llamarunner: update metrics

this change updates how metrics are collected. until now, performance
metrics, specifically initial input processing and subsequent generation
durations, were collected by taking the timestamp when creating a new
sequence, the first token generation, and completing generation. the
processing duration is taken as first token generation sub sequence
creation while generation is taken as completing generation sub first
token generation.

while this approach is an accurate end-to-end metric of processing and
generation, it's not comparable to other tools which only measure the
active, i.e. decode, duration.

this change updates the metrics to only capture decode duration so it
can be more directly compared to other tools

runner/llamarunner/runner.go

@@ -82,10 +82,10 @@ type Sequence struct {
 	doneReason llm.DoneReason
 
 	// Metrics
-	startProcessingTime time.Time
-	startGenerationTime time.Time
-	numDecoded          int
-	numPromptInputs     int
+	processingDuration time.Duration
+	generationDuration time.Duration
+	numDecoded         int
+	numPromptInputs    int
 }
 
 type NewSequenceParams struct {
@@ -99,8 +99,6 @@ type NewSequenceParams struct {
 func (s *Server) NewSequence(prompt string, images []llm.ImageData, params NewSequenceParams) (*Sequence, error) {
 	s.ready.Wait()
 
-	startTime := time.Now()
-
 	inputs, err := s.inputs(prompt, images)
 	if err != nil {
 		return nil, fmt.Errorf("failed to process inputs: %w", err)
@@ -142,18 +140,17 @@ func (s *Server) NewSequence(prompt string, images []llm.ImageData, params NewSe
 	}
 
 	return &Sequence{
-		inputs:              inputs,
-		numPromptInputs:     len(inputs),
-		startProcessingTime: startTime,
-		numPredict:          params.numPredict,
-		pendingResponses:    make([]string, 0),
-		responses:           make(chan string, 100),
-		quit:                make(chan bool, 1),
-		embedding:           make(chan []float32, 1),
-		samplingCtx:         sc,
-		embeddingOnly:       params.embedding,
-		stop:                params.stop,
-		numKeep:             params.numKeep,
+		inputs:           inputs,
+		numPromptInputs:  len(inputs),
+		numPredict:       params.numPredict,
+		pendingResponses: make([]string, 0),
+		responses:        make(chan string, 100),
+		quit:             make(chan bool, 1),
+		embedding:        make(chan []float32, 1),
+		samplingCtx:      sc,
+		embeddingOnly:    params.embedding,
+		stop:             params.stop,
+		numKeep:          params.numKeep,
 	}, nil
 }
 
@@ -438,8 +435,8 @@ func (s *Server) processBatch(tokenBatch *llama.Batch, embedBatch *llama.Batch)
 		return nil
 	}
 
-	err := s.lc.Decode(batch)
-	if err != nil {
+	t := time.Now()
+	if err := s.lc.Decode(batch); err != nil {
 		return fmt.Errorf("failed to decode batch: %w", err)
 	}
 
@@ -459,9 +456,12 @@ func (s *Server) processBatch(tokenBatch *llama.Batch, embedBatch *llama.Batch)
 			continue
 		}
 
-		seq.numDecoded += 1
-		if seq.numDecoded == 1 {
-			seq.startGenerationTime = time.Now()
+		s.lc.Synchronize()
+		seq.numDecoded++
+		if seq.numDecoded > 1 {
+			seq.generationDuration += time.Since(t)
+		} else {
+			seq.processingDuration += time.Since(t)
 		}
 
 		// if done processing the prompt, generate an embedding and return
@@ -646,9 +646,9 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 					Done:               true,
 					DoneReason:         seq.doneReason,
 					PromptEvalCount:    seq.numPromptInputs,
-					PromptEvalDuration: seq.startGenerationTime.Sub(seq.startProcessingTime),
+					PromptEvalDuration: seq.processingDuration,
 					EvalCount:          seq.numDecoded,
-					EvalDuration:       time.Since(seq.startGenerationTime),
+					EvalDuration:       seq.generationDuration,
 				}); err != nil {
 					http.Error(w, fmt.Sprintf("failed to encode final response: %v", err), http.StatusInternalServerError)
 				}