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Merge pull request #5410 from dhiltgen/ctx_cleanup

Fix case for NumCtx
Daniel Hiltgen 10 months ago
parent
commit
e70610ef06
2 changed files with 9 additions and 9 deletions
  1. 2 2
      envconfig/config.go
  2. 7 7
      server/sched.go

+ 2 - 2
envconfig/config.go

@@ -85,13 +85,13 @@ func AsMap() map[string]EnvVar {
 		"OLLAMA_HOST":              {"OLLAMA_HOST", Host, "IP Address for the ollama server (default 127.0.0.1:11434)"},
 		"OLLAMA_KEEP_ALIVE":        {"OLLAMA_KEEP_ALIVE", KeepAlive, "The duration that models stay loaded in memory (default \"5m\")"},
 		"OLLAMA_LLM_LIBRARY":       {"OLLAMA_LLM_LIBRARY", LLMLibrary, "Set LLM library to bypass autodetection"},
-		"OLLAMA_MAX_LOADED_MODELS": {"OLLAMA_MAX_LOADED_MODELS", MaxRunners, "Maximum number of loaded models per GPU (default auto)"},
+		"OLLAMA_MAX_LOADED_MODELS": {"OLLAMA_MAX_LOADED_MODELS", MaxRunners, "Maximum number of loaded models per GPU"},
 		"OLLAMA_MAX_QUEUE":         {"OLLAMA_MAX_QUEUE", MaxQueuedRequests, "Maximum number of queued requests"},
 		"OLLAMA_MAX_VRAM":          {"OLLAMA_MAX_VRAM", MaxVRAM, "Maximum VRAM"},
 		"OLLAMA_MODELS":            {"OLLAMA_MODELS", ModelsDir, "The path to the models directory"},
 		"OLLAMA_NOHISTORY":         {"OLLAMA_NOHISTORY", NoHistory, "Do not preserve readline history"},
 		"OLLAMA_NOPRUNE":           {"OLLAMA_NOPRUNE", NoPrune, "Do not prune model blobs on startup"},
-		"OLLAMA_NUM_PARALLEL":      {"OLLAMA_NUM_PARALLEL", NumParallel, "Maximum number of parallel requests (default auto)"},
+		"OLLAMA_NUM_PARALLEL":      {"OLLAMA_NUM_PARALLEL", NumParallel, "Maximum number of parallel requests"},
 		"OLLAMA_ORIGINS":           {"OLLAMA_ORIGINS", AllowOrigins, "A comma separated list of allowed origins"},
 		"OLLAMA_RUNNERS_DIR":       {"OLLAMA_RUNNERS_DIR", RunnersDir, "Location for runners"},
 		"OLLAMA_SCHED_SPREAD":      {"OLLAMA_SCHED_SPREAD", SchedSpread, "Always schedule model across all GPUs"},

+ 7 - 7
server/sched.go

@@ -23,7 +23,7 @@ type LlmRequest struct {
 	ctx             context.Context //nolint:containedctx
 	model           *Model
 	opts            api.Options
-	origNumCTX      int // Track the initial ctx request
+	origNumCtx      int // Track the initial ctx request
 	sessionDuration time.Duration
 	successCh       chan *runnerRef
 	errCh           chan error
@@ -118,8 +118,8 @@ func (s *Scheduler) processPending(ctx context.Context) {
 		case pending := <-s.pendingReqCh:
 			// Block other requests until we get this pending request running
 			pending.schedAttempts++
-			if pending.origNumCTX == 0 {
-				pending.origNumCTX = pending.opts.NumCtx
+			if pending.origNumCtx == 0 {
+				pending.origNumCtx = pending.opts.NumCtx
 			}
 
 			if pending.ctx.Err() != nil {
@@ -135,7 +135,7 @@ func (s *Scheduler) processPending(ctx context.Context) {
 			}
 			// Keep NumCtx and numParallel in sync
 			if numParallel > 1 {
-				pending.opts.NumCtx = pending.origNumCTX * numParallel
+				pending.opts.NumCtx = pending.origNumCtx * numParallel
 			}
 
 			for {
@@ -197,7 +197,7 @@ func (s *Scheduler) processPending(ctx context.Context) {
 						// simplifying assumption of defaultParallel when in CPU mode
 						if numParallel <= 0 {
 							numParallel = defaultParallel
-							pending.opts.NumCtx = pending.origNumCTX * numParallel
+							pending.opts.NumCtx = pending.origNumCtx * numParallel
 						}
 
 						if loadedCount == 0 {
@@ -691,7 +691,7 @@ func pickBestFitGPUs(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList, numP
 
 		// First attempt to fit the model into a single GPU
 		for _, p := range numParallelToTry {
-			req.opts.NumCtx = req.origNumCTX * p
+			req.opts.NumCtx = req.origNumCtx * p
 			if !envconfig.SchedSpread {
 				for _, g := range sgl {
 					if ok, estimatedVRAM = llm.PredictServerFit([]gpu.GpuInfo{g}, ggml, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts); ok {
@@ -709,7 +709,7 @@ func pickBestFitGPUs(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList, numP
 
 		// Now try all the GPUs
 		for _, p := range numParallelToTry {
-			req.opts.NumCtx = req.origNumCTX * p
+			req.opts.NumCtx = req.origNumCtx * p
 			if ok, estimatedVRAM = llm.PredictServerFit(sgl, ggml, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts); ok {
 				slog.Info("new model will fit in available VRAM, loading", "model", req.model.ModelPath, "library", sgl[0].Library, "parallel", p, "required", format.HumanBytes2(estimatedVRAM))
 				*numParallel = p