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Update lora affinity to be a scorer. #1121
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Original file line number | Diff line number | Diff line change |
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/* | ||
Copyright 2025 The Kubernetes Authors. | ||
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Licensed under the Apache License, Version 2.0 (the "License"); | ||
you may not use this file except in compliance with the License. | ||
You may obtain a copy of the License at | ||
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http://www.apache.org/licenses/LICENSE-2.0 | ||
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Unless required by applicable law or agreed to in writing, software | ||
distributed under the License is distributed on an "AS IS" BASIS, | ||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
See the License for the specific language governing permissions and | ||
limitations under the License. | ||
*/ | ||
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package scorer | ||
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import ( | ||
"context" | ||
"encoding/json" | ||
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"sigs.k8s.io/gateway-api-inference-extension/pkg/epp/plugins" | ||
"sigs.k8s.io/gateway-api-inference-extension/pkg/epp/scheduling/framework" | ||
"sigs.k8s.io/gateway-api-inference-extension/pkg/epp/scheduling/types" | ||
) | ||
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const ( | ||
DefaultLoraAffinityScorerWeight = 1 | ||
LoraAffinityScorerType = "lora-affinity" | ||
) | ||
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// compile-time type assertion | ||
var _ framework.Scorer = &LoraAffinityScorer{} | ||
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// LoraAffinityScorerFactory defines the factory function for LoraAffinityScorer. | ||
func LoraAffinityScorerFactory(name string, _ json.RawMessage, _ plugins.Handle) (plugins.Plugin, error) { | ||
return NewLoraAffinityScorer().WithName(name), nil | ||
} | ||
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// NewLoraAffinityScorer initializes a new LoraAffinityScorer and returns its pointer. | ||
func NewLoraAffinityScorer() *LoraAffinityScorer { | ||
return &LoraAffinityScorer{ | ||
tn: plugins.TypedName{Type: LoraAffinityScorerType, Name: LoraAffinityScorerType}, | ||
} | ||
} | ||
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// LoraAffinityScorer scores list of candidate pods based on Lora affinity and availability. | ||
type LoraAffinityScorer struct { | ||
tn plugins.TypedName | ||
} | ||
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// TypedName returns the type and name tuple of this plugin instance. | ||
func (s *LoraAffinityScorer) TypedName() plugins.TypedName { | ||
return s.tn | ||
} | ||
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// WithName sets the name of the scorer. | ||
func (s *LoraAffinityScorer) WithName(name string) *LoraAffinityScorer { | ||
s.tn.Name = name | ||
return s | ||
} | ||
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func (s *LoraAffinityScorer) Score(_ context.Context, _ *types.CycleState, request *types.LLMRequest, pods []types.Pod) map[types.Pod]float64 { | ||
scores := make(map[types.Pod]float64, len(pods)) | ||
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// Assign a score to each pod for loading the target adapter. | ||
for _, pod := range pods { | ||
_, active := pod.GetMetrics().ActiveModels[request.TargetModel] | ||
_, waiting := pod.GetMetrics().WaitingModels[request.TargetModel] | ||
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// Determine the model server's suitability score based on adapter load status and capacity. | ||
switch { | ||
// Ideal: The adapter is already active on this model server. | ||
case active: | ||
scores[pod] = 1.0 | ||
// Good: The model server has capacity to load at least one more adapter. | ||
case len(pod.GetMetrics().ActiveModels)+len(pod.GetMetrics().WaitingModels) < pod.GetMetrics().MaxActiveModels: | ||
scores[pod] = 0.8 | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. how did you select these numbers? is it based on some tests? performance comparison? intuition? There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. +1; how does this compare to the approach we have in the decision tree plugin. @kaushikmitr pls take a look as well |
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// Moderate: The adapter is already in the queue to be loaded on this model server. | ||
case waiting: | ||
scores[pod] = 0.6 | ||
// Unsuitable: The model server has reached its maximum capacity and cannot load the adapter. | ||
default: | ||
scores[pod] = 0.0 | ||
} | ||
} | ||
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return scores | ||
} |
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/* | ||
Copyright 2025 The Kubernetes Authors. | ||
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Licensed under the Apache License, Version 2.0 (the "License"); | ||
you may not use this file except in compliance with the License. | ||
You may obtain a copy of the License at | ||
|
||
http://www.apache.org/licenses/LICENSE-2.0 | ||
|
||
Unless required by applicable law or agreed to in writing, software | ||
distributed under the License is distributed on an "AS IS" BASIS, | ||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
See the License for the specific language governing permissions and | ||
limitations under the License. | ||
*/ | ||
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package scorer | ||
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import ( | ||
"context" | ||
"testing" | ||
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"github.com/stretchr/testify/assert" | ||
k8stypes "k8s.io/apimachinery/pkg/types" | ||
"sigs.k8s.io/gateway-api-inference-extension/pkg/epp/backend" | ||
backendmetrics "sigs.k8s.io/gateway-api-inference-extension/pkg/epp/backend/metrics" | ||
"sigs.k8s.io/gateway-api-inference-extension/pkg/epp/scheduling/types" | ||
) | ||
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func TestLoraAffinityScorer(t *testing.T) { | ||
tests := []struct { | ||
name string | ||
request *types.LLMRequest | ||
pods []types.Pod | ||
expectedScoresPod map[string]float64 // Map of pod name to expected score | ||
}{ | ||
{ | ||
name: "Target model is active", | ||
request: &types.LLMRequest{TargetModel: "active-model-1"}, | ||
pods: []types.Pod{ | ||
&types.PodMetrics{ | ||
Pod: &backend.Pod{NamespacedName: k8stypes.NamespacedName{Name: "pod1"}}, | ||
MetricsState: &backendmetrics.MetricsState{ | ||
ActiveModels: map[string]int{"active-model-1": 1}, | ||
WaitingModels: map[string]int{}, | ||
MaxActiveModels: 5, | ||
}, | ||
}, | ||
}, | ||
expectedScoresPod: map[string]float64{ | ||
"pod1": 1.0, | ||
}, | ||
}, | ||
{ | ||
name: "Target model is waiting", | ||
request: &types.LLMRequest{TargetModel: "active-model-1"}, | ||
pods: []types.Pod{ | ||
&types.PodMetrics{ | ||
Pod: &backend.Pod{NamespacedName: k8stypes.NamespacedName{Name: "pod1"}}, | ||
MetricsState: &backendmetrics.MetricsState{ | ||
ActiveModels: map[string]int{"active-model-2": 2}, | ||
WaitingModels: map[string]int{"active-model-1": 1}, | ||
MaxActiveModels: 2, | ||
}, | ||
}, | ||
}, | ||
expectedScoresPod: map[string]float64{ | ||
"pod1": 0.6, | ||
}, | ||
}, | ||
{ | ||
name: "Pods have no space for new model", | ||
request: &types.LLMRequest{TargetModel: "active-model-1"}, | ||
pods: []types.Pod{ | ||
&types.PodMetrics{ | ||
Pod: &backend.Pod{NamespacedName: k8stypes.NamespacedName{Name: "pod1"}}, | ||
MetricsState: &backendmetrics.MetricsState{ | ||
ActiveModels: map[string]int{"active-model-2": 2}, | ||
WaitingModels: map[string]int{"active-model-3": 1}, | ||
MaxActiveModels: 2, | ||
}, | ||
}, | ||
&types.PodMetrics{ | ||
Pod: &backend.Pod{NamespacedName: k8stypes.NamespacedName{Name: "pod2"}}, | ||
MetricsState: &backendmetrics.MetricsState{ | ||
ActiveModels: map[string]int{}, | ||
WaitingModels: map[string]int{}, | ||
MaxActiveModels: 0, | ||
}, | ||
}, | ||
}, | ||
expectedScoresPod: map[string]float64{ | ||
"pod1": 0.0, | ||
"pod2": 0.0, | ||
}, | ||
}, | ||
{ | ||
name: "Multiple pods with mixed active and waiting models", | ||
request: &types.LLMRequest{TargetModel: "active-model-1"}, | ||
pods: []types.Pod{ | ||
&types.PodMetrics{ | ||
Pod: &backend.Pod{NamespacedName: k8stypes.NamespacedName{Name: "pod1"}}, | ||
MetricsState: &backendmetrics.MetricsState{ | ||
ActiveModels: map[string]int{"active-model-1": 1}, | ||
WaitingModels: map[string]int{}, | ||
MaxActiveModels: 5, | ||
}, | ||
}, | ||
&types.PodMetrics{ | ||
Pod: &backend.Pod{NamespacedName: k8stypes.NamespacedName{Name: "pod2"}}, | ||
MetricsState: &backendmetrics.MetricsState{ | ||
ActiveModels: map[string]int{"active-model-2": 4}, | ||
WaitingModels: map[string]int{"active-model-1": 1}, | ||
MaxActiveModels: 5, | ||
}, | ||
}, | ||
&types.PodMetrics{ | ||
Pod: &backend.Pod{NamespacedName: k8stypes.NamespacedName{Name: "pod3"}}, | ||
MetricsState: &backendmetrics.MetricsState{ | ||
ActiveModels: map[string]int{"active-model-2": 1}, | ||
WaitingModels: map[string]int{}, | ||
MaxActiveModels: 2, | ||
}, | ||
}, | ||
&types.PodMetrics{ | ||
Pod: &backend.Pod{NamespacedName: k8stypes.NamespacedName{Name: "pod4"}}, | ||
MetricsState: &backendmetrics.MetricsState{ | ||
ActiveModels: map[string]int{"active-model-3": 1}, | ||
WaitingModels: map[string]int{"active-model-1": 1}, | ||
MaxActiveModels: 2, | ||
}, | ||
}, | ||
&types.PodMetrics{ | ||
Pod: &backend.Pod{NamespacedName: k8stypes.NamespacedName{Name: "pod5"}}, | ||
MetricsState: &backendmetrics.MetricsState{ | ||
ActiveModels: map[string]int{"active-model-4": 1, "active-model-5": 1}, | ||
WaitingModels: map[string]int{}, | ||
MaxActiveModels: 2, | ||
}, | ||
}, | ||
}, | ||
expectedScoresPod: map[string]float64{ | ||
"pod1": 1.0, | ||
"pod2": 0.8, | ||
"pod3": 0.8, | ||
"pod4": 0.6, | ||
"pod5": 0.0, | ||
}, | ||
}, | ||
{ | ||
name: "Empty pods slice", | ||
request: &types.LLMRequest{TargetModel: "modelA"}, | ||
pods: []types.Pod{}, | ||
expectedScoresPod: map[string]float64{}, // No pods, no scores | ||
}, | ||
} | ||
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for _, test := range tests { | ||
t.Run(test.name, func(t *testing.T) { | ||
scorer := &LoraAffinityScorer{} | ||
scores := scorer.Score(context.Background(), types.NewCycleState(), test.request, test.pods) | ||
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for _, pod := range test.pods { | ||
expectedScore, ok := test.expectedScoresPod[pod.GetPod().NamespacedName.Name] | ||
if !ok { | ||
t.Fatalf("Expected score not found for pod %s in test %s", pod.GetPod().NamespacedName, test.name) | ||
} | ||
assert.InDelta(t, expectedScore, scores[pod], 0.0001, "Pod %s should have score %f", pod.GetPod().NamespacedName.Name, expectedScore) | ||
} | ||
assert.Len(t, scores, len(test.expectedScoresPod), "Number of scored pods should match expected") | ||
}) | ||
} | ||
} |
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Q: perhaps allow setting DefaultLoraAffinityScorerWeight via configuration parameters in the config file?
We're trying to avoid using environment variables (e.g., added in runner.go).
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we are planning to have GIE default weight for scorers. if no weight specified in the config the weight will default to 1 automatically by the config api code.
this will be pushed in a separate, not in scope of this PR of course.