app

app.py

@@ -52,27 +52,7 @@ logging.getLogger('multipart').setLevel(logging.WARNING)
 device = "cuda" if torch.cuda.is_available() else "cpu"
 #device = "cpu"
 is_half = False
-
-tokenizer = AutoTokenizer.from_pretrained(bert_path)
-bert_model=AutoModelForMaskedLM.from_pretrained(bert_path)
-if(is_half==True):bert_model=bert_model.half().to(device)
-else:bert_model=bert_model.to(device)
 # bert_model=bert_model.to(device)
-def get_bert_feature(text, word2ph): # Bert(不是HuBERT的特征计算)
-    with torch.no_grad():
-        inputs = tokenizer(text, return_tensors="pt")
-        for i in inputs:
-            inputs[i] = inputs[i].to(device)#####输入是long不用管精度问题，精度随bert_model
-        res = bert_model(**inputs, output_hidden_states=True)
-        res = torch.cat(res["hidden_states"][-3:-2], -1)[0].cpu()[1:-1]
-    assert len(word2ph) == len(text)
-    phone_level_feature = []
-    for i in range(len(word2ph)):
-        repeat_feature = res[i].repeat(word2ph[i], 1)
-        phone_level_feature.append(repeat_feature)
-    phone_level_feature = torch.cat(phone_level_feature, dim=0)
-    # if(is_half==True):phone_level_feature=phone_level_feature.half()
-    return phone_level_feature.T
 
 loaded_sovits_model = [] # [(path, dict, model)]
 loaded_gpt_model = []
@@ -364,7 +344,7 @@ with gr.Blocks() as app:
                         )
                         prompt_language = gr.State(value="ja")
                     with gr.Column():
-                        text = gr.Textbox(label="Input Text", value="こんにちは、私はあなたのAIアシスタントです。仲良くしましょうね。")
+                        text = gr.Textbox(label="Input Text", value="学園アイドルマスター！")
                         text_language = gr.Dropdown(
                             label="Language",
                             choices=["ja"],