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[Executorch][SDPA] Remove slice creation #9911

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Merged
merged 1 commit into from
Apr 4, 2025
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[Executorch][SDPA] Remove slice creation #9911

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80 changes: 13 additions & 67 deletions extension/llm/custom_ops/op_sdpa.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -273,7 +273,6 @@ Tensor& flash_attention_kernel_out(
Format [n_layers, batch size, max_seq_len, num heads, head dim]
....
@param[in] start_pos: sequence position
@param[in] seq_len: Seq length. e.g. seq_len dim of q_projected.
*/
Tensor& custom_sdpa_out(
RuntimeContext& ctx,
Expand Down Expand Up @@ -306,63 +305,7 @@ Tensor& custom_sdpa_out(
const int64_t seq_len = q.size(1);
auto q_seq_len = q.size(1);

// Refactor the following into create_view util perhaps using
// TensorPtr
std::array<::executorch::aten::DimOrderType, sdpa::impl::kKVDim>
sliced_key_dim_order{0, 1, 2, 3};
std::array<::executorch::aten::SizesType, sdpa::impl::kKVDim>
sliced_key_sizes;
sliced_key_sizes[0] = k.size(0);
sliced_key_sizes[1] = start_pos + seq_len; // key_cache.size(2);
sliced_key_sizes[2] = k.size(2);
sliced_key_sizes[3] = k.size(3);
std::array<::executorch::aten::StridesType, sdpa::impl::kKVDim>
sliced_key_strides;
dim_order_to_stride_nocheck(
sliced_key_sizes.data(),
sliced_key_dim_order.data(),
sdpa::impl::kKVDim,
sliced_key_strides.data());
// since the cache is sliced, the batch stride needs to stay the same.
sliced_key_strides[0] = k.strides()[0];
void* key_cache_data = k.mutable_data_ptr();
TensorImpl k_impl = TensorImpl(
k.scalar_type(),
sdpa::impl::kKVDim,
sliced_key_sizes.data(),
key_cache_data,
sliced_key_dim_order.data(),
sliced_key_strides.data(),
TensorShapeDynamism::STATIC);
Tensor sliced_key_cache(&k_impl);

std::array<::executorch::aten::DimOrderType, sdpa::impl::kKVDim>
sliced_value_dim_order{0, 1, 2, 3};
std::array<::executorch::aten::SizesType, sdpa::impl::kKVDim>
sliced_value_sizes;
sliced_value_sizes[0] = v.size(0);
sliced_value_sizes[1] = start_pos + seq_len; // value_cache.size(2);
sliced_value_sizes[2] = v.size(2);
sliced_value_sizes[3] = v.size(3);
std::array<::executorch::aten::StridesType, sdpa::impl::kKVDim>
sliced_value_strides;
dim_order_to_stride_nocheck(
sliced_value_sizes.data(),
sliced_value_dim_order.data(),
sdpa::impl::kKVDim,
sliced_value_strides.data());
// since the cache is sliced, the batch stride needs to stay the same.
sliced_value_strides[0] = v.strides()[0];
void* value_cache_data = v.mutable_data_ptr();
TensorImpl value_impl = TensorImpl(
v.scalar_type(),
sdpa::impl::kKVDim,
sliced_value_sizes.data(),
value_cache_data,
sliced_value_dim_order.data(),
sliced_value_strides.data(),
TensorShapeDynamism::STATIC);
Tensor sliced_value_cache(&value_impl);
const int64_t num_keys_for_causal_attention = start_pos + seq_len;

ET_KERNEL_CHECK(
ctx,
Expand All @@ -380,38 +323,41 @@ Tensor& custom_sdpa_out(
sdpa::impl::cpu_flash_attention<CTYPE, 256, 512>(
output,
q,
sliced_key_cache,
sliced_value_cache,
k,
v,
dropout_p,
is_causal,
attn_mask,
scale,
true, /* is_seq_at_dim_1 */
start_pos);
start_pos,
num_keys_for_causal_attention);
} else if (q_seq_len >= 192) {
sdpa::impl::cpu_flash_attention<CTYPE, 64, 512>(
output,
q,
sliced_key_cache,
sliced_value_cache,
k,
v,
dropout_p,
is_causal,
attn_mask,
scale,
true, /* is_seq_at_dim_1 */
start_pos);
start_pos,
num_keys_for_causal_attention);
} else {
sdpa::impl::cpu_flash_attention<CTYPE, 32, 512>(
output,
q,
sliced_key_cache,
sliced_value_cache,
k,
v,
dropout_p,
is_causal,
attn_mask,
scale,
true, /* is_seq_at_dim_1 */
start_pos);
start_pos,
num_keys_for_causal_attention);
}
});
return output;
Expand Down
10 changes: 9 additions & 1 deletion extension/llm/custom_ops/op_sdpa_impl.h
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Original file line number Diff line number Diff line change
Expand Up @@ -212,7 +212,8 @@ void cpu_flash_attention(
const optional<Tensor>& attn_mask,
const optional<double>& scale,
bool is_seq_at_dim_1 = false,
const int64_t start_pos = 0) {
const int64_t start_pos = 0,
const int64_t num_keys_for_causal_attention = -1) {
(void)dropout_p;
// Query (Batch x Num_heads x Q_seq_len x Dim_per_head)
// Key (Batch x Num_heads x KV_seq_len x Dim_per_head)
Expand Down Expand Up @@ -258,6 +259,13 @@ void cpu_flash_attention(
kvSize = value.size(1);
}

if (num_keys_for_causal_attention > 0) {
ET_CHECK_MSG(
num_keys_for_causal_attention <= kvSize,
"num_keys_for_causal_attention must be <= kvSize");
kvSize = num_keys_for_causal_attention;
}

ET_CHECK_MSG(
num_heads_kv <= num_head,
"FlashAttention does not support num kv heads > num query heads.Got num query heads=%" PRId64
Expand Down
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