关于inference的Decoding函数 about decap HOT 2 CLOSED

def Decoding(model,clip_features):
    model.eval()
    embedding_cat = model.clip_project(clip_features).reshape(1,1,-1)
    entry_length = 30
    temperature = 1
    tokens = None
    for i in range(entry_length):
        outputs = model.decoder(inputs_embeds=embedding_cat)

        logits = outputs.logits
        logits = logits[:, -1, :] / (temperature if temperature > 0 else 1.0)
        logits_max = logits.max()
        logits = torch.nn.functional.softmax(logits)
        next_token = torch.argmax(logits, -1).unsqueeze(0)
        next_token_embed = model.decoder.transformer.wte(next_token)

        if tokens is None:
            tokens = next_token
        else:
            tokens = torch.cat((tokens, next_token), dim=1)
        if next_token.item()==49407:
            break
        embedding_cat = torch.cat((embedding_cat, next_token_embed), dim=1)
    try:
        output_list = list(tokens.squeeze().cpu().numpy())
        print(output_list)
        output = _Tokenizer.decode(output_list)
    except:
        output = 'None'
    return output