|
| 1 | +from contextlib import contextmanager, nullcontext |
| 2 | +from types import SimpleNamespace |
| 3 | +from unittest.mock import MagicMock |
| 4 | + |
| 5 | +import torch |
| 6 | + |
| 7 | +from invokeai.app.invocations.compel import SDXLPromptInvocationBase |
| 8 | + |
| 9 | + |
| 10 | +class FakeClipTextEncoder(torch.nn.Module): |
| 11 | + def __init__(self, effective_device: torch.device): |
| 12 | + super().__init__() |
| 13 | + self.register_parameter("cpu_param", torch.nn.Parameter(torch.ones(1))) |
| 14 | + self.register_buffer("active_buffer", torch.ones(1, device=effective_device)) |
| 15 | + self.dtype = torch.float32 |
| 16 | + |
| 17 | + @property |
| 18 | + def device(self) -> torch.device: |
| 19 | + return torch.device("cpu") |
| 20 | + |
| 21 | + |
| 22 | +class FakeTokenizer: |
| 23 | + pass |
| 24 | + |
| 25 | + |
| 26 | +class FakeLoadedModel: |
| 27 | + def __init__(self, model, config=None): |
| 28 | + self._model = model |
| 29 | + self.config = config |
| 30 | + |
| 31 | + @contextmanager |
| 32 | + def model_on_device(self): |
| 33 | + yield (None, self._model) |
| 34 | + |
| 35 | + def __enter__(self): |
| 36 | + return self._model |
| 37 | + |
| 38 | + def __exit__(self, exc_type, exc, tb): |
| 39 | + return False |
| 40 | + |
| 41 | + |
| 42 | +class FakeCompel: |
| 43 | + last_init_device: torch.device | None = None |
| 44 | + |
| 45 | + def __init__(self, *args, device: torch.device, **kwargs): |
| 46 | + del args, kwargs |
| 47 | + FakeCompel.last_init_device = device |
| 48 | + self.conditioning_provider = SimpleNamespace( |
| 49 | + get_pooled_embeddings=lambda prompts: torch.ones((len(prompts), 4), dtype=torch.float32) |
| 50 | + ) |
| 51 | + |
| 52 | + @staticmethod |
| 53 | + def parse_prompt_string(prompt: str) -> str: |
| 54 | + return prompt |
| 55 | + |
| 56 | + def build_conditioning_tensor_for_conjunction(self, conjunction: str): |
| 57 | + del conjunction |
| 58 | + return torch.ones((1, 4, 4), dtype=torch.float32), {} |
| 59 | + |
| 60 | + |
| 61 | +@contextmanager |
| 62 | +def fake_apply_ti(tokenizer, text_encoder, ti_list): |
| 63 | + del text_encoder, ti_list |
| 64 | + yield tokenizer, object() |
| 65 | + |
| 66 | + |
| 67 | +def test_sdxl_run_clip_compel_uses_effective_device_for_partially_loaded_model(monkeypatch): |
| 68 | + module_path = "invokeai.app.invocations.compel" |
| 69 | + effective_device = torch.device("meta") |
| 70 | + text_encoder = FakeClipTextEncoder(effective_device=effective_device) |
| 71 | + tokenizer = FakeTokenizer() |
| 72 | + text_encoder_info = FakeLoadedModel(text_encoder, config=SimpleNamespace(base="sdxl")) |
| 73 | + tokenizer_info = FakeLoadedModel(tokenizer) |
| 74 | + |
| 75 | + mock_context = MagicMock() |
| 76 | + mock_context.models.load.side_effect = [text_encoder_info, tokenizer_info] |
| 77 | + mock_context.config.get.return_value.log_tokenization = False |
| 78 | + mock_context.util.signal_progress = MagicMock() |
| 79 | + |
| 80 | + monkeypatch.setattr(f"{module_path}.CLIPTextModel", FakeClipTextEncoder) |
| 81 | + monkeypatch.setattr(f"{module_path}.CLIPTextModelWithProjection", FakeClipTextEncoder) |
| 82 | + monkeypatch.setattr(f"{module_path}.CLIPTokenizer", FakeTokenizer) |
| 83 | + monkeypatch.setattr(f"{module_path}.Compel", FakeCompel) |
| 84 | + monkeypatch.setattr(f"{module_path}.generate_ti_list", lambda prompt, base, context: []) |
| 85 | + monkeypatch.setattr(f"{module_path}.LayerPatcher.apply_smart_model_patches", lambda **kwargs: nullcontext()) |
| 86 | + monkeypatch.setattr(f"{module_path}.ModelPatcher.apply_clip_skip", lambda *args, **kwargs: nullcontext()) |
| 87 | + monkeypatch.setattr(f"{module_path}.ModelPatcher.apply_ti", fake_apply_ti) |
| 88 | + |
| 89 | + base = SDXLPromptInvocationBase() |
| 90 | + cond, pooled = base.run_clip_compel( |
| 91 | + context=mock_context, |
| 92 | + clip_field=SimpleNamespace( |
| 93 | + text_encoder=SimpleNamespace(), tokenizer=SimpleNamespace(), loras=[], skipped_layers=0 |
| 94 | + ), |
| 95 | + prompt="test prompt", |
| 96 | + get_pooled=False, |
| 97 | + lora_prefix="lora_te1_", |
| 98 | + zero_on_empty=False, |
| 99 | + ) |
| 100 | + |
| 101 | + assert FakeCompel.last_init_device == effective_device |
| 102 | + assert cond.shape == (1, 4, 4) |
| 103 | + assert pooled is None |
| 104 | + |
| 105 | + |
| 106 | +def test_sdxl_run_clip_compel_uses_cpu_for_fully_cpu_model(monkeypatch): |
| 107 | + module_path = "invokeai.app.invocations.compel" |
| 108 | + text_encoder = FakeClipTextEncoder(effective_device=torch.device("cpu")) |
| 109 | + tokenizer = FakeTokenizer() |
| 110 | + text_encoder_info = FakeLoadedModel(text_encoder, config=SimpleNamespace(base="sdxl")) |
| 111 | + tokenizer_info = FakeLoadedModel(tokenizer) |
| 112 | + |
| 113 | + mock_context = MagicMock() |
| 114 | + mock_context.models.load.side_effect = [text_encoder_info, tokenizer_info] |
| 115 | + mock_context.config.get.return_value.log_tokenization = False |
| 116 | + mock_context.util.signal_progress = MagicMock() |
| 117 | + |
| 118 | + monkeypatch.setattr(f"{module_path}.CLIPTextModel", FakeClipTextEncoder) |
| 119 | + monkeypatch.setattr(f"{module_path}.CLIPTextModelWithProjection", FakeClipTextEncoder) |
| 120 | + monkeypatch.setattr(f"{module_path}.CLIPTokenizer", FakeTokenizer) |
| 121 | + monkeypatch.setattr(f"{module_path}.Compel", FakeCompel) |
| 122 | + monkeypatch.setattr(f"{module_path}.generate_ti_list", lambda prompt, base, context: []) |
| 123 | + monkeypatch.setattr(f"{module_path}.LayerPatcher.apply_smart_model_patches", lambda **kwargs: nullcontext()) |
| 124 | + monkeypatch.setattr(f"{module_path}.ModelPatcher.apply_clip_skip", lambda *args, **kwargs: nullcontext()) |
| 125 | + monkeypatch.setattr(f"{module_path}.ModelPatcher.apply_ti", fake_apply_ti) |
| 126 | + |
| 127 | + base = SDXLPromptInvocationBase() |
| 128 | + base.run_clip_compel( |
| 129 | + context=mock_context, |
| 130 | + clip_field=SimpleNamespace( |
| 131 | + text_encoder=SimpleNamespace(), tokenizer=SimpleNamespace(), loras=[], skipped_layers=0 |
| 132 | + ), |
| 133 | + prompt="test prompt", |
| 134 | + get_pooled=False, |
| 135 | + lora_prefix="lora_te1_", |
| 136 | + zero_on_empty=False, |
| 137 | + ) |
| 138 | + |
| 139 | + assert FakeCompel.last_init_device == torch.device("cpu") |
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