Files
milvus-io--milvus/internal/util/function/chain/expr/xgboost_expr_test.go
T
wehub-resource-sync 498b235461
Build and test / Build and test AMD64 Ubuntu 22.04 (push) Failing after 0s
Publish Builder / amazonlinux2023 (push) Failing after 1s
Build and test / UT for Go (push) Has been skipped
Publish KRTE Images / KRTE (push) Failing after 1s
Build and test / Integration Test (push) Has been skipped
Build and test / Upload Code Coverage (push) Has been skipped
Publish Builder / rockylinux9 (push) Failing after 1s
Publish Builder / ubuntu22.04 (push) Failing after 0s
Publish Builder / ubuntu24.04 (push) Failing after 0s
Publish Gpu Builder / publish-gpu-builder (push) Failing after 1s
Publish Test Images / PyTest (push) Failing after 0s
Build and test / UT for Cpp (push) Has been cancelled
chore: import upstream snapshot with attribution
2026-07-13 12:31:17 +08:00

162 lines
5.6 KiB
Go

// Licensed to the LF AI & Data foundation under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you 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.
package expr
import (
"testing"
"github.com/apache/arrow/go/v17/arrow"
"github.com/apache/arrow/go/v17/arrow/array"
"github.com/apache/arrow/go/v17/arrow/memory"
"github.com/stretchr/testify/assert"
"github.com/stretchr/testify/require"
"github.com/milvus-io/milvus-proto/go-api/v3/schemapb"
"github.com/milvus-io/milvus/internal/util/function/chain/types"
)
func TestNewXGBoostExprFromParams(t *testing.T) {
params := map[string]*schemapb.FunctionParamValue{
xgboostParamModelResource: stringParam("rank_model"),
xgboostParamOutput: stringParam(xgboostOutputRaw),
}
expr, err := NewXGBoostExprFromParams(types.FunctionBuildContext{}, types.FunctionConfig{Params: params})
require.NoError(t, err)
xgb, ok := expr.(*XGBoostExpr)
require.True(t, ok)
assert.Equal(t, "rank_model", xgb.modelResource)
assert.Equal(t, xgboostOutputRaw, xgb.output)
assert.True(t, xgb.IsRunnable(types.StageL0Rerank))
assert.False(t, xgb.IsRunnable(types.StageL1Rerank))
assert.False(t, xgb.IsRunnable(types.StageL2Rerank))
}
func TestNewXGBoostExprFromParamsDefaults(t *testing.T) {
expr, err := NewXGBoostExprFromParams(types.FunctionBuildContext{}, types.FunctionConfig{Params: map[string]*schemapb.FunctionParamValue{
xgboostParamModelResource: stringParam("rank_model"),
}})
require.NoError(t, err)
xgb := expr.(*XGBoostExpr)
assert.Equal(t, xgboostOutputDefault, xgb.output)
}
func TestNewXGBoostExprFromParamsInvalid(t *testing.T) {
cases := []struct {
name string
params map[string]*schemapb.FunctionParamValue
}{
{
name: "missing model resource",
params: map[string]*schemapb.FunctionParamValue{},
},
{
name: "invalid output",
params: map[string]*schemapb.FunctionParamValue{
xgboostParamModelResource: stringParam("rank_model"),
xgboostParamOutput: stringParam("probability"),
},
},
{
name: "model_format unsupported",
params: map[string]*schemapb.FunctionParamValue{
xgboostParamModelResource: stringParam("rank_model"),
"model_format": stringParam("json"),
},
},
{
name: "feature_names unsupported",
params: map[string]*schemapb.FunctionParamValue{
xgboostParamModelResource: stringParam("rank_model"),
xgboostParamFeatureNames: stringParam("feature"),
},
},
{
name: "objective unsupported",
params: map[string]*schemapb.FunctionParamValue{
xgboostParamModelResource: stringParam("rank_model"),
xgboostParamObjective: stringParam("binary:logistic"),
},
},
{
name: "unknown param",
params: map[string]*schemapb.FunctionParamValue{
xgboostParamModelResource: stringParam("rank_model"),
"unknown": stringParam("value"),
},
},
}
for _, tc := range cases {
t.Run(tc.name, func(t *testing.T) {
_, err := NewXGBoostExprFromParams(types.FunctionBuildContext{}, types.FunctionConfig{Params: tc.params})
assert.Error(t, err)
})
}
}
func TestXGBoostExprValidateArgs(t *testing.T) {
expr, err := NewXGBoostExpr("rank_model", "", nil)
require.NoError(t, err)
assert.Error(t, expr.ValidateArgs(nil))
assert.NoError(t, expr.ValidateArgs([]*schemapb.FunctionChainExprArg{xgboostColumnArg("price")}))
assert.Error(t, expr.ValidateArgs([]*schemapb.FunctionChainExprArg{xgboostLiteralStringArg("price")}))
}
func TestValidateXGBoostInputChunks(t *testing.T) {
pool := memory.NewCheckedAllocator(memory.DefaultAllocator)
defer pool.AssertSize(t, 0)
col1 := newFloat32Chunked(pool, [][]float32{{1, 2}, {3}})
defer col1.Release()
col2 := newFloat32Chunked(pool, [][]float32{{4, 5}, {6}})
defer col2.Release()
assert.NoError(t, validateXGBoostInputChunks([]*arrow.Chunked{col1, col2}))
badChunkCount := newFloat32Chunked(pool, [][]float32{{1, 2}})
defer badChunkCount.Release()
assert.Error(t, validateXGBoostInputChunks([]*arrow.Chunked{col1, badChunkCount}))
badChunkLen := newFloat32Chunked(pool, [][]float32{{1}, {2}})
defer badChunkLen.Release()
assert.Error(t, validateXGBoostInputChunks([]*arrow.Chunked{col1, badChunkLen}))
assert.Error(t, validateXGBoostInputChunks([]*arrow.Chunked{nil}))
}
func xgboostColumnArg(name string) *schemapb.FunctionChainExprArg {
return &schemapb.FunctionChainExprArg{Arg: &schemapb.FunctionChainExprArg_Column{Column: &schemapb.FunctionChainColumnArg{Name: name}}}
}
func xgboostLiteralStringArg(value string) *schemapb.FunctionChainExprArg {
return &schemapb.FunctionChainExprArg{Arg: &schemapb.FunctionChainExprArg_Literal{Literal: stringParam(value)}}
}
func newFloat32Chunked(pool memory.Allocator, values [][]float32) *arrow.Chunked {
chunks := make([]arrow.Array, 0, len(values))
for _, chunkValues := range values {
builder := array.NewFloat32Builder(pool)
builder.AppendValues(chunkValues, nil)
chunk := builder.NewArray()
builder.Release()
chunks = append(chunks, chunk)
}
chunked := arrow.NewChunked(arrow.PrimitiveTypes.Float32, chunks)
for _, chunk := range chunks {
chunk.Release()
}
return chunked
}