settings, f, indent=4)
@@ -121,6 +123,7 @@ def load_settings(project_name):
             "tokenizer_type": "pinyin",
             "tokenizer_file": "",
             "mixed_precision": "none",
+            "logger": "wandb",
         }
         return (
             settings["exp_name"],
@@ -139,6 +142,7 @@ def load_settings(project_name):
             settings["tokenizer_type"],
             settings["tokenizer_file"],
             settings["mixed_precision"],
+            settings["logger"],
         )
 
     with open(file_setting, "r") as f:
@@ -160,6 +164,7 @@ def load_settings(project_name):
         settings["tokenizer_type"],
         settings["tokenizer_file"],
         settings["mixed_precision"],
+        settings["logger"],
     )
 
 
@@ -374,6 +379,7 @@ def start_training(
     tokenizer_file="",
     mixed_precision="fp16",
     stream=False,
+    logger="wandb",
 ):
     global training_process, tts_api, stop_signal
 
@@ -447,7 +453,7 @@ def start_training(
 
     cmd += f" --tokenizer {tokenizer_type} "
 
-    cmd += " --export_samples True --logger wandb "
+    cmd += f" --export_samples True --logger {logger} "
 
     print(cmd)
 
@@ -469,6 +475,7 @@ def start_training(
         tokenizer_type,
         tokenizer_file,
         mixed_precision,
+        logger,
     )
 
     try:
@@ -1508,6 +1515,7 @@ If you encounter a memory error, try reducing the batch size per GPU to a smalle
 
             with gr.Row():
                 mixed_precision = gr.Radio(label="mixed_precision", choices=["none", "fp16", "fpb16"], value="none")
+                cd_logger = gr.Radio(label="logger", choices=["none", "wandb", "tensorboard"], value="wandb")
                 start_button = gr.Button("Start Training")
                 stop_button = gr.Button("Stop Training", interactive=False)
 
@@ -1529,6 +1537,7 @@ If you encounter a memory error, try reducing the batch size per GPU to a smalle
                     tokenizer_typev,
                     tokenizer_filev,
                     mixed_precisionv,
+                    cd_loggerv,
                 ) = load_settings(projects_selelect)
                 exp_name.value = exp_namev
                 learning_rate.value = learning_ratev
@@ -1546,6 +1555,7 @@ If you encounter a memory error, try reducing the batch size per GPU to a smalle
                 tokenizer_type.value = tokenizer_typev
                 tokenizer_file.value = tokenizer_filev
                 mixed_precision.value = mixed_precisionv
+                cd_logger.value = cd_loggerv
 
             ch_stream = gr.Checkbox(label="stream output experiment.", value=True)
             txt_info_train = gr.Text(label="info", value="")
@@ -1611,6 +1621,7 @@ If you encounter a memory error, try reducing the batch size per GPU to a smalle
                     tokenizer_file,
                     mixed_precision,
                     ch_stream,
+                    cd_logger,
                 ],
                 outputs=[txt_info_train, start_button, stop_button],
             )
@@ -1662,6 +1673,7 @@ If you encounter a memory error, try reducing the batch size per GPU to a smalle
                     tokenizer_type,
                     tokenizer_file,
                     mixed_precision,
+                    cd_logger,
                 ]
 
                 return output_components