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文本相似度，添加GPU加速

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Downupanddownup 2024-04-26 14:31:54 +08:00
parent 878fef248a
commit 684e1cfd2f
1 changed files with 8 additions and 3 deletions
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11
Ref_Audio_Selector/tool/text_comparison/text_comparison.py
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@ -8,14 +8,19 @@ bert_path = os.environ.get(
"bert_path", "GPT_SoVITS/pretrained_models/chinese-roberta-wwm-ext-large"
)
# Set device to GPU if available, else CPU
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
print(f'使用计算设备: {device}')
tokenizer = AutoTokenizer.from_pretrained(bert_path)
model = AutoModel.from_pretrained(bert_path)
model = AutoModel.from_pretrained(bert_path).to(device)
def calculate_similarity(text1, text2, max_length=512):
# 预处理文本，设置最大长度
inputs1 = tokenizer(text1, padding=True, truncation=True, max_length=max_length, return_tensors='pt')
inputs2 = tokenizer(text2, padding=True, truncation=True, max_length=max_length, return_tensors='pt')
inputs1 = tokenizer(text1, padding=True, truncation=True, max_length=max_length, return_tensors='pt').to(device)
inputs2 = tokenizer(text2, padding=True, truncation=True, max_length=max_length, return_tensors='pt').to(device)
# 获取句子向量（这里是取CLS token的向量并展平为一维）
with torch.no_grad():