Add support for SWA (left, right) with FusedAttention #2477
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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@@ -406,9 +406,11 @@ NVTE_Fused_Attn_Backend nvte_get_fused_attn_backend( | |
| (window_size_right == -1 || window_size_right == 0)) || | ||
| // 9.2: SWA (left, 0) + top-left diagonal + {bshd, sbhd} | ||
| (cudnn_runtime_version >= 90200 && | ||
| ((window_size_left == -1 && window_size_right == -1 && | ||
| attn_mask_type == NVTE_Mask_Type::NVTE_NO_MASK) || | ||
| ((window_size_left == -1 || window_size_left >= 0) && window_size_right == 0 && | ||
| (attn_mask_type == NVTE_Mask_Type::NVTE_NO_MASK || | ||
| attn_mask_type == NVTE_Mask_Type::NVTE_CAUSAL_MASK || | ||
| (attn_mask_type == NVTE_Mask_Type::NVTE_CAUSAL_BOTTOM_RIGHT_MASK && | ||
| max_seqlen_q == max_seqlen_kv)) && | ||
| max_seqlen_q <= max_seqlen_kv && dropout == 0.0 && | ||
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@@ -418,12 +420,14 @@ NVTE_Fused_Attn_Backend nvte_get_fused_attn_backend( | |
| // 9.6: SWA (left, 0) + top-left/bottom-right diagonal + {bshd, sbhd, thd} | ||
| (cudnn_runtime_version >= 90600 && | ||
| ((window_size_left == -1 && (window_size_right == -1 || window_size_right == 0)) || | ||
| ((window_size_left >= 0 || window_size_left == -1) && | ||
| (window_size_right >= 0 || window_size_right == -1) && | ||
| ((attn_mask_type == NVTE_Mask_Type::NVTE_CAUSAL_BOTTOM_RIGHT_MASK && | ||
| // TODO(cyang): fix bug for BRCM + cross-attention on sm100 | ||
| (sm_arch_ < 100 || (sm_arch_ >= 100 && ((max_seqlen_q == max_seqlen_kv && | ||
| cudnn_runtime_version <= 90700) || | ||
| cudnn_runtime_version > 90700)))) || | ||
| attn_mask_type == NVTE_Mask_Type::NVTE_PADDING_MASK || | ||
| attn_mask_type == NVTE_Mask_Type::NVTE_PADDING_CAUSAL_MASK || | ||
| (attn_mask_type == NVTE_Mask_Type::NVTE_PADDING_CAUSAL_BOTTOM_RIGHT_MASK && | ||
| (sm_arch_ < 100 || (sm_arch_ >= 100 && ((max_seqlen_q == max_seqlen_kv && | ||
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@@ -504,18 +508,16 @@ NVTE_Fused_Attn_Backend nvte_get_fused_attn_backend( | |
| } | ||
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| // NVTE fused attention FWD with packed QKV | ||
| // DEPRECATED: This API is deprecated. (Should there be a version by which this is going to be removed? @cyang) | ||
|
Collaborator
There was a problem hiding this comment. I made some changes in #2272, but will see if I can make the 2.11 deadline. |
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| // Please use nvte_fused_attn_fwd with separate Q, K, V tensors instead. | ||
| void nvte_fused_attn_fwd_qkvpacked( | ||
| const NVTETensor QKV, const NVTETensor Bias, const NVTETensor SoftmaxOffset, NVTETensor S, | ||
| NVTETensor O, NVTETensorPack *Aux_CTX_Tensors, const NVTETensor cu_seqlens, | ||
| const NVTETensor cu_seqlens_padded, const NVTETensor rng_state, size_t max_seqlen, | ||
| bool is_training, bool return_max_logit, bool cuda_graph, float attn_scale, float dropout, | ||
| NVTE_QKV_Layout qkv_layout, NVTE_Bias_Type bias_type, NVTE_Mask_Type attn_mask_type, | ||
| NVTE_Softmax_Type softmax_type, int64_t window_size_left, int64_t window_size_right, | ||
| bool bottom_right_diagonal, NVTETensor workspace, cudaStream_t stream) { | ||
| NVTE_API_CALL(nvte_flash_attn_fwd_qkvpacked); | ||
| using namespace transformer_engine; | ||
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@@ -589,10 +591,10 @@ void nvte_fused_attn_fwd_qkvpacked(const NVTETensor QKV, const NVTETensor Bias, | |
| fused_attn_arbitrary_seqlen_fwd( | ||
| b, h, h, max_seqlen, max_seqlen, d, d, t, t, 0, 0, 0, 0, 0, 0, is_training, | ||
| return_max_logit, attn_scale, dropout, qkv_layout, bias_type, attn_mask_type, softmax_type, | ||
| window_size_left, window_size_right, bottom_right_diagonal, &Q_view, &K_view, &V_view, | ||
| input_Bias, input_SoftmaxOffset, output_O, Aux_CTX_Tensors, input_cu_seqlens, | ||
| input_cu_seqlens, input_cu_seqlens_padded, input_cu_seqlens_padded, nullptr, nullptr, | ||
| input_rng_state, wkspace, stream, handle); | ||
| #else | ||
| NVTE_ERROR( | ||
| "cuDNN 8.9.0 is required for BF16/FP16 fused attention with arbitrary sequence length. \n"); | ||
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@@ -629,8 +631,8 @@ void nvte_fused_attn_bwd_qkvpacked( | |
| NVTETensor dSoftmaxOffset, const NVTETensor cu_seqlens, const NVTETensor cu_seqlens_padded, | ||
| size_t max_seqlen, float attn_scale, float dropout, NVTE_QKV_Layout qkv_layout, | ||
| NVTE_Bias_Type bias_type, NVTE_Mask_Type attn_mask_type, NVTE_Softmax_Type softmax_type, | ||
| int64_t window_size_left, int64_t window_size_right, bool bottom_right_diagonal, | ||
| bool deterministic, bool cuda_graph, NVTETensor workspace, cudaStream_t stream) { | ||
| NVTE_API_CALL(nvte_flash_attn_bwd_qkvpacked); | ||
| using namespace transformer_engine; | ||
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@@ -725,10 +727,11 @@ void nvte_fused_attn_bwd_qkvpacked( | |
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| fused_attn_arbitrary_seqlen_bwd( | ||
| b, h, h, max_seqlen, max_seqlen, d, d, t, t, attn_scale, dropout, qkv_layout, bias_type, | ||
| attn_mask_type, softmax_type, window_size_left, window_size_right, bottom_right_diagonal, | ||
| deterministic, &Q_view, &K_view, &V_view, input_O, input_dO, input_Bias, | ||
| input_SoftmaxOffset, output_S, &dQ_view, &dK_view, &dV_view, output_dBias, | ||
| output_dSoftmaxOffset, input_cu_seqlens, input_cu_seqlens, input_cu_seqlens_padded, | ||
| input_cu_seqlens_padded, input_rng_state, wkspace, stream, handle); | ||
| #else | ||
| const char *err_msg = | ||
| "cuDNN 8.9.0 is required for BF16/FP16 fused attention " | ||
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@@ -779,7 +782,8 @@ void nvte_fused_attn_fwd_kvpacked( | |
| size_t max_seqlen_kv, bool is_training, bool return_max_logit, bool cuda_graph, | ||
| float attn_scale, float dropout, NVTE_QKV_Layout qkv_layout, NVTE_Bias_Type bias_type, | ||
| NVTE_Mask_Type attn_mask_type, NVTE_Softmax_Type softmax_type, int64_t window_size_left, | ||
| int64_t window_size_right, bool bottom_right_diagonal, NVTETensor workspace, | ||
| cudaStream_t stream) { | ||
| NVTE_API_CALL(nvte_flash_attn_fwd_kvpacked); | ||
| using namespace transformer_engine; | ||
| const Tensor *input_cu_seqlens_q = convertNVTETensorCheck(cu_seqlens_q); | ||
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@@ -891,10 +895,10 @@ void nvte_fused_attn_fwd_kvpacked( | |
| b, h_q, h_kv, max_seqlen_q, max_seqlen_kv, d, d, t_q, t_kv, num_pages_k, num_pages_v, | ||
| page_size_k, page_size_v, max_pages_per_seq_k, max_pages_per_seq_v, is_training, | ||
| return_max_logit, attn_scale, dropout, qkv_layout, bias_type, attn_mask_type, softmax_type, | ||
| window_size_left, window_size_right, bottom_right_diagonal, input_Q, &K_view, &V_view, | ||
| input_Bias, input_SoftmaxOffset, output_O, Aux_CTX_Tensors, input_cu_seqlens_q, | ||
| input_cu_seqlens_kv, input_cu_seqlens_q_padded, input_cu_seqlens_kv_padded, | ||
| input_page_table_k, input_page_table_v, input_rng_state, wkspace, stream, handle); | ||
| #else | ||
| NVTE_ERROR( | ||
| "cuDNN 8.9.3 is required for BF16/FP16 fused attention with arbitrary sequence length. \n"); | ||
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@@ -933,8 +937,8 @@ void nvte_fused_attn_bwd_kvpacked( | |
| const NVTETensor cu_seqlens_kv_padded, size_t max_seqlen_q, size_t max_seqlen_kv, | ||
| float attn_scale, float dropout, NVTE_QKV_Layout qkv_layout, NVTE_Bias_Type bias_type, | ||
| NVTE_Mask_Type attn_mask_type, NVTE_Softmax_Type softmax_type, int64_t window_size_left, | ||
| int64_t window_size_right, bool bottom_right_diagonal, bool deterministic, bool cuda_graph, | ||
| NVTETensor workspace, cudaStream_t stream) { | ||
| NVTE_API_CALL(nvte_flash_attn_bwd_kvpacked); | ||
| using namespace transformer_engine; | ||
| const Tensor *input_cu_seqlens_q = convertNVTETensorCheck(cu_seqlens_q); | ||
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@@ -1040,11 +1044,11 @@ void nvte_fused_attn_bwd_kvpacked( | |
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| fused_attn_arbitrary_seqlen_bwd( | ||
| b, h_q, h_kv, max_seqlen_q, max_seqlen_kv, d, d, t_q, t_kv, attn_scale, dropout, qkv_layout, | ||
| bias_type, attn_mask_type, softmax_type, window_size_left, window_size_right, | ||
| bottom_right_diagonal, deterministic, input_Q, &K_view, &V_view, input_O, input_dO, | ||
| input_Bias, input_SoftmaxOffset, output_S, output_dQ, &dK_view, &dV_view, output_dBias, | ||
| output_dSoftmaxOffset, input_cu_seqlens_q, input_cu_seqlens_kv, input_cu_seqlens_q_padded, | ||
| input_cu_seqlens_kv_padded, input_rng_state, wkspace, stream, handle); | ||
| #else | ||
| const char *err_msg = | ||
| "cuDNN 8.9.3 is required for BF16/FP16 fused attention " | ||
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@@ -1094,8 +1098,8 @@ void nvte_fused_attn_fwd(const NVTETensor Q, const NVTETensor K, const NVTETenso | |
| bool return_max_logit, bool cuda_graph, float attn_scale, float dropout, | ||
| NVTE_QKV_Layout qkv_layout, NVTE_Bias_Type bias_type, | ||
| NVTE_Mask_Type attn_mask_type, NVTE_Softmax_Type softmax_type, | ||
| int64_t window_size_left, int64_t window_size_right, | ||
| bool bottom_right_diagonal, NVTETensor workspace, cudaStream_t stream) { | ||
| NVTE_API_CALL(nvte_flash_attn_fwd); | ||
| using namespace transformer_engine; | ||
| const Tensor *input_cu_seqlens_q = convertNVTETensorCheck(cu_seqlens_q); | ||
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@@ -1183,10 +1187,10 @@ void nvte_fused_attn_fwd(const NVTETensor Q, const NVTETensor K, const NVTETenso | |
| b, h_q, h_kv, max_seqlen_q, max_seqlen_kv, d_qk, d_v, t_q, t_kv, num_pages_k, num_pages_v, | ||
| page_size_k, page_size_v, max_pages_per_seq_k, max_pages_per_seq_v, is_training, | ||
| return_max_logit, attn_scale, dropout, qkv_layout, bias_type, attn_mask_type, softmax_type, | ||
| window_size_left, window_size_right, bottom_right_diagonal, input_Q, input_K, input_V, | ||
| input_Bias, input_SoftmaxOffset, output_O, Aux_CTX_Tensors, input_cu_seqlens_q, | ||
| input_cu_seqlens_kv, input_cu_seqlens_q_padded, input_cu_seqlens_kv_padded, | ||
| input_page_table_k, input_page_table_v, input_rng_state, wkspace, stream, handle); | ||
| #else | ||
| NVTE_ERROR( | ||
| "cuDNN 8.9.0 is required for BF16/FP16 fused attention with arbitrary sequence length. \n"); | ||
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@@ -1215,8 +1219,9 @@ void nvte_fused_attn_bwd(const NVTETensor Q, const NVTETensor K, const NVTETenso | |
| size_t max_seqlen_kv, float attn_scale, float dropout, | ||
| NVTE_QKV_Layout qkv_layout, NVTE_Bias_Type bias_type, | ||
| NVTE_Mask_Type attn_mask_type, NVTE_Softmax_Type softmax_type, | ||
| int64_t window_size_left, int64_t window_size_right, | ||
| bool bottom_right_diagonal, bool deterministic, bool cuda_graph, | ||
| NVTETensor workspace, cudaStream_t stream) { | ||
| NVTE_API_CALL(nvte_flash_attn_bwd); | ||
| using namespace transformer_engine; | ||
| const Tensor *input_cu_seqlens_q = convertNVTETensorCheck(cu_seqlens_q); | ||
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@@ -1289,8 +1294,8 @@ void nvte_fused_attn_bwd(const NVTETensor Q, const NVTETensor K, const NVTETenso | |
| fused_attn_arbitrary_seqlen_bwd( | ||
| b, h_q, h_kv, max_seqlen_q, max_seqlen_kv, d_qk, d_v, t_q, t_kv, attn_scale, dropout, | ||
| qkv_layout, bias_type, attn_mask_type, softmax_type, window_size_left, window_size_right, | ||
| bottom_right_diagonal, deterministic, input_Q, input_K, input_V, input_O, input_dO, | ||
| input_Bias, input_SoftmaxOffset, output_S, output_dQ, output_dK, output_dV, output_dBias, | ||
| output_dSoftmaxOffset, input_cu_seqlens_q, input_cu_seqlens_kv, input_cu_seqlens_q_padded, | ||
| input_cu_seqlens_kv_padded, input_rng_state, wkspace, stream, handle); | ||
| #else | ||
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Could you add a couple of SWA tests to the CP tests as well? I think it's just a matter of replacing (left,0) with (left, right) and test them out. Thanks!