File size: 5,717 Bytes
4d1b54e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 |
#pragma once
#include <optional>
#include <vector>
#include <torch/torch.h>
std::vector<at::Tensor>
mha_fwd(at::Tensor &q, // (b, s_q, h, d) or (total_q, h, d) if there is cu_seqlens_q
const at::Tensor &k, // (b_k, s_k, h_k, d) or (total_k, h_k, d) if there is cu_seqlens_k or (num_pages, page_size, h_k, d) if there is page_table.
const at::Tensor &v, // (b_k, s_k, h_k, dv) or (total_k, h_k, dv) if there is cu_seqlens_k or (num_pages, page_size, h_k, dv) if there is page_table.
std::optional<const at::Tensor> &k_new_, // (b, s_k_new, h_k, d) or (total_k_new, h_k, d) if there is cu_seqlens_k_new
std::optional<const at::Tensor> &v_new_, // (b, s_k_new, h_k, dv) or (total_k_new, h_k, dv) if there is cu_seqlens_k_new
std::optional<const at::Tensor> &q_v_, // (b, s_q, h, dv) or (total_q_new, h, dv) if there is cu_seqlens_q
std::optional<at::Tensor> &out_, // (b, s_q, h, dv) or (total_q, h, dv) if there is cu_seqlens_q
std::optional<const at::Tensor> &cu_seqlens_q_, // b+1
std::optional<const at::Tensor> &cu_seqlens_k_, // b+1
std::optional<const at::Tensor> &cu_seqlens_k_new_, // b+1
std::optional<const at::Tensor> &seqused_q_, // b. If given, only this many elements of each batch element's queries and outputs are used.
std::optional<const at::Tensor> &seqused_k_, // b. If given, only this many elements of each batch element's keys are used.
std::optional<int> max_seqlen_q_,
// TODO: check if we need max_seqlen_k
std::optional<int> max_seqlen_k_,
std::optional<const at::Tensor> &page_table_, // (b_k, max_num_pages_per_seq)
std::optional<const at::Tensor> &kv_batch_idx_, // b. indices to index into the KV cache
std::optional<const at::Tensor> &leftpad_k_, // b
std::optional<const at::Tensor> &rotary_cos_, // seqlen_ro x (rotary_dim / 2)
std::optional<const at::Tensor> &rotary_sin_, // seqlen_ro x (rotary_dim / 2)
std::optional<const at::Tensor> &seqlens_rotary_, // b
std::optional<at::Tensor> &q_descale_, // (b, h_k), not (b, h)
std::optional<at::Tensor> &k_descale_, // (b, h_k)
std::optional<at::Tensor> &v_descale_, // (b, h_k)
float const softmax_scale,
bool is_causal,
int window_size_left,
int window_size_right,
float const softcap,
bool const is_rotary_interleaved, // if true, rotary combines indices 0 & 1, else indices 0 & rotary_dim / 2
std::optional<at::Tensor> &scheduler_metadata_, // (b + 1)
int num_splits,
std::optional<bool> pack_gqa_,
int const sm_margin,
std::optional<const at::Tensor> &s_aux_ // (h)
);
std::vector<at::Tensor> mha_bwd(
const at::Tensor &dout, // (b, s_q, h, d) or (total_q, h, d) if there is cu_seqlens_q
const at::Tensor &q, // (b, s_q, h, d) or (total_q, h, d) if there is cu_seqlens_q
const at::Tensor &k, // (b, s_k, h_k, d) or (total_k, h_k, d) if there is cu_seqlens_k
const at::Tensor &v, // (b, s_k, h_k, d) or (total_k, h_k, d) if there is cu_seqlens_k
const at::Tensor &out, // (b, s_q, h, d) or (total_q, h, d) if there is cu_seqlens_q
const at::Tensor &softmax_lse, // (b, h, s_q) or (h, total_q) if there is cu_seqlens_q
std::optional<at::Tensor> &dq_, // (b, s_q, h, d) or (total_q, h, d) if there is cu_seqlens_q
std::optional<at::Tensor> &dk_, // (b, s_k, h_k, d) or (total_k, h_k, d) if there is cu_seqlens_k
std::optional<at::Tensor> &dv_, // (b, s_k, h_k, d) or (total_k, h_k, d) if there is cu_seqlens_k
std::optional<const at::Tensor> &cu_seqlens_q_, // b+1
std::optional<const at::Tensor> &cu_seqlens_k_, // b+1
std::optional<const at::Tensor> &seqused_q_, // b. If given, only this many elements of each batch element's queries and outputs are used.
std::optional<const at::Tensor> &seqused_k_, // b. If given, only this many elements of each batch element's keys are used.
std::optional<int> max_seqlen_q_,
std::optional<int> max_seqlen_k_,
float const softmax_scale,
bool is_causal,
int window_size_left,
int window_size_right,
float const softcap,
bool const deterministic,
int const sm_margin);
std::vector<at::Tensor>
mha_combine(const at::Tensor &out_partial, // num_splits x batch_size x seqlen x num_heads x head_size
const at::Tensor &lse_partial, // num_splits x batch_size x seqlen x num_heads
std::optional<at::Tensor> out_, // batch_size x seqlen x num_heads x head_size
std::optional<at::ScalarType> out_dtype_
);
at::Tensor
mha_fwd_get_scheduler_metadata(
int batch_size,
int max_seqlen_q,
int max_seqlen_k,
int num_heads,
int num_heads_k,
int headdim,
int headdim_v,
at::ScalarType qkv_dtype,
const at::Tensor &seqused_k, // b
std::optional<const at::Tensor> &cu_seqlens_q_, // b+1
std::optional<const at::Tensor> &cu_seqlens_k_, // b+1
std::optional<const at::Tensor> &cu_seqlens_k_new_, // b+1
std::optional<const at::Tensor> &seqused_q_, // b. If given, only this many elements of each batch element's queries and outputs are used.
std::optional<const at::Tensor> &leftpad_k_, // b
std::optional<int> page_size,
int max_seqlen_k_new, // 0 means we're not appending new KV
bool is_causal,
int window_size_left,
int window_size_right,
bool has_softcap,
int num_splits,
std::optional<bool> pack_gqa_,
int const sm_margin
);
|