mirror of
https://github.com/ollama/ollama.git
synced 2026-07-23 09:10:53 -05:00
* Update MLX and MLX-C * Run MLX CGO work on a locked OS thread MLX now relies on OS-thread-local execution state for streams, encoders, and caches. Add an mlxthread executor backed by runtime.LockOSThread and route runner initialization, model load, inference, status memory reads, and cleanup through the worker so Go goroutine migration cannot split MLX state across native threads. Also stop caching default MLX streams before the runner owns the thread and add worker/threaded MLX regression tests. * mlx: use common status writer * mlx: bundle missing libjaccl on arm64 Inspired by #15793 * review comments
180 lines
4.6 KiB
Go
180 lines
4.6 KiB
Go
package mlxrunner
|
|
|
|
import (
|
|
"context"
|
|
"errors"
|
|
"log/slog"
|
|
"net"
|
|
"net/http"
|
|
"strings"
|
|
|
|
"golang.org/x/sync/errgroup"
|
|
|
|
"github.com/ollama/ollama/api"
|
|
"github.com/ollama/ollama/x/internal/mlxthread"
|
|
"github.com/ollama/ollama/x/mlxrunner/mlx"
|
|
"github.com/ollama/ollama/x/mlxrunner/model"
|
|
"github.com/ollama/ollama/x/mlxrunner/model/base"
|
|
"github.com/ollama/ollama/x/mlxrunner/sample"
|
|
"github.com/ollama/ollama/x/tokenizer"
|
|
)
|
|
|
|
// Request is a short-lived struct that carries a completion request through
|
|
// a channel from the HTTP handler to the runner goroutine. The ctx field
|
|
// must travel with the request so that cancellation propagates across the
|
|
// channel boundary.
|
|
type Request struct {
|
|
CompletionRequest
|
|
Responses chan CompletionResponse
|
|
Pipeline func(context.Context, Request) error
|
|
|
|
Ctx context.Context //nolint:containedctx
|
|
Tokens []int32
|
|
SamplerOpts sample.Options
|
|
}
|
|
|
|
type Runner struct {
|
|
Model base.Model
|
|
Tokenizer *tokenizer.Tokenizer
|
|
Requests chan Request
|
|
Sampler *sample.Sampler
|
|
cache kvCache
|
|
contextLength int
|
|
mlxThread *mlxthread.Thread
|
|
}
|
|
|
|
func (r *Runner) Load(modelName string) error {
|
|
root, err := model.Open(modelName)
|
|
if err != nil {
|
|
return err
|
|
}
|
|
defer root.Close()
|
|
|
|
m, err := base.New(root)
|
|
if err != nil {
|
|
return err
|
|
}
|
|
|
|
// Load all tensor blobs from manifest
|
|
tensors, err := loadTensorsFromManifest(root)
|
|
if err != nil {
|
|
return err
|
|
}
|
|
|
|
// Assign weights to model (model-specific logic)
|
|
loadWeights := base.Weights(m)
|
|
if err := loadWeights(tensors); err != nil {
|
|
return err
|
|
}
|
|
|
|
r.Model = m
|
|
r.Tokenizer = m.Tokenizer()
|
|
r.contextLength = m.MaxContextLength()
|
|
r.Sampler = sample.New(r.contextLength)
|
|
|
|
mlx.EnableCompile()
|
|
return nil
|
|
}
|
|
|
|
// loadTensorsFromManifest loads all tensor blobs from the manifest into a
|
|
// flat map, deduplicating by digest and remapping safetensors key suffixes.
|
|
//
|
|
// Uses a two-phase approach: first loads all raw tensors, then remaps
|
|
// .bias → _qbias with complete knowledge of which base names have .scale
|
|
// entries. This avoids a race condition where Go map iteration order could
|
|
// cause .bias to be processed before .scale within the same blob.
|
|
func loadTensorsFromManifest(root *model.Root) (map[string]*mlx.Array, error) {
|
|
// Phase 1: Load all tensors raw from all blobs
|
|
rawTensors := make(map[string]*mlx.Array)
|
|
seen := make(map[string]bool)
|
|
for _, layer := range root.Manifest.GetTensorLayers("") {
|
|
if seen[layer.Digest] {
|
|
continue
|
|
}
|
|
seen[layer.Digest] = true
|
|
blobPath := root.Manifest.BlobPath(layer.Digest)
|
|
for name, arr := range mlx.Load(blobPath) {
|
|
rawTensors[name] = arr
|
|
}
|
|
}
|
|
|
|
// Phase 2: Identify all base names that have .scale tensors and remap them
|
|
scaleBaseNames := make(map[string]bool)
|
|
allTensors := make(map[string]*mlx.Array, len(rawTensors))
|
|
for name, arr := range rawTensors {
|
|
if strings.HasSuffix(name, ".scale") {
|
|
baseName := strings.TrimSuffix(name, ".scale")
|
|
allTensors[baseName+"_scale"] = arr
|
|
scaleBaseNames[baseName] = true
|
|
}
|
|
}
|
|
|
|
// Phase 3: Process remaining tensors with complete scale knowledge
|
|
for name, arr := range rawTensors {
|
|
if strings.HasSuffix(name, ".scale") {
|
|
continue // already handled
|
|
}
|
|
if strings.HasSuffix(name, ".bias") && !strings.HasSuffix(name, ".weight_qbias") {
|
|
baseName := strings.TrimSuffix(name, ".bias")
|
|
if scaleBaseNames[baseName] {
|
|
allTensors[baseName+"_qbias"] = arr
|
|
} else {
|
|
allTensors[name] = arr
|
|
}
|
|
} else {
|
|
allTensors[name] = arr
|
|
}
|
|
}
|
|
|
|
slog.Info("Loaded tensors from manifest", "count", len(allTensors))
|
|
return allTensors, nil
|
|
}
|
|
|
|
func (r *Runner) Run(host, port string, mux http.Handler) error {
|
|
g, ctx := errgroup.WithContext(context.Background())
|
|
|
|
g.Go(func() error {
|
|
for {
|
|
select {
|
|
case <-ctx.Done():
|
|
return nil
|
|
case request := <-r.Requests:
|
|
err := r.runRequest(request)
|
|
if err != nil {
|
|
slog.Info("Request terminated", "error", err)
|
|
var statusErr api.StatusError
|
|
if !errors.As(err, &statusErr) {
|
|
statusErr = api.StatusError{
|
|
StatusCode: http.StatusInternalServerError,
|
|
ErrorMessage: err.Error(),
|
|
}
|
|
}
|
|
select {
|
|
case request.Responses <- CompletionResponse{Error: &statusErr}:
|
|
case <-request.Ctx.Done():
|
|
}
|
|
}
|
|
|
|
close(request.Responses)
|
|
}
|
|
}
|
|
})
|
|
|
|
g.Go(func() error {
|
|
slog.Info("Starting HTTP server", "host", host, "port", port)
|
|
return http.ListenAndServe(net.JoinHostPort(host, port), mux)
|
|
})
|
|
|
|
return g.Wait()
|
|
}
|
|
|
|
func (r *Runner) runRequest(request Request) error {
|
|
if r.mlxThread == nil {
|
|
return request.Pipeline(request.Ctx, request)
|
|
}
|
|
|
|
return r.mlxThread.Do(request.Ctx, func() error {
|
|
return request.Pipeline(request.Ctx, request)
|
|
})
|
|
}
|