#pragma once #include torch::Tensor LLMM1(at::Tensor& in_a, at::Tensor& in_b, const int64_t rows_per_block); torch::Tensor wvSplitK(at::Tensor& in_a, at::Tensor& in_b, const int64_t CuCount); void wvSplitKQ(at::Tensor& in_a, at::Tensor& in_b, at::Tensor& out_c, at::Tensor& scale_a, at::Tensor& scale_b, const int64_t CuCount); void paged_attention( torch::Tensor& out, torch::Tensor& exp_sums, torch::Tensor& max_logits, torch::Tensor& tmp_out, torch::Tensor& query, torch::Tensor& key_cache, torch::Tensor& value_cache, int64_t num_kv_heads, double scale, torch::Tensor& block_tables, torch::Tensor& context_lens, const std::optional& query_start_loc, int64_t block_size, int64_t max_context_len, const std::optional& alibi_slopes, const std::string& kv_cache_dtype, torch::Tensor& k_scale, torch::Tensor& v_scale, const std::optional& fp8_out_scale);