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0ce9643 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 | """Tests for AnalysisEngine — mock model scans."""
from neural_mri.core.analysis_engine import AnalysisEngine
def test_scan_structural_layer_count(mock_model_manager):
engine = AnalysisEngine(mock_model_manager)
data = engine.scan_structural()
# embed + 2*(attn+mlp) + unembed = 1 + 4 + 1 = 6
assert len(data.layers) == 6
assert data.layers[0].layer_type == "embedding"
assert data.layers[-1].layer_type == "output"
def test_scan_structural_connections(mock_model_manager):
engine = AnalysisEngine(mock_model_manager)
data = engine.scan_structural()
assert len(data.connections) == len(data.layers) - 1
def test_scan_structural_metadata(mock_model_manager):
engine = AnalysisEngine(mock_model_manager)
data = engine.scan_structural()
assert "device" in data.metadata
assert "compute_time_ms" in data.metadata
def test_scan_weights_returns_stats(mock_model_manager):
engine = AnalysisEngine(mock_model_manager)
data = engine.scan_weights()
assert len(data.layers) > 0
for layer in data.layers:
assert layer.l2_norm > 0
assert len(layer.histogram) == 20
def test_scan_activation_returns_normalized(mock_model_manager):
engine = AnalysisEngine(mock_model_manager)
from neural_mri.schemas.scan import ActivationScanRequest
data = engine.scan_activation(ActivationScanRequest(prompt="test"))
for layer in data.layers:
for val in layer.activations:
assert 0.0 <= val <= 1.0
def test_scan_anomaly_layer_count(mock_model_manager):
engine = AnalysisEngine(mock_model_manager)
from neural_mri.schemas.scan import AnomalyScanRequest
data = engine.scan_anomaly(AnomalyScanRequest(prompt="test"))
assert len(data.layers) == 2 # n_layers=2
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