Adding NSFW Filter and the Style TTS2 Train Branch

tts/StyleTTS2Train/Utils/PLBERT/util.py

@@ -0,0 +1,42 @@
+import os
+import yaml
+import torch
+from transformers import AlbertConfig, AlbertModel
+
+class CustomAlbert(AlbertModel):
+    def forward(self, *args, **kwargs):
+        # Call the original forward method
+        outputs = super().forward(*args, **kwargs)
+
+        # Only return the last_hidden_state
+        return outputs.last_hidden_state
+
+
+def load_plbert(log_dir):
+    config_path = os.path.join(log_dir, "config.yml")
+    plbert_config = yaml.safe_load(open(config_path))
+    
+    albert_base_configuration = AlbertConfig(**plbert_config['model_params'])
+    bert = CustomAlbert(albert_base_configuration)
+
+    files = os.listdir(log_dir)
+    ckpts = []
+    for f in os.listdir(log_dir):
+        if f.startswith("step_"): ckpts.append(f)
+
+    iters = [int(f.split('_')[-1].split('.')[0]) for f in ckpts if os.path.isfile(os.path.join(log_dir, f))]
+    iters = sorted(iters)[-1]
+
+    checkpoint = torch.load(log_dir + "/step_" + str(iters) + ".t7", map_location='cpu')
+    state_dict = checkpoint['net']
+    from collections import OrderedDict
+    new_state_dict = OrderedDict()
+    for k, v in state_dict.items():
+        name = k[7:] # remove `module.`
+        if name.startswith('encoder.'):
+            name = name[8:] # remove `encoder.`
+            new_state_dict[name] = v
+    del new_state_dict["embeddings.position_ids"]
+    bert.load_state_dict(new_state_dict, strict=False)
+    
+    return bert