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UPSTREAM PR #1306: improved flux attention qkv unpacking #71

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UPSTREAM PR #1306: improved flux attention qkv unpacking #71

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26 changes: 14 additions & 12 deletions src/flux.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -103,11 +103,13 @@ namespace Flux {
auto norm = std::dynamic_pointer_cast<QKNorm>(blocks["norm"]);

auto qkv = qkv_proj->forward(ctx, x);
auto qkv_vec = ggml_ext_chunk(ctx->ggml_ctx, qkv, 3, 0, true);
int64_t head_dim = qkv_vec[0]->ne[0] / num_heads;
auto q = ggml_reshape_4d(ctx->ggml_ctx, qkv_vec[0], head_dim, num_heads, qkv_vec[0]->ne[1], qkv_vec[0]->ne[2]);
auto k = ggml_reshape_4d(ctx->ggml_ctx, qkv_vec[1], head_dim, num_heads, qkv_vec[1]->ne[1], qkv_vec[1]->ne[2]);
auto v = ggml_reshape_4d(ctx->ggml_ctx, qkv_vec[2], head_dim, num_heads, qkv_vec[2]->ne[1], qkv_vec[2]->ne[2]);
int64_t head_dim = qkv->ne[0] / 3 / num_heads;
auto q = ggml_view_4d(ctx->ggml_ctx, qkv, head_dim, num_heads, qkv->ne[1], qkv->ne[2],
qkv->nb[0]*head_dim, qkv->nb[1], qkv->nb[2], 0);
auto k = ggml_view_4d(ctx->ggml_ctx, qkv, head_dim, num_heads, qkv->ne[1], qkv->ne[2],
qkv->nb[0]*head_dim, qkv->nb[1], qkv->nb[2], (qkv->nb[0])*qkv->ne[0]/3);
auto v = ggml_view_4d(ctx->ggml_ctx, qkv, head_dim, num_heads, qkv->ne[1], qkv->ne[2],
qkv->nb[0]*head_dim, qkv->nb[1], qkv->nb[2], (qkv->nb[0])*2*qkv->ne[0]/3);
q = norm->query_norm(ctx, q);
k = norm->key_norm(ctx, k);
return {q, k, v};
Expand Down Expand Up @@ -491,15 +493,15 @@ namespace Flux {
auto x_mod = Flux::modulate(ctx->ggml_ctx, pre_norm->forward(ctx, x), mod.shift, mod.scale);
auto qkv_mlp = linear1->forward(ctx, x_mod); // [N, n_token, hidden_size * 3 + mlp_hidden_dim*mlp_mult_factor]

auto q = ggml_view_3d(ctx->ggml_ctx, qkv_mlp, hidden_size, qkv_mlp->ne[1], qkv_mlp->ne[2], qkv_mlp->nb[1], qkv_mlp->nb[2], 0);
auto k = ggml_view_3d(ctx->ggml_ctx, qkv_mlp, hidden_size, qkv_mlp->ne[1], qkv_mlp->ne[2], qkv_mlp->nb[1], qkv_mlp->nb[2], hidden_size * qkv_mlp->nb[0]);
auto v = ggml_view_3d(ctx->ggml_ctx, qkv_mlp, hidden_size, qkv_mlp->ne[1], qkv_mlp->ne[2], qkv_mlp->nb[1], qkv_mlp->nb[2], hidden_size * 2 * qkv_mlp->nb[0]);

int64_t head_dim = hidden_size / num_heads;

q = ggml_reshape_4d(ctx->ggml_ctx, ggml_cont(ctx->ggml_ctx, q), head_dim, num_heads, q->ne[1], q->ne[2]); // [N, n_token, n_head, d_head]
k = ggml_reshape_4d(ctx->ggml_ctx, ggml_cont(ctx->ggml_ctx, k), head_dim, num_heads, k->ne[1], k->ne[2]); // [N, n_token, n_head, d_head]
v = ggml_reshape_4d(ctx->ggml_ctx, ggml_cont(ctx->ggml_ctx, v), head_dim, num_heads, v->ne[1], v->ne[2]); // [N, n_token, n_head, d_head]
auto q = ggml_view_4d(ctx->ggml_ctx, qkv_mlp, head_dim, num_heads, qkv_mlp->ne[1], qkv_mlp->ne[2],
qkv_mlp->nb[0]*head_dim, qkv_mlp->nb[1], qkv_mlp->nb[2], 0);
auto k = ggml_view_4d(ctx->ggml_ctx, qkv_mlp, head_dim, num_heads, qkv_mlp->ne[1], qkv_mlp->ne[2],
qkv_mlp->nb[0]*head_dim, qkv_mlp->nb[1], qkv_mlp->nb[2], (qkv_mlp->nb[0])*hidden_size);
auto v = ggml_view_4d(ctx->ggml_ctx, qkv_mlp, head_dim, num_heads, qkv_mlp->ne[1], qkv_mlp->ne[2],
qkv_mlp->nb[0]*head_dim, qkv_mlp->nb[1], qkv_mlp->nb[2], (qkv_mlp->nb[0])*2*hidden_size);


q = norm->query_norm(ctx, q);
k = norm->key_norm(ctx, k);
Expand Down