Merge pull request #741 from Chiyan200/main

Fix Settings Loader Issues: Resolve KeyErrors, Path Handling, and Component Assignment (#731)

Author: SWivid

src/f5_tts/train/finetune_gradio.py

@@ -116,41 +116,57 @@ def load_settings(project_name):
     path_project = os.path.join(path_project_ckpts, project_name)
     file_setting = os.path.join(path_project, "setting.json")
 
-    if not os.path.isfile(file_setting):
-        settings = {
-            "exp_name": "F5TTS_Base",
-            "learning_rate": 1e-05,
-            "batch_size_per_gpu": 1000,
-            "batch_size_type": "frame",
-            "max_samples": 64,
-            "grad_accumulation_steps": 1,
-            "max_grad_norm": 1,
-            "epochs": 100,
-            "num_warmup_updates": 2,
-            "save_per_updates": 300,
-            "keep_last_n_checkpoints": -1,
-            "last_per_updates": 100,
-            "finetune": True,
-            "file_checkpoint_train": "",
-            "tokenizer_type": "pinyin",
-            "tokenizer_file": "",
-            "mixed_precision": "none",
-            "logger": "wandb",
-            "bnb_optimizer": False,
-        }
-    else:
+    # Default settings
+    default_settings = {
+        "exp_name": "F5TTS_Base",
+        "learning_rate": 1e-05,
+        "batch_size_per_gpu": 1000,
+        "batch_size_type": "frame",
+        "max_samples": 64,
+        "grad_accumulation_steps": 1,
+        "max_grad_norm": 1,
+        "epochs": 100,
+        "num_warmup_updates": 2,
+        "save_per_updates": 300,
+        "keep_last_n_checkpoints": -1,
+        "last_per_updates": 100,
+        "finetune": True,
+        "file_checkpoint_train": "",
+        "tokenizer_type": "pinyin",
+        "tokenizer_file": "",
+        "mixed_precision": "none",
+        "logger": "wandb",
+        "bnb_optimizer": False,
+    }
+
+    # Load settings from file if it exists
+    if os.path.isfile(file_setting):
         with open(file_setting, "r") as f:
-            settings = json.load(f)
-            if "logger" not in settings:
-                settings["logger"] = "wandb"
-            if "bnb_optimizer" not in settings:
-                settings["bnb_optimizer"] = False
-            if "keep_last_n_checkpoints" not in settings:
-                settings["keep_last_n_checkpoints"] = -1  # default to keep all checkpoints
-            if "last_per_updates" not in settings:  # patch for backward compatibility, with before f992c4e
-                settings["last_per_updates"] = settings["last_per_steps"] // settings["grad_accumulation_steps"]
+            file_settings = json.load(f)
+        default_settings.update(file_settings)
 
-    return settings
+    # Return as a tuple in the correct order
+    return (
+        default_settings["exp_name"],
+        default_settings["learning_rate"],
+        default_settings["batch_size_per_gpu"],
+        default_settings["batch_size_type"],
+        default_settings["max_samples"],
+        default_settings["grad_accumulation_steps"],
+        default_settings["max_grad_norm"],
+        default_settings["epochs"],
+        default_settings["num_warmup_updates"],
+        default_settings["save_per_updates"],
+        default_settings["keep_last_n_checkpoints"],
+        default_settings["last_per_updates"],
+        default_settings["finetune"],
+        default_settings["file_checkpoint_train"],
+        default_settings["tokenizer_type"],
+        default_settings["tokenizer_file"],
+        default_settings["mixed_precision"],
+        default_settings["logger"],
+        default_settings["bnb_optimizer"],
+    )
 
 
 # Load metadata
@@ -1579,27 +1595,48 @@ def get_audio_select(file_sample):
                 stop_button = gr.Button("Stop Training", interactive=False)
 
             if projects_selelect is not None:
-                settings = load_settings(projects_selelect)
-
-                exp_name.value = settings["exp_name"]
-                learning_rate.value = settings["learning_rate"]
-                batch_size_per_gpu.value = settings["batch_size_per_gpu"]
-                batch_size_type.value = settings["batch_size_type"]
-                max_samples.value = settings["max_samples"]
-                grad_accumulation_steps.value = settings["grad_accumulation_steps"]
-                max_grad_norm.value = settings["max_grad_norm"]
-                epochs.value = settings["epochs"]
-                num_warmup_updates.value = settings["num_warmup_updates"]
-                save_per_updates.value = settings["save_per_updates"]
-                keep_last_n_checkpoints.value = settings["keep_last_n_checkpoints"]
-                last_per_updates.value = settings["last_per_updates"]
-                ch_finetune.value = settings["finetune"]
-                file_checkpoint_train.value = settings["file_checkpoint_train"]
-                tokenizer_type.value = settings["tokenizer_type"]
-                tokenizer_file.value = settings["tokenizer_file"]
-                mixed_precision.value = settings["mixed_precision"]
-                cd_logger.value = settings["logger"]
-                ch_8bit_adam.value = settings["bnb_optimizer"]
+                (
+                    exp_name_value,
+                    learning_rate_value,
+                    batch_size_per_gpu_value,
+                    batch_size_type_value,
+                    max_samples_value,
+                    grad_accumulation_steps_value,
+                    max_grad_norm_value,
+                    epochs_value,
+                    num_warmup_updates_value,
+                    save_per_updates_value,
+                    keep_last_n_checkpoints_value,
+                    last_per_updates_value,
+                    finetune_value,
+                    file_checkpoint_train_value,
+                    tokenizer_type_value,
+                    tokenizer_file_value,
+                    mixed_precision_value,
+                    logger_value,
+                    bnb_optimizer_value,
+                ) = load_settings(projects_selelect)
+
+                # Assigning values to the respective components
+                exp_name.value = exp_name_value
+                learning_rate.value = learning_rate_value
+                batch_size_per_gpu.value = batch_size_per_gpu_value
+                batch_size_type.value = batch_size_type_value
+                max_samples.value = max_samples_value
+                grad_accumulation_steps.value = grad_accumulation_steps_value
+                max_grad_norm.value = max_grad_norm_value
+                epochs.value = epochs_value
+                num_warmup_updates.value = num_warmup_updates_value
+                save_per_updates.value = save_per_updates_value
+                keep_last_n_checkpoints.value = keep_last_n_checkpoints_value
+                last_per_updates.value = last_per_updates_value
+                ch_finetune.value = finetune_value
+                file_checkpoint_train.value = file_checkpoint_train_value
+                tokenizer_type.value = tokenizer_type_value
+                tokenizer_file.value = tokenizer_file_value
+                mixed_precision.value = mixed_precision_value
+                cd_logger.value = logger_value
+                ch_8bit_adam.value = bnb_optimizer_value
 
             ch_stream = gr.Checkbox(label="Stream Output Experiment", value=True)
             txt_info_train = gr.Text(label="Info", value="")