Fixed some deprecation issues.

app.py

@@ -67,8 +67,10 @@ def tts_fn(
 
     if(not model_holder.current_model):
         model_holder.load_model_gr(model_name, model_path)
+        logger.info(f"Loaded model '{model_name}'")
     if(model_holder.current_model.model_path != model_path):
         model_holder.load_model_gr(model_name, model_path)
+        logger.info(f"Swapped to model '{model_name}'")
     speaker_id = model_holder.current_model.spk2id[speaker]
     start_time = datetime.datetime.now()
 
@@ -288,7 +290,7 @@ if __name__ == "__main__":
         for (name, model_path, voice_name, speakerid, datasetauthor, image) in voicedata:
             with gr.TabItem(name):
                 mn = gr.Textbox(value=model_path, visible=False, interactive=False)
-                mp = gr.Textbox(value=f"model_assets/{model_path}/{model_path}.safetensors", visible=False, interactive=False)
+                mp = gr.Textbox(value=f"model_assets\\{model_path}\\{model_path}.safetensors", visible=False, interactive=False)
                 spk = gr.Textbox(value=speakerid, visible=False, interactive=False)
                 with gr.Row():
                     with gr.Column():

models.py

@@ -5,7 +5,8 @@ import torch
 from torch import nn
 from torch.nn import Conv1d, Conv2d, ConvTranspose1d
 from torch.nn import functional as F
-from torch.nn.utils import remove_weight_norm, spectral_norm, weight_norm
+from torch.nn.utils import remove_weight_norm
+from torch.nn.utils.parametrizations import spectral_norm, weight_norm
 
 import attentions
 import commons

models_jp_extra.py

@@ -9,7 +9,8 @@ import attentions
 import monotonic_align
 
 from torch.nn import Conv1d, ConvTranspose1d, Conv2d
-from torch.nn.utils import weight_norm, remove_weight_norm, spectral_norm
+from torch.nn.utils import remove_weight_norm
+from torch.nn.utils.parametrizations import spectral_norm, weight_norm
 
 from commons import init_weights, get_padding
 from text import symbols, num_tones, num_languages

modules.py

@@ -5,7 +5,8 @@ import torch
 from torch import nn
 from torch.nn import Conv1d
 from torch.nn import functional as F
-from torch.nn.utils import remove_weight_norm, weight_norm
+from torch.nn.utils import remove_weight_norm
+from torch.nn.utils.parametrizations import weight_norm
 
 import commons
 from attentions import Encoder
@@ -158,7 +159,7 @@ class WN(torch.nn.Module):
             cond_layer = torch.nn.Conv1d(
                 gin_channels, 2 * hidden_channels * n_layers, 1
             )
-            self.cond_layer = torch.nn.utils.weight_norm(cond_layer, name="weight")
+            self.cond_layer = torch.nn.utils.parametrizations.weight_norm(cond_layer, name="weight")
 
         for i in range(n_layers):
             dilation = dilation_rate**i
@@ -170,7 +171,7 @@ class WN(torch.nn.Module):
                 dilation=dilation,
                 padding=padding,
             )
-            in_layer = torch.nn.utils.weight_norm(in_layer, name="weight")
+            in_layer = torch.nn.utils.parametrizations.weight_norm(in_layer, name="weight")
             self.in_layers.append(in_layer)
 
             # last one is not necessary
@@ -180,7 +181,7 @@ class WN(torch.nn.Module):
                 res_skip_channels = hidden_channels
 
             res_skip_layer = torch.nn.Conv1d(hidden_channels, res_skip_channels, 1)
-            res_skip_layer = torch.nn.utils.weight_norm(res_skip_layer, name="weight")
+            res_skip_layer = torch.nn.utils.parametrizations.weight_norm(res_skip_layer, name="weight")
             self.res_skip_layers.append(res_skip_layer)
 
     def forward(self, x, x_mask, g=None, **kwargs):

utils.py

@@ -162,10 +162,7 @@ def load_safetensors(checkpoint_path, model, for_infer=False):
         if key == "iteration":
             continue
         logger.warning(f"Unexpected key: {key}")
-    if iteration is None:
-        logger.info(f"Loaded '{checkpoint_path}'")
-    else:
-        logger.info(f"Loaded '{checkpoint_path}' (iteration {iteration})")
+    #logger.info(f"Swapped to model '{checkpoint_path}'")
     return model, iteration