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January 8, 2026 03:26
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| // --- 该 token 在当前序列中的相对位置 | ||
| size_t q_token_idx = global_token_idx - offset_[seq_idx]; | ||
| const int64_t total_kv_len = total_kv_lens_[seq_idx]; |
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为什么用 int64_t 而不是 size_t？size_t 和 int64_t 一个是有符号，一个是无符号，应该是有明确的功能区分的，且 size_t 严格定义的话并不一定是 64bit。 size_t 和 int64_t 肯定不能混用， size_t 和 uint64_t 应该也是尽量不混用的
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total_kv_lens是从python端传进来的，所以和pytorch默认int64的行为保持了一致。目前这几个跟index相关的参数只支持了int64类型，在创建的时候也做了限制。如果传入类型需要支持更多类型，可以增加模板参数。
在kernel内部如果需要规范可以强转：“size_t total_kv_len = size_t(total_kv_lens_[seq_idx]); ”，需要这么改吗？
| const int64_t causal_limit = history_len + q_token_idx; | ||
| const Tdata *q_ptr_base = q_ + global_token_idx * num_heads * head_size + head_idx * head_size; | ||
| // 4. 计算指针偏移 |
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注释改英文，新加代码的注释全用英文，老的遗留问题现在不用改，后面集中改
| } | ||
| return INFINI_STATUS_DEVICE_TYPE_NOT_SUPPORTED; | ||
| } | ||
| } No newline at end of file |
| if (!alibi_slopes.is_none()) { | ||
| alibi_slopes_tensor = alibi_slopes.cast<Tensor>(); | ||
| } | ||
| op::paged_attention_prefill_(out, q, k_cache, v_cache, block_tables, history_lens, cu_seqlens_q, alibi_slopes_tensor, scale); |
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现在没这个强制要求了，因为有些强行换行会影响阅读。现在写代码的人可以决定是否换行，这个需要换行吗？
whjthu
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python 测试：
