Repository: ollama/ollama
Pull request: runner.go: Don't set cross attention before sending embeddings

Currently if an input has embeddings at any point then we will set cross attention to true from the beginning. This means that any tokens before the embeddings are sent will incorrectly have cross attention layers applied.

This only sets cross attention when we have an embedding, either previously in this sequence or in the cache. It also makes cross attention capable of supporting parallelism at the runner level, though the mllama implementation doesn't support that yet.

Changed files:
filename: llama/runner/image.go
patch: @@ -5,6 +5,7 @@ import (
 	"fmt"
 	"hash/maphash"
 	"log/slog"
+	"slices"
 	"sync"
 	"time"
 
@@ -96,6 +97,16 @@ func (c *ImageContext) EmbedSize(llamaContext *llama.Context) int {
 	}
 }
 
+func (c *ImageContext) NeedCrossAttention(inputs ...input) bool {
+	if c == nil || c.mllama == nil {
+		return false
+	}
+
+	return slices.ContainsFunc(inputs, func(input input) bool {
+		return input.embed != nil
+	})
+}
+
 type imageCache struct {
 	key      uint64
 	val      [][]float32

filename: llama/runner/runner.go
patch: @@ -52,6 +52,10 @@ type Sequence struct {
 	// input cache being used by this sequence
 	cache *InputCacheSlot
 
+	// does this sequence require cross-attention layers to be processed? - if we have seen
+	// an image for certain multi-modal models
+	crossAttention bool
+
 	// channel to send responses over
 	responses chan string
 
@@ -287,7 +291,6 @@ func flushPending(seq *Sequence) bool {
 func (s *Server) removeSequence(seqIndex int, reason string) {
 	seq := s.seqs[seqIndex]
 
-	s.lc.SetCrossAttention(false)
 	flushPending(seq)
 	seq.doneReason = reason
 	close(seq.responses)
@@ -334,6 +337,7 @@ func (s *Server) processBatch(tokenBatch *llama.Batch, embedBatch *llama.Batch)
 	defer s.mu.Unlock()
 
 	var batch *llama.Batch
+	crossAttention := false
 
 	seqIdx := s.nextSeq - 1
 	for range s.seqs {
@@ -367,8 +371,9 @@ func (s *Server) processBatch(tokenBatch *llama.Batch, embedBatch *llama.Batch)
 					batch = tokenBatch
 				} else {
 					batch = embedBatch
+					seq.crossAttention = s.image.NeedCrossAttention(input)
 				}
-			} else if embedding != batch.IsEmbedding() {
+			} else if embedding != batch.IsEmbedding() || crossAttention != seq.crossAttention {
 				s.nextSeq = seqIdx
 				break
 			}
@@ -378,6 +383,7 @@ func (s *Server) processBatch(tokenBatch *llama.Batch, embedBatch *llama.Batch)
 				break
 			}
 
+			crossAttention = seq.crossAttention
 			batch.Add(input.token, input.embed, seq.numPast, []int{seq.cache.Id}, numInputsProcessed+1 == len(seq.inputs))
 			seq.numPast++
 			numInputsProcessed++
@@ -394,6 +400,8 @@ func (s *Server) processBatch(tokenBatch *llama.Batch, embedBatch *llama.Batch)
 		return
 	}
 
+	s.lc.SetCrossAttention(crossAttention)
+
 	err := s.lc.Decode(batch)
 	if err != nil {
 		slog.Error("failed to decode batch", "error", err)
@@ -605,20 +613,15 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 	s.mu.Lock()
 	for i, sq := range s.seqs {
 		if sq == nil {
-			for _, input := range seq.inputs {
-				if input.embed != nil {
-					s.lc.SetCrossAttention(true)
-					break
-				}
-			}
-
 			seq.cache, seq.inputs, seq.numPast, err = s.cache.LoadCacheSlot(seq.inputs, req.CachePrompt)
 			if err != nil {
 				s.mu.Unlock()
 				http.Error(w, fmt.Sprintf("Failed to load cache: %v", err), http.StatusInternalServerError)
 				return
 			}
 
+			seq.crossAttention = s.image.NeedCrossAttention(seq.cache.Inputs...)
+
 			s.seqs[i] = seq
 			s.cond.Signal()
 			break