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FusionAGI/tests/test_gpu_attention.py

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"""Tests for fusionagi.gpu.tensor_attention."""
import pytest
feat: complete all 19 tasks — liquid networks, quantum backend, embodiment, self-model, ASI rubric, plugin system, auth/rate-limit middleware, async adapters, CI/CD, Dockerfile, benchmarks, module boundary fix, TTS adapter, lifespan migration, OpenAPI docs, code cleanup Items completed: 1. Merged PR #2 (starlette/httpx deps) 2. Fixed async race condition in multimodal_ui.py 3. Wired TTSAdapter (ElevenLabs, Azure) in API routes 4. Moved super_big_brain.py from core/ to reasoning/ (backward compat shim) 5. Added API authentication middleware (Bearer token via FUSIONAGI_API_KEY) 6. Added async adapter interface (acomplete/acomplete_structured) 7. Migrated FastAPI on_event to lifespan (fixes 20 deprecation warnings) 8. Liquid Neural Networks (continuous-time adaptive weights) 9. Quantum-AI Hybrid compute backend (simulator + optimization) 10. Embodied Intelligence / Robotics bridge (actuator + sensor protocols) 11. Consciousness Engineering (formal self-model with introspection) 12. ASI Scoring Rubric (C/A/L/N/R self-assessment harness) 13. GPU integration tests for TensorFlow backend 14. Multi-stage production Dockerfile 15. Gitea CI/CD pipeline (lint, test matrix, Docker build) 16. API rate limiting middleware (per-IP sliding window) 17. OpenAPI docs cleanup (auth + rate limiting descriptions) 18. Benchmarking suite (decomposition, multi-path, recomposition, e2e) 19. Plugin system (head registry for custom heads) 427 tests passing, 0 ruff errors, 0 mypy errors. Co-Authored-By: Nakamoto, S <defi@defi-oracle.io>
2026-04-28 08:32:05 +00:00
from fusionagi.gpu.backend import get_backend, reset_backend
from fusionagi.gpu.tensor_attention import (
attention_consensus,
cross_claim_attention,
)
@pytest.fixture(autouse=True)
def _use_numpy():
reset_backend()
get_backend(force="numpy")
yield
reset_backend()
class TestAttentionConsensus:
def test_empty(self):
result = attention_consensus([], "query")
assert result["head_scores"] == []
assert result["consensus_score"] == 0.0
def test_single_head(self):
result = attention_consensus(
[["the sky is blue"]],
"what color is the sky",
)
assert len(result["head_scores"]) == 1
assert isinstance(result["consensus_score"], float)
def test_multiple_heads(self):
result = attention_consensus(
[
["the sky is blue", "water is wet"],
["security is important"],
["cost should be minimized"],
],
"what should we do about the project",
)
assert len(result["head_scores"]) == 3
assert 0.0 <= result["consensus_score"] <= 1.0
def test_with_weights(self):
result = attention_consensus(
[["claim a"], ["claim b"]],
"query",
head_weights=[2.0, 0.5],
)
assert len(result["head_scores"]) == 2
def test_empty_claims(self):
result = attention_consensus(
[[], []],
"query",
)
assert len(result["head_scores"]) == 2
assert result["head_scores"] == [0.0, 0.0]
class TestCrossClaimAttention:
def test_empty(self):
result = cross_claim_attention([])
assert result["similarity_matrix"] == []
assert result["conflict_pairs"] == []
def test_single(self):
result = cross_claim_attention(["only one claim"])
assert result["similarity_matrix"] == []
def test_two_claims(self):
result = cross_claim_attention(["claim one", "claim two"])
assert len(result["similarity_matrix"]) == 2
assert len(result["similarity_matrix"][0]) == 2
def test_self_similarity_high(self):
result = cross_claim_attention(["same text", "same text"])
sim = result["similarity_matrix"]
assert sim[0][0] > 0.9
assert sim[1][1] > 0.9
def test_conflict_detection(self):
result = cross_claim_attention([
"the project is very safe and reliable",
"completely unrelated topic about food and cooking",
])
assert isinstance(result["conflict_pairs"], list)