ml: Allow models to constrain inputs to a single batch

Models may require that a set of inputs all be processed as part
of the same batch. For example, if an image has multiple patches
with fully connected attention between them, we should not split
the batch in the middle of an image.

Fixes #9697

model/models/gemma3/model.go

@@ -2,10 +2,9 @@ package gemma3
 
 import (
 	"bytes"
-	"encoding/binary"
-	"hash/fnv"
 	"image"
 	"math"
+	"slices"
 
 	"github.com/ollama/ollama/kvcache"
 	"github.com/ollama/ollama/ml"
@@ -112,36 +111,23 @@ func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) (any, er
 	return visionOutputs, nil
 }
 
-type imageToken struct {
-	embedding ml.Tensor
-	index     int
-}
-
 func (m *Model) PostTokenize(ctx ml.Context, inputs []input.Input) ([]input.Input, error) {
 	var result []input.Input
-	fnvHash := fnv.New64a()
 
 	for _, inp := range inputs {
 		if inp.Multimodal == nil {
 			result = append(result, inp)
 		} else {
-			imageInputs := []input.Input{
-				{Token: 108},    // "\n\n"
-				{Token: 255999}, // "<start_of_image>""
-			}
-			result = append(result, imageInputs...)
-
-			// add image embeddings
 			inputMultimodal := inp.Multimodal.(ml.Tensor)
 
-			for i := range inputMultimodal.Dim(1) {
-				fnvHash.Reset()
-				binary.Write(fnvHash, binary.NativeEndian, inp.MultimodalHash)
-				fnvHash.Write([]byte{byte(i)})
+			result = append(result,
+				input.Input{Token: 108, SameBatch: inputMultimodal.Dim(1) + 3},               // "\n\n"
+				input.Input{Token: 255999},                                                   // "<start_of_image>""
+				input.Input{Multimodal: inputMultimodal, MultimodalHash: inp.MultimodalHash}, // image data is on the first placeholder
+			)
 
-				imageToken := imageToken{embedding: inputMultimodal, index: i}
-				result = append(result, input.Input{Multimodal: imageToken, MultimodalHash: fnvHash.Sum64()})
-			}
+			// add image token placeholders
+			result = append(result, slices.Repeat([]input.Input{{Token: 0}}, inputMultimodal.Dim(1)-1)...)
 
 			result = append(result,
 				input.Input{Token: 256000}, // <end_of_image>