Codex
78 lines
3.8 KiB
Java
78 lines
3.8 KiB
Java
package com.quantai.trader.model;
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import com.quantai.trader.artifact.TraderArtifactLoader;
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import com.quantai.trader.artifact.TraderModelManifest;
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import com.quantai.trader.feature.TraderFeatureVectorBuilder;
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import org.junit.jupiter.api.Test;
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import org.junit.jupiter.api.io.TempDir;
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import java.io.IOException;
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import java.nio.file.Path;
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import java.util.Map;
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import static com.quantai.trader.TestFixtures.*;
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import static org.assertj.core.api.Assertions.assertThat;
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import static org.assertj.core.api.Assertions.assertThatThrownBy;
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class OnnxTraderModelServiceTest {
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@TempDir
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Path artifactRoot;
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@Test
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void evaluatesFiveModelFamiliesWithFeatureOrderCalibrationAndOutputBounds() throws IOException {
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writeArtifactBundle(artifactRoot);
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var properties = propertiesWithArtifactRoot(artifactRoot);
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var bundle = new TraderArtifactLoader(properties, objectMapper()).loadActiveBundle();
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OnnxTraderModelService service = new OnnxTraderModelService(
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properties,
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objectMapper(),
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new TraderFeatureVectorBuilder(properties, objectMapper()),
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new FakeInferenceClient());
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var output = service.evaluate(snapshot(), bundle);
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assertThat(output.direction().longProb()).isEqualByComparingTo("0.62");
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assertThat(output.entry().longExpectedNetEdgeBps()).isEqualByComparingTo("12");
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assertThat(output.continuation().shortExpectedContinueEdgeBps()).isEqualByComparingTo("1.5");
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assertThat(output.exit().reasonScore("reversal_prob")).isEqualByComparingTo("0.25");
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assertThat(output.risk().reasonScore("liquidity_deterioration_prob")).isEqualByComparingTo("0.12");
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assertThat(output.metadata().uncertainty()).isEqualByComparingTo("0.38");
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assertThat(output.metadata().oodScore()).isEqualByComparingTo("0.05");
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}
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@Test
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void failsWhenShadowSnapshotHasNoOodScore() throws IOException {
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writeArtifactBundle(artifactRoot);
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var properties = propertiesWithArtifactRoot(artifactRoot);
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var bundle = new TraderArtifactLoader(properties, objectMapper()).loadActiveBundle();
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OnnxTraderModelService service = new OnnxTraderModelService(
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properties,
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objectMapper(),
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new TraderFeatureVectorBuilder(properties, objectMapper()),
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new FakeInferenceClient());
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var snapshot = new com.quantai.trader.domain.TraderMarketSnapshot("snapshot-1", "run-1", "cycle-1",
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"BTC-USDT-PERP", T0, "feature-v4-p0", bd("100"), bd("99.5"), bd("1.2"),
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bd("0.5"), bd("1000"), bd("1400"), bd("2200"), true, featureJson(), Map.of());
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assertThatThrownBy(() -> service.evaluate(snapshot, bundle))
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.isInstanceOf(com.quantai.trader.domain.TraderException.class)
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.hasMessageContaining("ood_score");
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}
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private static final class FakeInferenceClient implements TraderOnnxInferenceClient {
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@Override
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public Map<String, float[]> infer(TraderModelManifest manifest, Path modelPath, float[] features) {
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return switch (manifest.modelType()) {
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case "DIRECTION" -> Map.of("probabilities", new float[]{0.5f, 0.5f, 0.5f});
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case "ENTRY" -> Map.of("entry", new float[]{0.5f, 0.5f, 12.0f, 8.0f});
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case "CONTINUE" -> Map.of("continue", new float[]{0.5f, 0.5f, 3.0f, 1.5f});
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case "EXIT" -> Map.of("exit", new float[]{0.5f, 0.5f, 10.0f, 18.0f, 0.5f, 0.5f, 0.5f, 0.5f});
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case "RISK" -> Map.of("risk", new float[]{0.5f, 0.5f, 0.5f, 20.0f, 20.0f, 30.0f,
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0.5f, 0.5f, 0.5f, 0.5f, 0.5f});
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default -> throw new IllegalArgumentException("unexpected model type: " + manifest.modelType());
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};
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}
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}
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}
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