| import torch |
|
|
| from model.wan_kv_mmd import WanKVMMD |
| from video_fd.encoders.vjepa2_dense_metadata import ( |
| canonical_vjepa2_dense_feature_metadata, |
| uniform_dense_token_indices, |
| ) |
|
|
|
|
| def test_triple_vjepa_metadata_matches_bank_last_64_contract(): |
| model = object.__new__(WanKVMMD) |
| model.feature_type = "triple_dinov3_vjepa2_videomae_v2_dense_latent" |
| model.dense_feature_prefix = "triple" |
| model.dense_encoder_name = "triple" |
| model.dense_log_prefix = "triple_dense" |
| model.vjepa2_reference_model_id = "vjepa2-vitl-fpc64-256" |
| model.vjepa2_model_id = "/unused/local/model" |
| model.vjepa2_dense_layer = 15 |
| model.vjepa2_dense_layers = (15,) |
| model.vjepa2_dense_num_frames = 64 |
| model.vjepa2_dense_source_num_frames = 81 |
| model.vjepa2_dense_frame_sampling = "last_contiguous" |
| model.vjepa2_dense_resize_short_side = 292 |
| model.vjepa2_dense_crop_size = 256 |
| model.vjepa2_dense_raw_tokens = 2048 |
| model.vjepa2_dense_num_tokens = 1024 |
| model.vjepa2_dense_feature_dim = 1024 |
| indices = uniform_dense_token_indices(2048, 1024) |
| actual = model._vjepa2_feature_metadata(indices) |
| expected = canonical_vjepa2_dense_feature_metadata( |
| model_id="vjepa2-vitl-fpc64-256", |
| layer_index=15, |
| num_frames=64, |
| resize_short_side=292, |
| crop_size=256, |
| raw_tokens=2048, |
| num_tokens=1024, |
| feature_dim=1024, |
| token_indices=indices, |
| frame_sampling="last_contiguous", |
| source_num_frames=81, |
| ) |
| assert actual == expected |
| assert actual["selected_frame_start"] == 17 |
| assert actual["selected_frame_end_inclusive"] == 80 |
|
|
|
|
| def test_dual_dinov3_vjepa_metadata_uses_explicit_uniform_indices_by_default(): |
| model = object.__new__(WanKVMMD) |
| model.feature_type = "dual_dinov3_vjepa2_dense_latent" |
| model.dense_feature_prefix = "dinov3_vjepa2" |
| model.dense_encoder_name = "dinov3_vjepa2" |
| model.dense_log_prefix = "dinov3_vjepa2_dense" |
| model.vjepa2_reference_model_id = "vjepa2-vitl-fpc64-256" |
| model.vjepa2_model_id = "/unused/local/model" |
| model.vjepa2_dense_layer = 15 |
| model.vjepa2_dense_layers = (15,) |
| model.vjepa2_dense_num_frames = 64 |
| model.vjepa2_dense_source_num_frames = 81 |
| model.vjepa2_dense_frame_sampling = "center_contiguous" |
| model.vjepa2_dense_resize_short_side = 292 |
| model.vjepa2_dense_crop_size = 256 |
| model.vjepa2_dense_raw_tokens = 2048 |
| model.vjepa2_dense_num_tokens = 1024 |
| model.vjepa2_dense_feature_dim = 1024 |
| actual = model._vjepa2_feature_metadata() |
| indices = uniform_dense_token_indices(2048, 1024) |
| expected = canonical_vjepa2_dense_feature_metadata( |
| model_id="vjepa2-vitl-fpc64-256", |
| layer_index=15, |
| num_frames=64, |
| resize_short_side=292, |
| crop_size=256, |
| raw_tokens=2048, |
| num_tokens=1024, |
| feature_dim=1024, |
| token_indices=indices, |
| frame_sampling="last_contiguous", |
| source_num_frames=81, |
| ) |
| assert actual == expected |
| assert actual["token_alignment"] == "same_explicit_indices_and_order" |
|
|
|
|
| def test_frozen_videomae_identity_never_accesses_old_mount(monkeypatch): |
| from video_fd.encoders import videomae_v2_dense_metadata as vm |
| identity = "/unavailable/reference/model" |
| expected = vm.canonical_videomae_v2_dense_feature_metadata( |
| model_id=identity, layer_index=15, num_tokens=256, |
| model_id_is_reference=True) |
| def forbidden(*args, **kwargs): |
| raise AssertionError("Frozen reference identity was treated as a local path") |
| monkeypatch.setattr(vm.os.path, "exists", forbidden) |
| monkeypatch.setattr(vm.os.path, "realpath", forbidden) |
| actual = vm.canonical_videomae_v2_dense_feature_metadata( |
| model_id=identity, layer_index=15, num_tokens=256, |
| model_id_is_reference=True) |
| assert actual == expected |
| assert actual["model_id"] == identity |
|
|
|
|
| def test_dinov3_relocation_preserves_frozen_metadata_without_changing_load_paths(): |
| import hashlib |
| import json |
| from types import SimpleNamespace |
| model = object.__new__(WanKVMMD) |
| torch.nn.Module.__init__(model) |
| metadata = dict(feature_type='dinov3_dense_latent', model_id='dinov3', |
| raw_tokens=5120, num_tokens=1024, feature_dim=1024, matrix_shape=[1024, 1024], |
| repo_path='/relocated/models/dinov3-src', weight_path='/relocated/models/weights.pth') |
| model.dinov3_encoder = SimpleNamespace(feature_metadata=lambda: dict(metadata)) |
| model.dinov3_model_id = 'dinov3' |
| model.dinov3_dense_raw_tokens = 5120 |
| model.dinov3_dense_num_tokens = model.dinov3_dense_feature_dim = 1024 |
| model.dinov3_reference_paths = dict(repo_path='/frozen/models/dinov3-src', weight_path='/frozen/models/weights.pth') |
| expected = {**metadata, **model.dinov3_reference_paths} |
| expected['feature_contract_sha256'] = hashlib.sha256(json.dumps(expected, |
| sort_keys=True, separators=(',', ':'), ensure_ascii=True, allow_nan=False).encode()).hexdigest() |
| assert model._dinov3_feature_metadata() == expected |
| assert model.dinov3_encoder.feature_metadata()['repo_path'] == '/relocated/models/dinov3-src' |
|
|
