ollama/server/sched_test.go
2026-06-16 12:55:52 -07:00

2248 lines
72 KiB
Go

package server
import (
"bytes"
"context"
"errors"
"log/slog"
"os"
"sync"
"testing"
"time"
"github.com/stretchr/testify/require"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/format"
"github.com/ollama/ollama/fs/ggml"
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/ml"
"github.com/ollama/ollama/types/model"
)
func TestMain(m *testing.M) {
os.Setenv("OLLAMA_DEBUG", "1")
logger := slog.New(slog.NewTextHandler(os.Stdout, &slog.HandlerOptions{Level: slog.LevelDebug}))
slog.SetDefault(logger)
os.Exit(m.Run())
}
func TestSchedInit(t *testing.T) {
ctx, done := context.WithCancel(t.Context())
defer done()
s := InitScheduler(ctx)
s.loadedMu.Lock()
require.NotNil(t, s.loaded)
s.loadedMu.Unlock()
}
func TestSchedLoad(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 20*time.Millisecond)
defer done()
s := InitScheduler(ctx)
s.waitForRecovery = 10 * time.Millisecond
modelPath, _ := createBinFile(t, ggml.KV{
"general.architecture": "llama",
"llama.context_length": uint32(32),
"llama.embedding_length": uint32(4096),
"llama.block_count": uint32(1),
"llama.attention.head_count": uint32(32),
"llama.attention.head_count_kv": uint32(32),
"tokenizer.ggml.tokens": []string{" "},
"tokenizer.ggml.scores": []float32{0},
"tokenizer.ggml.token_type": []int32{0},
}, []*ggml.Tensor{
{Name: "blk.0.attn.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
{Name: "output.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
})
req := &LlmRequest{
ctx: ctx,
model: &Model{ModelPath: modelPath},
opts: api.DefaultOptions(),
successCh: make(chan *runnerRef, 1),
errCh: make(chan error, 1),
sessionDuration: &api.Duration{Duration: 2 * time.Second},
}
// Fail to load model first
s.newServerFn = func(systemInfo ml.SystemInfo, gpus []ml.DeviceInfo, model string, f *ggml.GGML, adapters []string, projectors []string, opts api.Options, numParallel int, _ llm.LlamaServerConfig) (llm.LlamaServer, error) {
return nil, errors.New("something failed to load model blah")
}
gpus := []ml.DeviceInfo{}
systemInfo := ml.SystemInfo{}
s.load(req, systemInfo, gpus, false)
require.Empty(t, req.successCh)
require.Len(t, req.errCh, 1)
s.loadedMu.Lock()
require.Empty(t, s.loaded)
s.loadedMu.Unlock()
err := <-req.errCh
require.Contains(t, err.Error(), "this model may be incompatible")
server := &mockLlm{vramSize: 10, vramByGPU: map[ml.DeviceID]uint64{}}
s.newServerFn = func(systemInfo ml.SystemInfo, gpus []ml.DeviceInfo, model string, f *ggml.GGML, adapters []string, projectors []string, opts api.Options, numParallel int, _ llm.LlamaServerConfig) (llm.LlamaServer, error) {
server.modelPath = model
return server, nil
}
s.load(req, systemInfo, gpus, false)
select {
case err := <-req.errCh:
require.NoError(t, err)
case resp := <-req.successCh:
require.Equal(t, uint64(10), resp.vramSize)
require.Equal(t, uint(1), resp.refCount)
s.loadedMu.Lock()
require.Len(t, s.loaded, 1)
s.loadedMu.Unlock()
}
modelPath2, _ := createBinFile(t, ggml.KV{
"general.architecture": "llama",
"llama.context_length": uint32(32),
"llama.embedding_length": uint32(4096),
"llama.block_count": uint32(1),
"llama.attention.head_count": uint32(32),
"llama.attention.head_count_kv": uint32(32),
"tokenizer.ggml.tokens": []string{" "},
"tokenizer.ggml.scores": []float32{0},
"tokenizer.ggml.token_type": []int32{0},
}, []*ggml.Tensor{
{Name: "blk.0.attn.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
{Name: "output.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
})
req.model.ModelPath = modelPath2
server.waitResp = errors.New("wait failure")
s.load(req, systemInfo, gpus, false)
select {
case err := <-req.errCh:
require.Contains(t, err.Error(), "wait failure")
case resp := <-req.successCh:
t.Fatalf("unexpected success %v", resp)
}
s.loadedMu.Lock()
runner := s.loaded[modelPath2]
s.loadedMu.Unlock()
require.NotNil(t, runner)
require.Equal(t, uint(0), runner.refCount)
time.Sleep(1 * time.Millisecond)
require.Len(t, s.expiredCh, 1)
}
func TestSchedLoadStoresEffectiveContextLength(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 500*time.Millisecond)
defer done()
s := InitScheduler(ctx)
scenario := newScenarioRequest(t, ctx, "test", 10, nil, map[ml.DeviceID]uint64{})
scenario.req.opts.NumCtx = 262144
scenario.req.numCtxAuto = true
scenario.srv.contextLength = 131072
s.newServerFn = scenario.newServer
s.load(scenario.req, ml.SystemInfo{}, nil, false)
select {
case err := <-scenario.req.errCh:
require.NoError(t, err)
case runner := <-scenario.req.successCh:
require.Equal(t, 131072, runner.Options.NumCtx)
}
}
func TestSchedLoadStoresEffectiveExplicitContextLength(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 500*time.Millisecond)
defer done()
s := InitScheduler(ctx)
scenario := newScenarioRequest(t, ctx, "test", 10, nil, map[ml.DeviceID]uint64{})
scenario.req.opts.NumCtx = 262144
scenario.srv.contextLength = 131072
s.newServerFn = scenario.newServer
s.load(scenario.req, ml.SystemInfo{}, nil, false)
select {
case err := <-scenario.req.errCh:
require.NoError(t, err)
case runner := <-scenario.req.successCh:
require.Equal(t, 131072, runner.Options.NumCtx)
}
}
func TestSchedVisionContextFloor(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 500*time.Millisecond)
defer done()
visionModel := &Model{
Name: "vision-test",
Config: model.ConfigV2{
Capabilities: []string{string(model.CapabilityVision)},
},
}
t.Run("automatic num_ctx is floored", func(t *testing.T) {
s := InitScheduler(ctx)
opts := api.DefaultOptions()
opts.NumCtx = 128
s.getRunner(ctx, visionModel, opts, nil, true, false, nil)
req := <-s.pendingReqCh
require.Equal(t, 2048, req.opts.NumCtx)
require.True(t, req.numCtxAuto)
})
t.Run("explicit num_ctx is floored", func(t *testing.T) {
s := InitScheduler(ctx)
opts := api.DefaultOptions()
opts.NumCtx = 128
s.getRunner(ctx, visionModel, opts, nil, false, false, nil)
req := <-s.pendingReqCh
require.Equal(t, 2048, req.opts.NumCtx)
require.False(t, req.numCtxAuto)
})
}
type reqBundle struct {
ctx context.Context //nolint:containedctx
ctxDone func()
srv *mockLlm
req *LlmRequest
}
func (scenario *reqBundle) newServer(systemInfo ml.SystemInfo, gpus []ml.DeviceInfo, model string, f *ggml.GGML, adapters []string, projectors []string, opts api.Options, numParallel int, _ llm.LlamaServerConfig) (llm.LlamaServer, error) {
scenario.srv.modelPath = model
return scenario.srv, nil
}
func newScenarioRequest(t *testing.T, ctx context.Context, modelName string, vramSize uint64, duration *api.Duration, vramByGPU map[ml.DeviceID]uint64) *reqBundle {
return newScenarioRequestWithContext(t, ctx, modelName, vramSize, duration, vramByGPU, 32)
}
func newScenarioRequestWithContext(t *testing.T, ctx context.Context, modelName string, vramSize uint64, duration *api.Duration, vramByGPU map[ml.DeviceID]uint64, trainCtx uint32) *reqBundle {
b := &reqBundle{}
b.ctx, b.ctxDone = context.WithCancel(ctx)
t.Helper()
p, _ := createBinFile(t, ggml.KV{
"general.architecture": "llama",
"llama.context_length": trainCtx,
"llama.embedding_length": uint32(4096),
"llama.block_count": uint32(1),
"llama.attention.head_count": uint32(32),
"llama.attention.head_count_kv": uint32(32),
"tokenizer.ggml.tokens": []string{" "},
"tokenizer.ggml.scores": []float32{0},
"tokenizer.ggml.token_type": []int32{0},
}, []*ggml.Tensor{
{Name: "blk.0.attn.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
{Name: "output.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
})
model := &Model{Name: modelName, ModelPath: p}
if duration == nil {
duration = &api.Duration{Duration: 5 * time.Millisecond}
}
b.req = &LlmRequest{
ctx: b.ctx,
model: model,
opts: api.DefaultOptions(),
sessionDuration: duration,
successCh: make(chan *runnerRef, 1),
errCh: make(chan error, 1),
}
b.srv = &mockLlm{vramSize: vramSize, vramByGPU: vramByGPU}
return b
}
func getGpuFn(ctx context.Context, runners []ml.FilteredRunnerDiscovery) []ml.DeviceInfo {
slog.Info("test getGpuFn called", "runners", runners)
g := ml.DeviceInfo{DeviceID: ml.DeviceID{Library: "Metal"}}
g.TotalMemory = 24 * format.GigaByte
g.FreeMemory = 12 * format.GigaByte
return []ml.DeviceInfo{g}
}
func getSystemInfoFn() ml.SystemInfo {
slog.Info("test getSystemInfoFn called")
return ml.SystemInfo{
TotalMemory: 32 * format.GigaByte,
FreeMemory: 26 * format.GigaByte,
}
}
func TestSchedRequestsSameModelSameRequest(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 500*time.Millisecond)
defer done()
s := InitScheduler(ctx)
s.waitForRecovery = 10 * time.Millisecond
s.getGpuFn = getGpuFn
s.getSystemInfoFn = getSystemInfoFn
a := newScenarioRequest(t, ctx, "ollama-model-1", 10, &api.Duration{Duration: 5 * time.Millisecond}, nil)
b := newScenarioRequest(t, ctx, "ollama-model-1", 11, &api.Duration{Duration: 0}, nil)
b.req.model = a.req.model
s.newServerFn = a.newServer
slog.Info("a")
s.pendingReqCh <- a.req
require.Len(t, s.pendingReqCh, 1)
s.Run(ctx)
select {
case resp := <-a.req.successCh:
require.Equal(t, resp.llama, a.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, a.req.errCh)
case err := <-a.req.errCh:
t.Fatal(err.Error())
case <-ctx.Done():
t.Fatal("timeout")
}
// Same runner as first request due to not needing a reload
s.newServerFn = b.newServer
slog.Info("b")
s.pendingReqCh <- b.req
select {
case resp := <-b.req.successCh:
require.Equal(t, resp.llama, a.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, b.req.errCh)
case err := <-b.req.errCh:
t.Fatal(err.Error())
case <-ctx.Done():
t.Fatal("timeout")
}
}
func TestSchedRequestsSimpleReloadSameModel(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 5000*time.Millisecond)
defer done()
s := InitScheduler(ctx)
s.waitForRecovery = 10 * time.Millisecond
g := ml.DeviceInfo{DeviceID: ml.DeviceID{Library: "Metal"}}
g.TotalMemory = 24 * format.GigaByte
g.FreeMemory = 12 * format.GigaByte
gMu := sync.Mutex{}
s.getGpuFn = func(ctx context.Context, runners []ml.FilteredRunnerDiscovery) []ml.DeviceInfo {
slog.Info("test getGpuFn called", "runners", runners)
gMu.Lock()
defer gMu.Unlock()
return []ml.DeviceInfo{g}
}
s.getSystemInfoFn = getSystemInfoFn
a := newScenarioRequest(t, ctx, "ollama-model-1", 10, &api.Duration{Duration: 5 * time.Millisecond}, nil)
b := newScenarioRequest(t, ctx, "ollama-model-1", 20, &api.Duration{Duration: 5 * time.Millisecond}, nil)
tmpModel := *a.req.model
b.req.model = &tmpModel
s.newServerFn = a.newServer
slog.Info("a")
s.pendingReqCh <- a.req
require.Len(t, s.pendingReqCh, 1)
s.Run(ctx)
select {
case resp := <-a.req.successCh:
require.Equal(t, resp.llama, a.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, a.req.errCh)
case err := <-a.req.errCh:
t.Fatal(err.Error())
case <-ctx.Done():
t.Fatal("timeout")
}
// Trigger a reload
s.newServerFn = b.newServer
b.req.model.AdapterPaths = []string{"new"}
slog.Info("b")
s.pendingReqCh <- b.req
// finish first two requests, so model can reload
time.Sleep(1 * time.Millisecond)
a.ctxDone()
// Report recovered VRAM usage
time.Sleep(1 * time.Millisecond)
gMu.Lock()
g.FreeMemory = 24 * format.GigaByte
gMu.Unlock()
select {
case resp := <-b.req.successCh:
require.Equal(t, resp.llama, b.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, b.req.errCh)
case err := <-b.req.errCh:
t.Fatal(err.Error())
case <-ctx.Done():
t.Fatal("timeout")
}
}
func TestSchedRequestsMultipleLoadedModels(t *testing.T) {
slog.Info("TestRequestsMultipleLoadedModels")
ctx, done := context.WithTimeout(t.Context(), 1000*time.Millisecond)
defer done()
s := InitScheduler(ctx)
s.waitForRecovery = 10 * time.Millisecond
g := ml.DeviceInfo{DeviceID: ml.DeviceID{Library: "Metal"}}
g.TotalMemory = 24 * format.GigaByte
g.FreeMemory = 12 * format.GigaByte
gMu := sync.Mutex{}
s.getGpuFn = func(ctx context.Context, runners []ml.FilteredRunnerDiscovery) []ml.DeviceInfo {
slog.Info("test getGpuFn called", "runners", runners)
gMu.Lock()
defer gMu.Unlock()
return []ml.DeviceInfo{g}
}
s.getSystemInfoFn = getSystemInfoFn
// Multiple loaded models
a := newScenarioRequest(t, ctx, "model-a-1g-gpu", 1*format.GigaByte, nil, map[ml.DeviceID]uint64{{Library: "Metal"}: 1 * format.GigaByte})
a.req.sessionDuration = &api.Duration{Duration: 5 * time.Millisecond}
b := newScenarioRequest(t, ctx, "model-b-10g-gpu", 10*format.GigaByte, nil, map[ml.DeviceID]uint64{{Library: "Metal"}: 10 * format.GigaByte})
b.req.sessionDuration = &api.Duration{Duration: 5 * time.Millisecond}
c := newScenarioRequest(t, ctx, "model-c-10g-cpu", 10*format.GigaByte, nil, nil /* No GPU load */)
c.req.opts.NumGPU = 0 // CPU load, will be allowed
b.req.sessionDuration = &api.Duration{Duration: 10 * time.Millisecond} // longer than b to cause the scheduler to favor unloading b over c
d := newScenarioRequest(t, ctx, "model-d-10g-gpu", 13*format.GigaByte, nil, map[ml.DeviceID]uint64{{Library: "Metal"}: 13 * format.GigaByte}) // Needs prior unloaded
s.newServerFn = a.newServer
slog.Info("Loading A")
s.pendingReqCh <- a.req
s.Run(ctx)
select {
case resp := <-a.req.successCh:
require.Equal(t, resp.llama, a.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, a.req.errCh)
case err := <-a.req.errCh:
t.Fatal(err.Error())
case <-ctx.Done():
t.Fatal("timeout")
}
s.loadedMu.Lock()
require.Len(t, s.loaded, 1)
s.loadedMu.Unlock()
t.Setenv("OLLAMA_MAX_LOADED_MODELS", "0")
s.newServerFn = b.newServer
slog.Info("Loading B")
s.pendingReqCh <- b.req
select {
case resp := <-b.req.successCh:
require.Equal(t, resp.llama, b.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, b.req.errCh)
case err := <-b.req.errCh:
t.Fatal(err.Error())
case <-ctx.Done():
t.Fatal("timeout")
}
s.loadedMu.Lock()
require.Len(t, s.loaded, 2)
s.loadedMu.Unlock()
// This is a CPU load with NumGPU = 0 so it should load
s.newServerFn = c.newServer
slog.Info("Loading C")
s.pendingReqCh <- c.req
select {
case resp := <-c.req.successCh:
require.Equal(t, resp.llama, c.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, c.req.errCh)
case err := <-c.req.errCh:
t.Fatal(err.Error())
case <-ctx.Done():
slog.Info("FAIL: scheduler state", "s.loaded", s.loaded)
t.Fatal("timeout")
}
s.loadedMu.Lock()
require.Len(t, s.loaded, 3)
s.loadedMu.Unlock()
// Try to load a model that won't fit
s.newServerFn = d.newServer
slog.Info("d")
s.loadedMu.Lock()
require.Len(t, s.loaded, 3)
s.loadedMu.Unlock()
a.ctxDone() // Won't help since this one isn't big enough to make room
time.Sleep(2 * time.Millisecond)
s.pendingReqCh <- d.req
// finish prior request, so new model can load
time.Sleep(6 * time.Millisecond)
s.loadedMu.Lock()
require.Len(t, s.loaded, 2)
s.loadedMu.Unlock()
// Mark b done so it can unload
b.ctxDone()
// Report recovered VRAM usage so scheduler will finish waiting and unload
time.Sleep(1 * time.Millisecond)
gMu.Lock()
g.FreeMemory = 24 * format.GigaByte
gMu.Unlock()
select {
case resp := <-d.req.successCh:
require.Equal(t, resp.llama, d.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, d.req.errCh)
case <-ctx.Done():
t.Fatal("timeout")
}
// Wait for b to close
closeWait:
for {
select {
case <-ctx.Done():
t.Fatal("timeout")
default:
if b.srv.closeCalled {
break closeWait
}
time.Sleep(1 * time.Millisecond)
}
}
s.loadedMu.Lock()
require.Len(t, s.loaded, 2)
s.loadedMu.Unlock()
}
func TestSchedGetRunner(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 3*time.Second)
defer done()
a := newScenarioRequest(t, ctx, "ollama-model-1a", 10, &api.Duration{Duration: 2 * time.Millisecond}, nil)
b := newScenarioRequest(t, ctx, "ollama-model-1b", 10, &api.Duration{Duration: 2 * time.Millisecond}, nil)
c := newScenarioRequest(t, ctx, "ollama-model-1c", 10, &api.Duration{Duration: 2 * time.Millisecond}, nil)
t.Setenv("OLLAMA_MAX_QUEUE", "1")
s := InitScheduler(ctx)
s.waitForRecovery = 10 * time.Millisecond
s.getGpuFn = getGpuFn
s.getSystemInfoFn = getSystemInfoFn
s.newServerFn = a.newServer
slog.Info("a")
successCh1a, errCh1a := s.GetRunner(a.ctx, a.req.model, a.req.opts, a.req.sessionDuration)
require.Len(t, s.pendingReqCh, 1)
slog.Info("b")
successCh1b, errCh1b := s.GetRunner(b.ctx, b.req.model, b.req.opts, b.req.sessionDuration)
require.Len(t, s.pendingReqCh, 1)
require.Empty(t, successCh1b)
require.Len(t, errCh1b, 1)
err := <-errCh1b
require.Contains(t, err.Error(), "server busy")
s.Run(ctx)
select {
case resp := <-successCh1a:
require.Equal(t, resp.llama, a.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, errCh1a)
case err := <-errCh1a:
t.Fatal(err.Error())
case <-ctx.Done():
t.Fatal("timeout")
}
a.ctxDone() // Set "a" model to idle so it can unload
s.loadedMu.Lock()
require.Len(t, s.loaded, 1)
s.loadedMu.Unlock()
c.req.model.ModelPath = "bad path"
slog.Info("c")
successCh1c, errCh1c := s.GetRunner(c.ctx, c.req.model, c.req.opts, c.req.sessionDuration)
// Starts in pending channel, then should be quickly processed to return an error
time.Sleep(50 * time.Millisecond) // Long enough for the "a" model to expire and unload
require.Empty(t, successCh1c)
s.loadedMu.Lock()
require.Empty(t, s.loaded)
s.loadedMu.Unlock()
require.Len(t, errCh1c, 1)
err = <-errCh1c
require.Contains(t, err.Error(), "bad path")
b.ctxDone()
}
func TestSchedGetRunnerUsesDigestKeyWhenModelPathEmpty(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 100*time.Millisecond)
defer done()
s := InitScheduler(ctx)
opts := api.DefaultOptions()
opts.NumCtx = 4
loadedModel := &Model{Name: "safetensors-a", Digest: "sha-a"}
loadedRunner := &runnerRef{
model: loadedModel,
modelKey: schedulerModelKey(loadedModel),
llama: &mockLlm{vramByGPU: map[ml.DeviceID]uint64{}},
Options: &opts,
numParallel: 1,
}
s.loadedMu.Lock()
s.loaded[loadedRunner.modelKey] = loadedRunner
s.loadedMu.Unlock()
reqModel := &Model{Name: "safetensors-b", Digest: "sha-b"}
successCh, errCh := s.GetRunner(ctx, reqModel, opts, nil)
require.Empty(t, successCh)
require.Empty(t, errCh)
require.Len(t, s.pendingReqCh, 1)
}
func TestSchedGetRunnerReusesSameDigestWhenModelPathEmpty(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 100*time.Millisecond)
defer done()
s := InitScheduler(ctx)
opts := api.DefaultOptions()
opts.NumCtx = 4
loadedModel := &Model{Name: "safetensors-a", Digest: "sha-a"}
loadedRunner := &runnerRef{
model: loadedModel,
modelKey: schedulerModelKey(loadedModel),
llama: &mockLlm{vramByGPU: map[ml.DeviceID]uint64{}},
Options: &opts,
numParallel: 1,
}
s.loadedMu.Lock()
s.loaded[loadedRunner.modelKey] = loadedRunner
s.loadedMu.Unlock()
reqCtx, cancelReq := context.WithCancel(ctx)
successCh, errCh := s.GetRunner(reqCtx, &Model{Name: "safetensors-a-copy", Digest: "sha-a"}, opts, nil)
cancelReq()
select {
case runner := <-successCh:
require.Equal(t, loadedRunner, runner)
default:
t.Fatal("expected existing runner to be reused")
}
require.Empty(t, errCh)
require.Empty(t, s.pendingReqCh)
}
func TestSchedExpireRunner(t *testing.T) {
ctx, done := context.WithCancel(t.Context())
defer done()
s := InitScheduler(ctx)
s.waitForRecovery = 10 * time.Millisecond
modelPath, _ := createBinFile(t, ggml.KV{
"general.architecture": "llama",
"llama.context_length": uint32(32),
"llama.embedding_length": uint32(4096),
"llama.block_count": uint32(1),
"llama.attention.head_count": uint32(32),
"llama.attention.head_count_kv": uint32(32),
"tokenizer.ggml.tokens": []string{" "},
"tokenizer.ggml.scores": []float32{0},
"tokenizer.ggml.token_type": []int32{0},
}, []*ggml.Tensor{
{Name: "blk.0.attn.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
{Name: "output.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
})
reqCtx, cancelReq := context.WithCancel(ctx)
defer cancelReq()
req := &LlmRequest{
ctx: reqCtx,
model: &Model{ModelPath: modelPath},
opts: api.DefaultOptions(),
successCh: make(chan *runnerRef, 1),
errCh: make(chan error, 1),
sessionDuration: &api.Duration{Duration: 2 * time.Minute},
}
gpus := []ml.DeviceInfo{}
systemInfo := ml.SystemInfo{}
server := &mockLlm{vramSize: 10, vramByGPU: map[ml.DeviceID]uint64{}}
s.newServerFn = func(systemInfo ml.SystemInfo, gpus []ml.DeviceInfo, model string, f *ggml.GGML, adapters []string, projectors []string, opts api.Options, numParallel int, _ llm.LlamaServerConfig) (llm.LlamaServer, error) {
server.modelPath = model
return server, nil
}
s.load(req, systemInfo, gpus, false)
select {
case err := <-req.errCh:
if err != nil {
t.Fatalf("expected no errors when loading, got '%s'", err.Error())
}
case resp := <-req.successCh:
s.loadedMu.Lock()
if resp.refCount != uint(1) || len(s.loaded) != 1 {
t.Fatalf("expected a model to be loaded")
}
s.loadedMu.Unlock()
}
completedDone := make(chan struct{})
go func() {
defer close(completedDone)
s.processCompleted(ctx)
}()
s.expireRunner(&Model{ModelPath: modelPath})
cancelReq()
select {
case <-s.unloadedCh:
case <-time.After(5 * time.Second):
t.Fatal("expected model to be unloaded")
}
s.loadedMu.Lock()
if len(s.loaded) != 0 {
t.Fatalf("expected model to be unloaded")
}
s.loadedMu.Unlock()
done()
select {
case <-completedDone:
case <-time.After(5 * time.Second):
t.Fatal("expected completed loop to stop")
}
}
// TODO - add one scenario that triggers the bogus finished event with positive ref count
func TestSchedPrematureExpired(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 1000*time.Millisecond)
defer done()
// Same model, same request
scenario1a := newScenarioRequest(t, ctx, "ollama-model-1a", 10, &api.Duration{Duration: 100 * time.Millisecond}, nil)
s := InitScheduler(ctx)
s.waitForRecovery = 10 * time.Millisecond
s.getGpuFn = getGpuFn
s.getSystemInfoFn = getSystemInfoFn
s.newServerFn = scenario1a.newServer
successCh1a, errCh1a := s.GetRunner(scenario1a.ctx, scenario1a.req.model, scenario1a.req.opts, scenario1a.req.sessionDuration)
require.Len(t, s.pendingReqCh, 1)
s.Run(ctx)
select {
case resp := <-successCh1a:
require.Equal(t, resp.llama, scenario1a.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, errCh1a)
s.loadedMu.Lock()
require.Len(t, s.loaded, 1)
s.loadedMu.Unlock()
slog.Info("sending premature expired event now")
s.expiredCh <- resp // Shouldn't happen in real life, but make sure its safe
case err := <-errCh1a:
t.Fatal(err.Error())
case <-ctx.Done():
t.Fatal("timeout")
}
time.Sleep(scenario1a.req.sessionDuration.Duration)
scenario1a.ctxDone()
time.Sleep(20 * time.Millisecond)
require.LessOrEqual(t, len(s.finishedReqCh), 1)
time.Sleep(10 * time.Millisecond)
require.Empty(t, s.finishedReqCh)
s.loadedMu.Lock()
require.Empty(t, s.loaded)
s.loadedMu.Unlock()
// also shouldn't happen in real life
s.finishedReqCh <- scenario1a.req
time.Sleep(5 * time.Millisecond)
}
func TestSchedUseLoadedRunner(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 100*time.Millisecond)
req := &LlmRequest{
ctx: ctx,
opts: api.DefaultOptions(),
successCh: make(chan *runnerRef, 1),
sessionDuration: &api.Duration{Duration: 2},
}
finished := make(chan *LlmRequest)
llm1 := &mockLlm{vramByGPU: map[ml.DeviceID]uint64{}}
r1 := &runnerRef{llama: llm1, sessionDuration: 1, numParallel: 1}
req.useLoadedRunner(r1, finished)
require.Equal(t, uint(1), r1.refCount)
require.Equal(t, time.Duration(2), r1.sessionDuration)
select {
case success := <-req.successCh:
require.Equal(t, r1, success)
case err := <-req.errCh:
t.Fatal(err.Error())
case <-ctx.Done():
t.Fatal("timeout")
}
done()
fin := <-finished
require.Equal(t, req, fin)
}
func TestSchedUpdateFreeSpace(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 100*time.Millisecond)
defer done()
gpus := []ml.DeviceInfo{
{
DeviceID: ml.DeviceID{
ID: "1",
},
},
{
DeviceID: ml.DeviceID{
ID: "2",
},
},
}
gpus[0].TotalMemory = 1000
gpus[0].FreeMemory = 900
gpus[1].TotalMemory = 2000
gpus[1].FreeMemory = 1900
gpuIDs := []ml.DeviceID{
{
ID: "1",
},
{
ID: "2",
},
}
llm1 := &mockLlm{vramByGPU: map[ml.DeviceID]uint64{{ID: "1"}: 50, {ID: "2"}: 50}}
llm2 := &mockLlm{vramByGPU: map[ml.DeviceID]uint64{{ID: "1"}: 125, {ID: "2"}: 75}}
r1 := &runnerRef{llama: llm1, gpus: gpuIDs, numParallel: 1}
r2 := &runnerRef{llama: llm2, gpus: gpuIDs, numParallel: 1}
s := InitScheduler(ctx)
s.waitForRecovery = 10 * time.Millisecond
s.loadedMu.Lock()
s.loaded["a"] = r1
s.loaded["b"] = r2
s.loadedMu.Unlock()
s.updateFreeSpace(gpus)
require.Equal(t, uint64(1000-50-125), gpus[0].FreeMemory)
require.Equal(t, uint64(2000-50-75), gpus[1].FreeMemory)
}
func TestSchedFindRunnerToUnload(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 100*time.Millisecond)
defer done()
r1 := &runnerRef{refCount: 1, sessionDuration: 1, numParallel: 1}
r2 := &runnerRef{sessionDuration: 2, numParallel: 1}
s := InitScheduler(ctx)
s.waitForRecovery = 10 * time.Millisecond
s.loadedMu.Lock()
s.loaded["a"] = r1
s.loaded["b"] = r2
s.loadedMu.Unlock()
resp := s.findRunnerToUnload()
require.Equal(t, r2, resp)
r2.refCount = 1
resp = s.findRunnerToUnload()
require.Equal(t, r1, resp)
}
func TestSchedNeedsReload(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 100*time.Millisecond)
defer done()
llm := &mockLlm{vramByGPU: map[ml.DeviceID]uint64{}}
do := api.DefaultOptions()
runner := &runnerRef{
model: &Model{
AdapterPaths: []string{"adapter1"},
ProjectorPaths: []string{"projector1"},
},
Options: &do,
llama: llm,
numParallel: 1,
}
req := &LlmRequest{
model: &Model{
AdapterPaths: []string{"adapter2"},
ProjectorPaths: []string{"projector2"},
},
opts: api.DefaultOptions(),
}
resp := runner.needsReload(ctx, req)
require.True(t, resp)
req.model.AdapterPaths = runner.model.AdapterPaths
resp = runner.needsReload(ctx, req)
require.True(t, resp)
req.model.ProjectorPaths = runner.model.ProjectorPaths
runner.loading = true
req.opts.NumBatch = 1234
resp = runner.needsReload(ctx, req)
require.True(t, resp)
req.opts.NumBatch = runner.Options.NumBatch
llm.pingResp = errors.New("foo")
resp = runner.needsReload(ctx, req)
require.True(t, resp)
llm.pingResp = nil
resp = runner.needsReload(ctx, req)
require.False(t, resp)
req.opts.NumGPU = 99
resp = runner.needsReload(ctx, req)
require.True(t, resp)
req.opts.NumGPU = -1
resp = runner.needsReload(ctx, req)
require.False(t, resp)
req.contextShift = true
resp = runner.needsReload(ctx, req)
require.True(t, resp)
}
func TestResolveContextShift(t *testing.T) {
trueValue := true
falseValue := false
tests := []struct {
name string
shift *bool
model *Model
want bool
}{
{name: "unset defaults to shift", want: true},
{name: "unset deepseek2 disables shift", model: &Model{Config: model.ConfigV2{ModelFamily: "deepseek2"}}, want: false},
{name: "unset deepseek2 family disables shift", model: &Model{Config: model.ConfigV2{ModelFamilies: []string{"llama", "deepseek2"}}}, want: false},
{name: "explicit false disables shift", shift: &falseValue, want: false},
{name: "explicit false disables shift for deepseek2", shift: &falseValue, model: &Model{Config: model.ConfigV2{ModelFamily: "deepseek2"}}, want: false},
{name: "explicit true enables shift", shift: &trueValue, want: true},
{name: "explicit true enables shift for deepseek2", shift: &trueValue, model: &Model{Config: model.ConfigV2{ModelFamily: "deepseek2"}}, want: true},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
require.Equal(t, tt.want, resolveContextShift(tt.shift, tt.model))
})
}
}
func TestSchedNeedsReloadIgnoresAutomaticNumCtxClamp(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 100*time.Millisecond)
defer done()
llm := &mockLlm{vramByGPU: map[ml.DeviceID]uint64{}}
opts := api.DefaultOptions()
opts.NumCtx = 131072
model := &Model{}
runner := &runnerRef{
model: model,
Options: &opts,
llama: llm,
numParallel: 1,
numCtxAuto: true,
}
req := &LlmRequest{
model: model,
opts: api.DefaultOptions(),
numCtxAuto: true,
}
req.opts.NumCtx = 262144
require.False(t, runner.needsReload(ctx, req))
req.numCtxAuto = false
require.True(t, runner.needsReload(ctx, req))
}
func TestSchedNeedsReloadUsesEffectiveAutomaticContextShift(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 100*time.Millisecond)
defer done()
llm := &mockLlm{vramByGPU: map[ml.DeviceID]uint64{}}
opts := api.DefaultOptions()
opts.NumCtx = 128
model := &Model{ModelPath: "model.gguf"}
runner := &runnerRef{
model: model,
Options: &opts,
llama: llm,
numParallel: 1,
numCtxAuto: true,
contextShift: true,
}
req := &LlmRequest{
model: model,
opts: api.DefaultOptions(),
numCtxAuto: true,
}
req.opts.NumCtx = 262144
require.False(t, runner.needsReload(ctx, req))
req.numCtxAuto = false
require.True(t, runner.needsReload(ctx, req))
}
func TestSchedNeedsReloadUsesEffectiveExplicitContext(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 100*time.Millisecond)
defer done()
llm := &mockLlm{vramByGPU: map[ml.DeviceID]uint64{}}
opts := api.DefaultOptions()
opts.NumCtx = 2048
model := &Model{ModelPath: "model.gguf"}
runner := &runnerRef{
model: model,
Options: &opts,
llama: llm,
numParallel: 1,
contextShift: true,
trainContext: 2048,
}
req := &LlmRequest{
model: model,
opts: api.DefaultOptions(),
}
req.opts.NumCtx = 262144
require.False(t, runner.needsReload(ctx, req))
req.opts.NumCtx = 1024
require.True(t, runner.needsReload(ctx, req))
}
func TestSchedNeedsReloadIgnoresAutomaticNumBatchDerivation(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 100*time.Millisecond)
defer done()
llm := &mockLlm{vramByGPU: map[ml.DeviceID]uint64{}}
opts := api.DefaultOptions()
opts.NumBatch = 1024
model := &Model{}
runner := &runnerRef{
model: model,
Options: &opts,
llama: llm,
numParallel: 1,
numBatchAuto: true,
}
req := &LlmRequest{
model: model,
opts: api.DefaultOptions(),
numBatchAuto: true,
}
req.opts.NumBatch = 512
require.False(t, runner.needsReload(ctx, req))
req.numBatchAuto = false
require.True(t, runner.needsReload(ctx, req))
}
func TestSchedNeedsReloadIgnoresAutomaticUseMMapDefault(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 100*time.Millisecond)
defer done()
llm := &mockLlm{vramByGPU: map[ml.DeviceID]uint64{}}
useMmap := false
opts := api.DefaultOptions()
opts.UseMMap = &useMmap
model := &Model{}
runner := &runnerRef{
model: model,
Options: &opts,
llama: llm,
numParallel: 1,
useMMapAuto: true,
}
req := &LlmRequest{
model: model,
opts: api.DefaultOptions(),
}
require.False(t, runner.needsReload(ctx, req))
explicitUseMmap := true
req.opts.UseMMap = &explicitUseMmap
require.True(t, runner.needsReload(ctx, req))
req.opts.UseMMap = &useMmap
require.False(t, runner.needsReload(ctx, req))
runner.useMMapAuto = false
req.opts.UseMMap = nil
require.True(t, runner.needsReload(ctx, req))
}
func TestAutomaticGenerationBatch(t *testing.T) {
tests := []struct {
name string
effectiveCtx int
predicted uint64
available uint64
flash ml.FlashAttentionType
gpus []ml.DeviceInfo
want int
}{
{
name: "small context keeps default",
effectiveCtx: 4096,
flash: ml.FlashAttentionAuto,
want: 512,
},
{
name: "medium context uses 1024 with unknown memory",
effectiveCtx: 32768,
flash: ml.FlashAttentionAuto,
want: 1024,
},
{
name: "large context uses 2048 with headroom",
effectiveCtx: 131072,
predicted: 8 * format.GibiByte,
available: 14 * format.GibiByte,
flash: ml.FlashAttentionAuto,
want: 2048,
},
{
name: "large context steps down to 1024 without 2048 headroom",
effectiveCtx: 131072,
predicted: 9 * format.GibiByte,
available: 14 * format.GibiByte,
flash: ml.FlashAttentionAuto,
want: 1024,
},
{
name: "large context steps down to 1024 for headroom",
effectiveCtx: 131072,
predicted: 8 * format.GibiByte,
available: 11 * format.GibiByte,
flash: ml.FlashAttentionAuto,
want: 1024,
},
{
name: "medium context steps down to 512 for headroom",
effectiveCtx: 32768,
predicted: 8500 * format.MebiByte,
available: 11 * format.GibiByte,
flash: ml.FlashAttentionAuto,
want: 512,
},
{
name: "flash attention disabled suppresses promotion",
effectiveCtx: 131072,
predicted: 8 * format.GibiByte,
available: 14 * format.GibiByte,
flash: ml.FlashAttentionDisabled,
gpus: []ml.DeviceInfo{{DeviceID: ml.DeviceID{Library: "CUDA"}, FreeMemory: 14 * format.GibiByte}},
want: 512,
},
{
name: "constrained CUDA without flash attention uses smaller batch",
effectiveCtx: 131072,
predicted: 3 * format.GibiByte,
available: 6 * format.GibiByte,
flash: ml.FlashAttentionDisabled,
gpus: []ml.DeviceInfo{{DeviceID: ml.DeviceID{Library: "CUDA"}, FreeMemory: 6 * format.GibiByte}},
want: 256,
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
require.Equal(t, tt.want, automaticGenerationBatch(tt.effectiveCtx, tt.predicted, tt.available, tt.flash, tt.gpus))
})
}
}
func TestSchedUnloadAllRunners(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 100*time.Millisecond)
defer done()
llm1 := &mockLlm{vramByGPU: map[ml.DeviceID]uint64{}}
llm2 := &mockLlm{vramByGPU: map[ml.DeviceID]uint64{}}
s := InitScheduler(ctx)
s.waitForRecovery = 10 * time.Millisecond
s.unloadAllRunners()
r1 := &runnerRef{llama: llm1, numParallel: 1}
r2 := &runnerRef{llama: llm2, numParallel: 1}
s.loadedMu.Lock()
s.loaded["a"] = r1
s.loaded["b"] = r2
s.loadedMu.Unlock()
s.unloadAllRunners()
require.True(t, llm1.closeCalled)
require.True(t, llm2.closeCalled)
}
func TestSchedUnload(t *testing.T) {
llm1 := &mockLlm{vramByGPU: map[ml.DeviceID]uint64{}}
r1 := &runnerRef{llama: llm1, numParallel: 1}
r2 := &runnerRef{model: &Model{AdapterPaths: []string{"A"}}, numParallel: 1}
r1.unload()
require.True(t, llm1.closeCalled)
r2.unload()
require.Nil(t, r2.model)
}
func TestSchedAlreadyCanceled(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 500*time.Millisecond)
defer done()
dctx, done2 := context.WithCancel(ctx)
done2()
scenario1a := newScenarioRequest(t, dctx, "ollama-model-1", 10, &api.Duration{Duration: 0}, nil)
s := InitScheduler(ctx)
s.waitForRecovery = 10 * time.Millisecond
slog.Info("scenario1a")
s.pendingReqCh <- scenario1a.req
require.Len(t, s.pendingReqCh, 1)
s.Run(ctx)
time.Sleep(5 * time.Millisecond)
require.Empty(t, s.pendingReqCh)
require.Empty(t, scenario1a.req.errCh)
require.Empty(t, scenario1a.req.successCh)
}
// hasLoadedRunner is a test helper that checks if any runner is loaded.
func hasLoadedRunner(s *Scheduler) bool {
s.loadedMu.Lock()
defer s.loadedMu.Unlock()
for _, r := range s.loaded {
if r.llama != nil {
return true
}
}
return false
}
func TestSchedLlamaServerEvictsWhenVRAMInsufficient(t *testing.T) {
// When a llama-server model is predicted to exceed available VRAM,
// the scheduler should signal eviction before spawning
ctx, done := context.WithTimeout(t.Context(), 500*time.Millisecond)
defer done()
s := InitScheduler(ctx)
s.waitForRecovery = 10 * time.Millisecond
// GPU with very little free memory — the model won't fit
s.getGpuFn = func(ctx context.Context, runners []ml.FilteredRunnerDiscovery) []ml.DeviceInfo {
g := ml.DeviceInfo{DeviceID: ml.DeviceID{Library: "Metal"}}
g.TotalMemory = 24 * format.GigaByte
g.FreeMemory = 0 // no free VRAM — forces eviction
return []ml.DeviceInfo{g}
}
s.getSystemInfoFn = getSystemInfoFn
// Pre-load a regular model
s.loadedMu.Lock()
s.loaded["existing-model"] = &runnerRef{
llama: &mockLlm{modelPath: "existing"},
modelKey: "existing-model",
}
s.loadedMu.Unlock()
// Create a request — the model file + KV cache will exceed 100 MiB
scenario := newScenarioRequest(t, ctx, "llama-server-model", 1*format.GigaByte, nil, nil)
s.newServerFn = func(systemInfo ml.SystemInfo, gpus []ml.DeviceInfo, model string, f *ggml.GGML, adapters []string, projectors []string, opts api.Options, numParallel int, _ llm.LlamaServerConfig) (llm.LlamaServer, error) {
return &mockLlm{modelPath: model}, nil
}
systemInfo := getSystemInfoFn()
gpus := s.getGpuFn(ctx, nil)
needEvict := s.load(scenario.req, systemInfo, gpus, true)
require.True(t, needEvict, "expected eviction when predicted VRAM exceeds free memory")
}
func TestSchedLlamaServerExplicitPartialNumGPUSkipsFullFitEviction(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 500*time.Millisecond)
defer done()
s := InitScheduler(ctx)
s.waitForRecovery = 10 * time.Millisecond
s.getGpuFn = func(ctx context.Context, runners []ml.FilteredRunnerDiscovery) []ml.DeviceInfo {
g := ml.DeviceInfo{DeviceID: ml.DeviceID{Library: "Metal"}}
g.TotalMemory = 24 * format.GigaByte
g.FreeMemory = 0
return []ml.DeviceInfo{g}
}
s.getSystemInfoFn = getSystemInfoFn
s.loadedMu.Lock()
s.loaded["existing-model"] = &runnerRef{
llama: &mockLlm{modelPath: "existing"},
modelKey: "existing-model",
}
s.loadedMu.Unlock()
scenario := newScenarioRequest(t, ctx, "partial-llama-server-model", 1*format.GigaByte, nil, nil)
scenario.req.opts.NumGPU = 1
scenario.srv.vramSize = 0
called := false
s.newServerFn = func(systemInfo ml.SystemInfo, gpus []ml.DeviceInfo, model string, f *ggml.GGML, adapters []string, projectors []string, opts api.Options, numParallel int, _ llm.LlamaServerConfig) (llm.LlamaServer, error) {
called = true
require.Equal(t, 1, opts.NumGPU)
return scenario.srv, nil
}
systemInfo := getSystemInfoFn()
gpus := s.getGpuFn(ctx, nil)
needEvict := s.load(scenario.req, systemInfo, gpus, true)
require.False(t, needEvict, "explicit partial offload should not trigger full-fit eviction")
require.True(t, called, "scheduler should try the explicitly partial load")
}
func TestSchedLlamaServerFitsAlongside(t *testing.T) {
// When a llama-server model is predicted to fit in remaining VRAM,
// it should load without evicting existing models
ctx, done := context.WithTimeout(t.Context(), 500*time.Millisecond)
defer done()
s := InitScheduler(ctx)
s.waitForRecovery = 10 * time.Millisecond
// GPU with plenty of free memory
s.getGpuFn = func(ctx context.Context, runners []ml.FilteredRunnerDiscovery) []ml.DeviceInfo {
g := ml.DeviceInfo{DeviceID: ml.DeviceID{Library: "Metal"}}
g.TotalMemory = 24 * format.GigaByte
g.FreeMemory = 20 * format.GigaByte
return []ml.DeviceInfo{g}
}
s.getSystemInfoFn = getSystemInfoFn
// Pre-load a regular model
s.loadedMu.Lock()
s.loaded["existing-model"] = &runnerRef{
llama: &mockLlm{modelPath: "existing"},
modelKey: "existing-model",
}
s.loadedMu.Unlock()
// The test model GGUF is tiny (~64 bytes) — should easily fit in 20 GiB
scenario := newScenarioRequest(t, ctx, "small-llama-server", 1*format.GigaByte, nil, nil)
s.newServerFn = scenario.newServer
systemInfo := getSystemInfoFn()
gpus := s.getGpuFn(ctx, nil)
// Should NOT evict — model fits alongside existing
needEvict := s.load(scenario.req, systemInfo, gpus, true)
require.False(t, needEvict, "expected no eviction when model fits in available VRAM")
}
func TestSchedLlamaServerPredictionUsesTotalParallelContext(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 500*time.Millisecond)
defer done()
t.Setenv("OLLAMA_NUM_PARALLEL", "2")
s := InitScheduler(ctx)
s.waitForRecovery = 10 * time.Millisecond
s.getGpuFn = func(ctx context.Context, runners []ml.FilteredRunnerDiscovery) []ml.DeviceInfo {
g := ml.DeviceInfo{DeviceID: ml.DeviceID{Library: "Metal"}}
g.TotalMemory = 24 * format.GigaByte
g.FreeMemory = 900 * format.MebiByte
return []ml.DeviceInfo{g}
}
s.getSystemInfoFn = getSystemInfoFn
s.loadedMu.Lock()
s.loaded["existing-model"] = &runnerRef{
llama: &mockLlm{modelPath: "existing"},
modelKey: "existing-model",
}
s.loadedMu.Unlock()
scenario := newScenarioRequestWithContext(t, ctx, "parallel-context-model", 1*format.GigaByte, nil, nil, 65536)
scenario.req.opts.NumCtx = 32768
called := false
s.newServerFn = func(systemInfo ml.SystemInfo, gpus []ml.DeviceInfo, model string, f *ggml.GGML, adapters []string, projectors []string, opts api.Options, numParallel int, _ llm.LlamaServerConfig) (llm.LlamaServer, error) {
called = true
return scenario.srv, nil
}
systemInfo := getSystemInfoFn()
gpus := s.getGpuFn(ctx, nil)
needEvict := s.load(scenario.req, systemInfo, gpus, true)
require.True(t, needEvict, "expected eviction when total parallel context exceeds available memory")
require.False(t, called, "preflight prediction should reject before spawning llama-server")
}
func TestAvailableMemoryForLoadUsesWorstSharedMemoryMeasurement(t *testing.T) {
tests := []struct {
name string
systemFree uint64
gpus []ml.DeviceInfo
wantAvailable uint64
wantGPUFree uint64
wantSystemLimited bool
}{
{
name: "integrated metal uses lower system free",
systemFree: 80 * format.GigaByte,
gpus: []ml.DeviceInfo{{
DeviceID: ml.DeviceID{Library: "Metal"},
Integrated: true,
FreeMemory: 300 * format.GigaByte,
}},
wantAvailable: 80 * format.GigaByte,
wantGPUFree: 300 * format.GigaByte,
wantSystemLimited: true,
},
{
name: "integrated gpu uses lower system free",
systemFree: 6 * format.GigaByte,
gpus: []ml.DeviceInfo{{
DeviceID: ml.DeviceID{Library: "Vulkan"},
Integrated: true,
FreeMemory: 12 * format.GigaByte,
}},
wantAvailable: 6 * format.GigaByte,
wantGPUFree: 12 * format.GigaByte,
wantSystemLimited: true,
},
{
name: "discrete metal ignores lower system free",
systemFree: 6 * format.GigaByte,
gpus: []ml.DeviceInfo{{
DeviceID: ml.DeviceID{Library: "Metal"},
FreeMemory: 12 * format.GigaByte,
}},
wantAvailable: 12 * format.GigaByte,
wantGPUFree: 12 * format.GigaByte,
},
{
name: "discrete gpu ignores lower system free",
systemFree: 6 * format.GigaByte,
gpus: []ml.DeviceInfo{{
DeviceID: ml.DeviceID{Library: "CUDA"},
FreeMemory: 12 * format.GigaByte,
}},
wantAvailable: 12 * format.GigaByte,
wantGPUFree: 12 * format.GigaByte,
},
{
name: "mixed gpus only clamp integrated contribution",
systemFree: 6 * format.GigaByte,
gpus: []ml.DeviceInfo{
{
DeviceID: ml.DeviceID{Library: "CUDA"},
FreeMemory: 12 * format.GigaByte,
},
{
DeviceID: ml.DeviceID{Library: "Vulkan"},
Integrated: true,
FreeMemory: 10 * format.GigaByte,
},
},
wantAvailable: 18 * format.GigaByte,
wantGPUFree: 22 * format.GigaByte,
wantSystemLimited: true,
},
{
name: "shared gpu keeps lower adjusted gpu baseline",
systemFree: 20 * format.GigaByte,
gpus: []ml.DeviceInfo{{
DeviceID: ml.DeviceID{Library: "Metal"},
Integrated: true,
FreeMemory: 12 * format.GigaByte,
}},
wantAvailable: 12 * format.GigaByte,
wantGPUFree: 12 * format.GigaByte,
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
available, gpuFree, systemLimited := availableMemoryForLoad(ml.SystemInfo{FreeMemory: tt.systemFree}, tt.gpus)
require.Equal(t, tt.wantAvailable, available)
require.Equal(t, tt.wantGPUFree, gpuFree)
require.Equal(t, tt.wantSystemLimited, systemLimited)
})
}
}
func TestSelectLlamaServerPlacement(t *testing.T) {
systemInfo := ml.SystemInfo{FreeMemory: 14 * format.GigaByte}
tests := []struct {
name string
gpus []ml.DeviceInfo
predictedVRAM uint64
opts api.Options
schedSpread string
wantLibrary string
wantMainGPU *int
wantSelectedGPUs int
wantGPUID string
}{
{
name: "compacts onto largest same-backend GPU",
predictedVRAM: 8 * format.GigaByte,
gpus: []ml.DeviceInfo{
{DeviceID: ml.DeviceID{ID: "0", Library: "CUDA"}, Name: "small", FreeMemory: 10 * format.GigaByte},
{DeviceID: ml.DeviceID{ID: "1", Library: "CUDA"}, Name: "large", FreeMemory: 20 * format.GigaByte},
},
opts: api.DefaultOptions(),
wantLibrary: "CUDA",
wantMainGPU: testIntPtr(0),
wantSelectedGPUs: 1,
wantGPUID: "1",
},
{
name: "explicit main gpu selects matching backend group",
predictedVRAM: 8 * format.GigaByte,
gpus: []ml.DeviceInfo{
{DeviceID: ml.DeviceID{ID: "0", Library: "CUDA"}, FreeMemory: 10 * format.GigaByte},
{DeviceID: ml.DeviceID{ID: "0", Library: "ROCm"}, FreeMemory: 20 * format.GigaByte},
{DeviceID: ml.DeviceID{ID: "1", Library: "ROCm"}, FreeMemory: 24 * format.GigaByte},
},
opts: api.Options{
Runner: api.Runner{MainGPU: testIntPtr(1), NumGPU: -1},
},
wantLibrary: "ROCm",
wantMainGPU: testIntPtr(0),
wantSelectedGPUs: 1,
wantGPUID: "1",
},
{
name: "integrated GPU is capped by system free memory",
predictedVRAM: 12 * format.GigaByte,
gpus: []ml.DeviceInfo{
{DeviceID: ml.DeviceID{ID: "0", Library: "Metal"}, Integrated: true, FreeMemory: 32 * format.GigaByte},
{DeviceID: ml.DeviceID{ID: "1", Library: "Metal"}, FreeMemory: 16 * format.GigaByte},
},
opts: api.DefaultOptions(),
wantLibrary: "Metal",
wantMainGPU: testIntPtr(0),
wantSelectedGPUs: 1,
wantGPUID: "1",
},
{
name: "prefers discrete GPU over integrated GPU with more available memory",
predictedVRAM: 8 * format.GigaByte,
gpus: []ml.DeviceInfo{
{DeviceID: ml.DeviceID{ID: "0", Library: "Vulkan"}, Name: "integrated", Integrated: true, FreeMemory: 32 * format.GigaByte},
{DeviceID: ml.DeviceID{ID: "1", Library: "Vulkan"}, Name: "discrete", FreeMemory: 10 * format.GigaByte},
},
opts: api.DefaultOptions(),
wantLibrary: "Vulkan",
wantMainGPU: testIntPtr(0),
wantSelectedGPUs: 1,
wantGPUID: "1",
},
{
name: "spread disables automatic compaction",
predictedVRAM: 8 * format.GigaByte,
schedSpread: "1",
gpus: []ml.DeviceInfo{
{DeviceID: ml.DeviceID{ID: "0", Library: "CUDA"}, FreeMemory: 10 * format.GigaByte},
{DeviceID: ml.DeviceID{ID: "1", Library: "CUDA"}, FreeMemory: 20 * format.GigaByte},
},
opts: api.DefaultOptions(),
wantLibrary: "CUDA",
wantSelectedGPUs: 2,
},
{
name: "no single fit chooses best backend group for llama-server split",
predictedVRAM: 30 * format.GigaByte,
gpus: []ml.DeviceInfo{
{DeviceID: ml.DeviceID{ID: "0", Library: "CUDA"}, FreeMemory: 10 * format.GigaByte},
{DeviceID: ml.DeviceID{ID: "1", Library: "CUDA"}, FreeMemory: 18 * format.GigaByte},
{DeviceID: ml.DeviceID{ID: "0", Library: "ROCm"}, FreeMemory: 12 * format.GigaByte},
},
opts: api.DefaultOptions(),
wantLibrary: "CUDA",
wantSelectedGPUs: 2,
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
t.Setenv("OLLAMA_SCHED_SPREAD", tt.schedSpread)
selected, launchOpts := selectLlamaServerPlacement(systemInfo, tt.gpus, tt.predictedVRAM, tt.opts)
require.Len(t, selected, tt.wantSelectedGPUs)
require.Equal(t, tt.wantLibrary, selected[0].Library)
if tt.wantGPUID != "" {
require.Equal(t, tt.wantGPUID, selected[0].ID)
}
if tt.wantMainGPU == nil {
require.Nil(t, launchOpts.MainGPU)
} else {
require.NotNil(t, launchOpts.MainGPU)
require.Equal(t, *tt.wantMainGPU, *launchOpts.MainGPU)
}
})
}
}
func testIntPtr(v int) *int {
return &v
}
func TestDisableMmapDefaultReason(t *testing.T) {
useMmap := true
tests := []struct {
name string
goos string
opts api.Options
gpus []ml.DeviceInfo
blockCount uint64
predictedVRAM uint64
availableVRAM uint64
want string
}{
{
name: "explicit use_mmap true wins",
goos: "windows",
opts: api.Options{Runner: api.Runner{NumGPU: -1, UseMMap: &useMmap}},
gpus: []ml.DeviceInfo{{DeviceID: ml.DeviceID{Library: "CUDA"}}},
},
{
name: "cpu-only request disables mmap",
goos: "linux",
opts: api.Options{Runner: api.Runner{NumGPU: 0}},
gpus: []ml.DeviceInfo{{DeviceID: ml.DeviceID{Library: "CUDA"}}},
want: "cpu",
},
{
name: "no GPU devices disables mmap",
goos: "linux",
opts: api.Options{Runner: api.Runner{NumGPU: -1}},
want: "cpu",
},
{
name: "windows cuda disables mmap",
goos: "windows",
opts: api.Options{Runner: api.Runner{NumGPU: -1}},
gpus: []ml.DeviceInfo{{DeviceID: ml.DeviceID{Library: "CUDA"}}},
want: "windows_cuda",
},
{
name: "metal partial offload disables mmap",
goos: "darwin",
opts: api.Options{Runner: api.Runner{NumGPU: 10}},
gpus: []ml.DeviceInfo{{DeviceID: ml.DeviceID{Library: "Metal"}}},
blockCount: 20,
want: "metal_partial_offload",
},
{
name: "metal full offload keeps default",
goos: "darwin",
opts: api.Options{Runner: api.Runner{NumGPU: 21}},
gpus: []ml.DeviceInfo{{DeviceID: ml.DeviceID{Library: "Metal"}}},
blockCount: 20,
},
{
name: "metal auto partial offload disables mmap",
goos: "darwin",
opts: api.Options{Runner: api.Runner{NumGPU: -1}},
gpus: []ml.DeviceInfo{{DeviceID: ml.DeviceID{Library: "Metal"}}},
predictedVRAM: 30 * format.GigaByte,
availableVRAM: 20 * format.GigaByte,
want: "metal_partial_offload",
},
{
name: "metal auto full offload keeps default",
goos: "darwin",
opts: api.Options{Runner: api.Runner{NumGPU: -1}},
gpus: []ml.DeviceInfo{{DeviceID: ml.DeviceID{Library: "Metal"}}},
predictedVRAM: 10 * format.GigaByte,
availableVRAM: 20 * format.GigaByte,
},
{
name: "linux cuda keeps default",
goos: "linux",
opts: api.Options{Runner: api.Runner{NumGPU: -1}},
gpus: []ml.DeviceInfo{{DeviceID: ml.DeviceID{Library: "CUDA"}}},
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
require.Equal(t, tt.want, disableMmapDefaultReason(tt.goos, tt.opts, tt.gpus, tt.blockCount, tt.predictedVRAM, tt.availableVRAM))
})
}
}
func TestDisableMmapForHostPressure(t *testing.T) {
gpus := []ml.DeviceInfo{{
DeviceID: ml.DeviceID{Library: "CUDA"},
TotalMemory: 100 * format.GigaByte,
FreeMemory: 80 * format.GigaByte,
}}
systemInfo := ml.SystemInfo{
TotalMemory: 100 * format.GigaByte,
FreeMemory: 50 * format.GigaByte,
}
require.True(t, disableMmapForHostPressure(
"linux",
api.Options{},
systemInfo,
gpus,
20*format.GigaByte,
25*format.GigaByte,
30*format.GigaByte,
80*format.GigaByte,
))
useMmap := true
require.False(t, disableMmapForHostPressure(
"linux",
api.Options{Runner: api.Runner{UseMMap: &useMmap}},
systemInfo,
gpus,
20*format.GigaByte,
25*format.GigaByte,
30*format.GigaByte,
80*format.GigaByte,
), "explicit use_mmap=true should win")
require.False(t, disableMmapForHostPressure(
"darwin",
api.Options{},
systemInfo,
gpus,
20*format.GigaByte,
25*format.GigaByte,
30*format.GigaByte,
80*format.GigaByte,
), "only the Linux pressure heuristic is restored")
igpu := append([]ml.DeviceInfo(nil), gpus...)
igpu[0].Integrated = true
require.False(t, disableMmapForHostPressure(
"linux",
api.Options{},
systemInfo,
igpu,
20*format.GigaByte,
25*format.GigaByte,
30*format.GigaByte,
80*format.GigaByte,
), "shared-memory GPU loads should keep the normal mmap path")
require.False(t, disableMmapForHostPressure(
"linux",
api.Options{},
systemInfo,
gpus,
20*format.GigaByte,
25*format.GigaByte,
70*format.GigaByte,
80*format.GigaByte,
), "when VRAM is tight, no-mmap could make partial CPU offload worse")
}
// TestSchedLoadCrashTriggersEvictAllAndRetry verifies that a post-spawn
// Load() OOM while other models are resident signals evict-all-and-retry
// on the first attempt, but fails fast on the second attempt.
func TestSchedLoadCrashTriggersEvictAllAndRetry(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 500*time.Millisecond)
defer done()
s := InitScheduler(ctx)
s.waitForRecovery = 10 * time.Millisecond
s.getGpuFn = func(ctx context.Context, runners []ml.FilteredRunnerDiscovery) []ml.DeviceInfo {
g := ml.DeviceInfo{DeviceID: ml.DeviceID{Library: "Metal"}}
g.TotalMemory = 24 * format.GigaByte
g.FreeMemory = 20 * format.GigaByte
return []ml.DeviceInfo{g}
}
s.getSystemInfoFn = getSystemInfoFn
// Pre-load a different model so evict-all has something to evict.
s.loadedMu.Lock()
s.loaded["existing-model"] = &runnerRef{
llama: &mockLlm{modelPath: "/fake/existing"},
modelKey: "existing-model",
}
s.loadedMu.Unlock()
// newServerFn returns a mockLlm that crashes in Load()
loadCrash := errors.New("cudaMalloc failed: out of memory")
s.newServerFn = func(systemInfo ml.SystemInfo, gpus []ml.DeviceInfo, model string, f *ggml.GGML, adapters []string, projectors []string, opts api.Options, numParallel int, _ llm.LlamaServerConfig) (llm.LlamaServer, error) {
return &mockLlm{modelPath: model, loadErr: loadCrash}, nil
}
scenario := newScenarioRequest(t, ctx, "crashing-model", 1*format.GigaByte, nil, nil)
systemInfo := getSystemInfoFn()
gpus := s.getGpuFn(ctx, nil)
// First attempt: should signal evict-all by returning true and NOT send
// the error to errCh (so the caller will retry).
needEvict := s.load(scenario.req, systemInfo, gpus, true)
require.True(t, needEvict, "first load OOM should signal eviction")
require.True(t, scenario.req.oomRetryAttempted, "oomRetryAttempted should be set")
select {
case err := <-scenario.req.errCh:
t.Fatalf("errCh should be empty on first crash, got %v", err)
default:
}
// Second attempt (simulating the retry after processPending evicted all
// other runners): same crash, but this time oomRetryAttempted is set so
// load() should fail fast and report the error.
needEvict = s.load(scenario.req, systemInfo, gpus, true)
require.False(t, needEvict, "second load OOM should not ask for another eviction")
select {
case err := <-scenario.req.errCh:
require.ErrorIs(t, err, loadCrash)
case <-time.After(100 * time.Millisecond):
t.Fatal("expected error on errCh after second crash")
}
}
func TestSchedLoadOOMReducesAutomaticContextBeforeRetry(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 500*time.Millisecond)
defer done()
s := InitScheduler(ctx)
s.waitForRecovery = 10 * time.Millisecond
s.getGpuFn = func(ctx context.Context, runners []ml.FilteredRunnerDiscovery) []ml.DeviceInfo {
g := ml.DeviceInfo{DeviceID: ml.DeviceID{Library: "Metal"}}
g.TotalMemory = 24 * format.GigaByte
g.FreeMemory = 20 * format.GigaByte
return []ml.DeviceInfo{g}
}
s.getSystemInfoFn = getSystemInfoFn
s.loadedMu.Lock()
s.loaded["existing-model"] = &runnerRef{
llama: &mockLlm{modelPath: "/fake/existing"},
modelKey: "existing-model",
}
s.loadedMu.Unlock()
loadCrash := errors.New("cudaMalloc failed: out of memory")
var seenNumCtx []int
var seenNumBatch []int
s.newServerFn = func(systemInfo ml.SystemInfo, gpus []ml.DeviceInfo, model string, f *ggml.GGML, adapters []string, projectors []string, opts api.Options, numParallel int, _ llm.LlamaServerConfig) (llm.LlamaServer, error) {
seenNumCtx = append(seenNumCtx, opts.NumCtx)
seenNumBatch = append(seenNumBatch, opts.NumBatch)
return &mockLlm{modelPath: model, loadErr: loadCrash}, nil
}
scenario := newScenarioRequestWithContext(t, ctx, "crashing-model", 1*format.GigaByte, nil, nil, 131072)
scenario.req.opts.NumCtx = 262144
scenario.req.numCtxAuto = true
scenario.req.numBatchAuto = true
systemInfo := getSystemInfoFn()
gpus := s.getGpuFn(ctx, nil)
needEvict := s.load(scenario.req, systemInfo, gpus, true)
require.True(t, needEvict, "first automatic-context load OOM should signal eviction and retry")
require.True(t, scenario.req.oomRetryAttempted)
require.Equal(t, 32768, scenario.req.opts.NumCtx)
require.Equal(t, 1024, scenario.req.opts.NumBatch)
select {
case err := <-scenario.req.errCh:
t.Fatalf("errCh should be empty on first crash, got %v", err)
default:
}
needEvict = s.load(scenario.req, systemInfo, gpus, true)
require.False(t, needEvict, "second load OOM should not ask for another eviction")
require.Equal(t, []int{262144, 32768}, seenNumCtx)
require.Equal(t, []int{2048, 1024}, seenNumBatch)
select {
case err := <-scenario.req.errCh:
require.ErrorIs(t, err, loadCrash)
case <-time.After(100 * time.Millisecond):
t.Fatal("expected error on errCh after second crash")
}
}
func TestSchedLoadOOMKeepsExplicitContextBeforeRetry(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 500*time.Millisecond)
defer done()
s := InitScheduler(ctx)
s.waitForRecovery = 10 * time.Millisecond
s.getGpuFn = func(ctx context.Context, runners []ml.FilteredRunnerDiscovery) []ml.DeviceInfo {
g := ml.DeviceInfo{DeviceID: ml.DeviceID{Library: "Metal"}}
g.TotalMemory = 24 * format.GigaByte
g.FreeMemory = 20 * format.GigaByte
return []ml.DeviceInfo{g}
}
s.getSystemInfoFn = getSystemInfoFn
s.loadedMu.Lock()
s.loaded["existing-model"] = &runnerRef{
llama: &mockLlm{modelPath: "/fake/existing"},
modelKey: "existing-model",
}
s.loadedMu.Unlock()
loadCrash := errors.New("cudaMalloc failed: out of memory")
s.newServerFn = func(systemInfo ml.SystemInfo, gpus []ml.DeviceInfo, model string, f *ggml.GGML, adapters []string, projectors []string, opts api.Options, numParallel int, _ llm.LlamaServerConfig) (llm.LlamaServer, error) {
return &mockLlm{modelPath: model, loadErr: loadCrash}, nil
}
scenario := newScenarioRequestWithContext(t, ctx, "crashing-model", 1*format.GigaByte, nil, nil, 131072)
scenario.req.opts.NumCtx = 262144
scenario.req.numCtxAuto = false
systemInfo := getSystemInfoFn()
gpus := s.getGpuFn(ctx, nil)
needEvict := s.load(scenario.req, systemInfo, gpus, true)
require.True(t, needEvict, "explicit-context load OOM should still evict and retry once")
require.True(t, scenario.req.oomRetryAttempted)
require.Equal(t, 262144, scenario.req.opts.NumCtx)
select {
case err := <-scenario.req.errCh:
t.Fatalf("errCh should be empty on first crash, got %v", err)
default:
}
}
func TestSchedFirstLoadOOMReducesAutomaticContextAndRetries(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), time.Second)
defer done()
s := InitScheduler(ctx)
s.waitForRecovery = 10 * time.Millisecond
s.getGpuFn = func(ctx context.Context, runners []ml.FilteredRunnerDiscovery) []ml.DeviceInfo {
g := ml.DeviceInfo{DeviceID: ml.DeviceID{Library: "Metal"}}
g.TotalMemory = 24 * format.GigaByte
g.FreeMemory = 20 * format.GigaByte
return []ml.DeviceInfo{g}
}
s.getSystemInfoFn = getSystemInfoFn
loadCrash := errors.New("cudaMalloc failed: out of memory")
var seenNumCtx []int
s.newServerFn = func(systemInfo ml.SystemInfo, gpus []ml.DeviceInfo, model string, f *ggml.GGML, adapters []string, projectors []string, opts api.Options, numParallel int, _ llm.LlamaServerConfig) (llm.LlamaServer, error) {
seenNumCtx = append(seenNumCtx, opts.NumCtx)
if len(seenNumCtx) == 1 {
return &mockLlm{modelPath: model, loadErr: loadCrash}, nil
}
return &mockLlm{modelPath: model, vramSize: 1 * format.GigaByte, contextLength: opts.NumCtx}, nil
}
scenario := newScenarioRequestWithContext(t, ctx, "first-load-crashing-model", 1*format.GigaByte, nil, nil, 131072)
scenario.req.opts.NumCtx = 262144
scenario.req.numCtxAuto = true
s.pendingReqCh <- scenario.req
s.Run(ctx)
select {
case runner := <-scenario.req.successCh:
require.Equal(t, 32768, runner.Options.NumCtx)
require.Equal(t, []int{262144, 32768}, seenNumCtx)
case err := <-scenario.req.errCh:
t.Fatalf("expected retry success, got error %v", err)
case <-ctx.Done():
t.Fatal("timed out waiting for first-load retry")
}
}
// TestSchedLoadCrashNoOtherModelsFailsFast verifies that a Load() crash with
// no other resident models reports the error immediately (no retry).
func TestSchedLoadCrashNoOtherModelsFailsFast(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 500*time.Millisecond)
defer done()
s := InitScheduler(ctx)
s.waitForRecovery = 10 * time.Millisecond
s.getGpuFn = func(ctx context.Context, runners []ml.FilteredRunnerDiscovery) []ml.DeviceInfo {
g := ml.DeviceInfo{DeviceID: ml.DeviceID{Library: "Metal"}}
g.TotalMemory = 24 * format.GigaByte
g.FreeMemory = 20 * format.GigaByte
return []ml.DeviceInfo{g}
}
s.getSystemInfoFn = getSystemInfoFn
loadCrash := errors.New("simulated llama-server OOM crash")
s.newServerFn = func(systemInfo ml.SystemInfo, gpus []ml.DeviceInfo, model string, f *ggml.GGML, adapters []string, projectors []string, opts api.Options, numParallel int, _ llm.LlamaServerConfig) (llm.LlamaServer, error) {
return &mockLlm{modelPath: model, loadErr: loadCrash}, nil
}
scenario := newScenarioRequest(t, ctx, "crashing-model", 1*format.GigaByte, nil, nil)
systemInfo := getSystemInfoFn()
gpus := s.getGpuFn(ctx, nil)
needEvict := s.load(scenario.req, systemInfo, gpus, true)
require.False(t, needEvict, "crash with no other runners should not ask for eviction")
require.False(t, scenario.req.oomRetryAttempted, "oomRetryAttempted must stay false")
select {
case err := <-scenario.req.errCh:
require.ErrorIs(t, err, loadCrash)
case <-time.After(100 * time.Millisecond):
t.Fatal("expected error on errCh immediately")
}
}
func TestSchedLoadNonOOMWithOtherModelsFailsFast(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 500*time.Millisecond)
defer done()
s := InitScheduler(ctx)
s.waitForRecovery = 10 * time.Millisecond
s.getGpuFn = func(ctx context.Context, runners []ml.FilteredRunnerDiscovery) []ml.DeviceInfo {
g := ml.DeviceInfo{DeviceID: ml.DeviceID{Library: "Metal"}}
g.TotalMemory = 24 * format.GigaByte
g.FreeMemory = 20 * format.GigaByte
return []ml.DeviceInfo{g}
}
s.getSystemInfoFn = getSystemInfoFn
s.loadedMu.Lock()
s.loaded["existing-model"] = &runnerRef{
llama: &mockLlm{modelPath: "/fake/existing"},
modelKey: "existing-model",
}
s.loadedMu.Unlock()
loadCrash := errors.New("server parse failed")
s.newServerFn = func(systemInfo ml.SystemInfo, gpus []ml.DeviceInfo, model string, f *ggml.GGML, adapters []string, projectors []string, opts api.Options, numParallel int, _ llm.LlamaServerConfig) (llm.LlamaServer, error) {
return &mockLlm{modelPath: model, loadErr: loadCrash}, nil
}
scenario := newScenarioRequest(t, ctx, "crashing-model", 1*format.GigaByte, nil, nil)
systemInfo := getSystemInfoFn()
gpus := s.getGpuFn(ctx, nil)
needEvict := s.load(scenario.req, systemInfo, gpus, true)
require.False(t, needEvict, "non-OOM load crash should not ask for eviction")
require.False(t, scenario.req.oomRetryAttempted, "oomRetryAttempted must stay false")
select {
case err := <-scenario.req.errCh:
require.ErrorIs(t, err, loadCrash)
case <-time.After(100 * time.Millisecond):
t.Fatal("expected error on errCh immediately")
}
}
func TestSchedRuntimeOOMExpiresLoadedRunners(t *testing.T) {
ctx, done := context.WithCancel(t.Context())
defer done()
s := InitScheduler(ctx)
currentModel := &Model{ModelPath: "/tmp/current.gguf"}
current := &runnerRef{
model: currentModel,
modelKey: schedulerModelKey(currentModel),
sessionDuration: time.Hour,
llama: &mockLlm{modelPath: "/tmp/current.gguf"},
}
otherModel := &Model{ModelPath: "/tmp/other.gguf"}
other := &runnerRef{
model: otherModel,
modelKey: schedulerModelKey(otherModel),
sessionDuration: time.Hour,
llama: &mockLlm{modelPath: "/tmp/other.gguf"},
}
s.loadedMu.Lock()
s.loaded[current.modelKey] = current
s.loaded[other.modelKey] = other
s.loadedMu.Unlock()
s.expireRunnersForRuntimeOOM(currentModel, errors.New("cudaMalloc failed: out of memory"))
require.Equal(t, time.Duration(0), current.sessionDuration)
require.Equal(t, time.Duration(0), other.sessionDuration)
require.Len(t, s.expiredCh, 2)
}
func TestSchedLlamaServerEvictsExistingOnPending(t *testing.T) {
// When a llama-server runner is already loaded and a new model is requested,
// the scheduler should evict the llama-server runner
ctx, done := context.WithCancel(t.Context())
defer done()
s := InitScheduler(ctx)
// Load a llama-server runner
s.loadedMu.Lock()
s.loaded["llama-model"] = &runnerRef{
llama: &mockLlm{modelPath: "/tmp/model.gguf"},
modelKey: "llama-model",
}
s.loadedMu.Unlock()
require.True(t, hasLoadedRunner(s))
// The findRunnerToUnload should find and return the llama-server runner
runner := s.findRunnerToUnload()
require.NotNil(t, runner)
}
type mockLlm struct {
modelPath string
pingResp error
waitResp error
completionResp error
embeddingResp []float32
embeddingRespErr error
tokenizeResp []int
tokenizeRespErr error
detokenizeResp string
detonekizeRespErr error
closeResp error
closeCalled bool
vramSize uint64
totalSize uint64
contextLength int
vramByGPU map[ml.DeviceID]uint64
// loadErr, if non-nil, is returned from Load() to simulate a post-spawn
// load failure (e.g. llama-server crashing due to under-predicted VRAM).
loadErr error
}
func (s *mockLlm) ModelPath() string {
return s.modelPath
}
func (s *mockLlm) Load(ctx context.Context, sytemInfo ml.SystemInfo, gpus []ml.DeviceInfo, requireFull bool) ([]ml.DeviceID, error) {
if s.loadErr != nil {
return nil, s.loadErr
}
if requireFull {
if len(gpus) == 0 {
slog.Info("mockLlm.Load CPU based load")
return nil, nil
}
for _, g := range gpus {
if g.FreeMemory >= s.vramSize {
return []ml.DeviceID{g.DeviceID}, nil
}
}
return nil, llm.ErrLoadRequiredFull
}
gpuIDs := make([]ml.DeviceID, len(gpus))
for i := range gpus {
gpuIDs[i] = gpus[i].DeviceID
}
return gpuIDs, nil
}
func (s *mockLlm) Ping(ctx context.Context) error { return s.pingResp }
func (s *mockLlm) WaitUntilRunning(ctx context.Context) error { return s.waitResp }
func (s *mockLlm) Completion(ctx context.Context, req llm.CompletionRequest, fn func(llm.CompletionResponse)) error {
return s.completionResp
}
func (s *mockLlm) Chat(ctx context.Context, req llm.ChatRequest, fn func(llm.ChatResponse)) error {
return errors.New("not implemented")
}
func (s *mockLlm) ApplyChatTemplate(ctx context.Context, req llm.ChatRequest) (string, error) {
return "", errors.New("not implemented")
}
func (s *mockLlm) Embedding(ctx context.Context, input string) ([]float32, int, error) {
return s.embeddingResp, 0, s.embeddingRespErr
}
func (s *mockLlm) Tokenize(ctx context.Context, content string) ([]int, error) {
return s.tokenizeResp, s.tokenizeRespErr
}
func (s *mockLlm) Detokenize(ctx context.Context, tokens []int) (string, error) {
return s.detokenizeResp, s.detonekizeRespErr
}
func (s *mockLlm) Close() error {
s.closeCalled = true
return s.closeResp
}
func (s *mockLlm) MemorySize() (uint64, uint64) { return s.totalSize, s.vramSize }
func (s *mockLlm) VRAMByGPU(id ml.DeviceID) uint64 { return s.vramByGPU[id] }
func (s *mockLlm) Pid() int { return -1 }
func (s *mockLlm) GetPort() int { return -1 }
func (s *mockLlm) GetDeviceInfos(ctx context.Context) []ml.DeviceInfo { return nil }
func (s *mockLlm) HasExited() bool { return false }
func (s *mockLlm) GetActiveDeviceIDs() []ml.DeviceID { return nil }
func (s *mockLlm) ContextLength() int { return s.contextLength }
// TestImageGenRunnerCanBeEvicted verifies that an image generation model
// loaded in the scheduler can be evicted when idle.
func TestImageGenRunnerCanBeEvicted(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 500*time.Millisecond)
defer done()
s := InitScheduler(ctx)
s.getGpuFn = getGpuFn
s.getSystemInfoFn = getSystemInfoFn
// Simulate an image gen runner already loaded
imageGenRunner := &runnerRef{
model: &Model{Name: "z-image", ModelPath: "/fake/image/model"},
modelPath: "/fake/image/model",
llama: &mockLlm{vramSize: 21 * format.GigaByte, vramByGPU: map[ml.DeviceID]uint64{}},
sessionDuration: 5 * time.Millisecond,
refCount: 0, // idle
}
s.loadedMu.Lock()
s.loaded["/fake/image/model"] = imageGenRunner
s.loadedMu.Unlock()
// Verify the image gen runner is loaded
s.loadedMu.Lock()
require.Len(t, s.loaded, 1)
s.loadedMu.Unlock()
// findRunnerToUnload should find the idle image gen runner
runner := s.findRunnerToUnload()
require.NotNil(t, runner)
require.Equal(t, "/fake/image/model", runner.modelPath)
}
// TestImageGenSchedulerCoexistence verifies that image generation models
// can coexist with language models in the scheduler and VRAM is tracked correctly.
func TestImageGenSchedulerCoexistence(t *testing.T) {
ctx, done := context.WithTimeout(t.Context(), 500*time.Millisecond)
defer done()
s := InitScheduler(ctx)
s.getGpuFn = getGpuFn
s.getSystemInfoFn = getSystemInfoFn
// Load both an imagegen runner and a language model runner
imageGenRunner := &runnerRef{
model: &Model{Name: "flux", ModelPath: "/fake/flux/model"},
modelPath: "/fake/flux/model",
llama: &mockLlm{vramSize: 8 * format.GigaByte, vramByGPU: map[ml.DeviceID]uint64{{Library: "Metal"}: 8 * format.GigaByte}},
sessionDuration: 10 * time.Millisecond,
numParallel: 1,
refCount: 0,
}
langModelRunner := &runnerRef{
model: &Model{Name: "llama3", ModelPath: "/fake/llama3/model"},
modelPath: "/fake/llama3/model",
llama: &mockLlm{vramSize: 4 * format.GigaByte, vramByGPU: map[ml.DeviceID]uint64{{Library: "Metal"}: 4 * format.GigaByte}},
sessionDuration: 10 * time.Millisecond,
numParallel: 1,
refCount: 0,
}
s.loadedMu.Lock()
s.loaded["/fake/flux/model"] = imageGenRunner
s.loaded["/fake/llama3/model"] = langModelRunner
s.loadedMu.Unlock()
// Verify both are loaded
s.loadedMu.Lock()
require.Len(t, s.loaded, 2)
require.NotNil(t, s.loaded["/fake/flux/model"])
require.NotNil(t, s.loaded["/fake/llama3/model"])
s.loadedMu.Unlock()
// Verify updateFreeSpace accounts for both
gpus := []ml.DeviceInfo{
{
DeviceID: ml.DeviceID{Library: "Metal"},
TotalMemory: 24 * format.GigaByte,
FreeMemory: 24 * format.GigaByte,
},
}
s.updateFreeSpace(gpus)
// Free memory should be reduced by both models
expectedFree := uint64(24*format.GigaByte) - uint64(8*format.GigaByte) - uint64(4*format.GigaByte)
require.Equal(t, expectedFree, gpus[0].FreeMemory)
}