| import torch |
| from lightnest.global_patch_context import GlobalPatchNetwork,freeze,examples |
| from lightnest.learned_patch import batch,PatchNetwork |
| from lightnest.probe_receptive_field import measure |
|
|
| def test_frozen_pairs_and_labels(): |
| pairs=freeze(12,2,'combined');ex=examples(pairs) |
| assert len(ex)==4 |
| assert all(sum(a!=b for a,b in zip(e.binary,e.target))==1 for e in ex) |
| assert freeze(12,2,'combined')==pairs |
|
|
| def test_global_context_breaks_local_invariance(): |
| torch.set_num_threads(2);torch.manual_seed(82) |
| pairs=freeze(12,2,'combined');local=PatchNetwork();global_model=GlobalPatchNetwork() |
| global_model.load_state_dict(local.state_dict(),strict=False) |
| with torch.no_grad(): global_model.global_scale.fill_(1.) |
| assert all(x['pair_difference_change']==0 for x in measure(local,pairs)) |
| assert any(x['pair_difference_change']>1e-5 for x in measure(global_model,pairs)) |
| assert not global_model.native_packer_compatible |
|
|
| def test_outputs_and_gradients(): |
| torch.set_num_threads(2);model=GlobalPatchNetwork();c,b,p,y=batch(examples(freeze(13,1,'train'))) |
| scores,bits=model(c,b) |
| assert scores.shape==(2,257) and bits.shape==(2,256,8) |
| torch.nn.functional.cross_entropy(scores,p).backward() |
| assert model.global_attention.in_proj_weight.grad.abs().sum()>0 |
| assert torch.isfinite(scores).all() |
|
|
