| import pytest |
| import torch |
| from synapse.agent import IntegratedAgent |
| from synapse.config import SynapseConfig |
| from synapse.hypernetwork import WeightSpaceHypernetwork, compile_hypernetwork_patch |
|
|
| def test_hypernetwork_patch_synthesis(): |
| config = SynapseConfig(seed=42, nodes_per_source=16) |
| agent = IntegratedAgent(config) |
| hypernet = WeightSpaceHypernetwork(in_dim=32, rank=2) |
|
|
| diag = { |
| 'mean_return': 0.15, |
| 'total_steps': 30, |
| 'mean_graph_activity': 0.08, |
| 'mean_approach_valence': 0.2, |
| 'mean_avoid_valence': -0.1, |
| 'action_mean': [0.1, -0.05, 0.0, 0.0, 0.0], |
| 'task': 'forage', |
| } |
|
|
| patch = compile_hypernetwork_patch(agent, hypernet, diag, target_surface='motor.weight', max_edits=16) |
| assert patch['schema'] == 'synapse-weight-program-v1' |
| assert patch['writes'] > 0 |
| assert patch['delta_l2'] >= 0.0 |
|
|
| |
| graft_patch = compile_hypernetwork_patch(agent, hypernet, diag, target_surface='brain.graft_w', max_edits=16) |
| assert graft_patch['schema'] == 'synapse-weight-program-v1' |
| assert graft_patch['writes'] > 0 |
|
|
