chore: import upstream snapshot with attribution

tests/backend/patches/layers/test_set_parameter_layer.py

@@ -0,0 +1,49 @@
+import pytest
+import torch
+
+from invokeai.backend.patches.layers.set_parameter_layer import SetParameterLayer
+
+
+def test_set_parameter_layer_get_parameters():
+    orig_module = torch.nn.Linear(4, 8)
+
+    target_weight = torch.randn(8, 4)
+    layer = SetParameterLayer(param_name="weight", weight=target_weight)
+
+    params = layer.get_parameters(dict(orig_module.named_parameters(recurse=False)), weight=1.0)
+    assert len(params) == 1
+    new_weight = orig_module.weight + params["weight"]
+    assert torch.allclose(new_weight, target_weight)
+
+
+@pytest.mark.parametrize(
+    ["device"],
+    [
+        pytest.param("cuda", marks=pytest.mark.skipif(not torch.cuda.is_available(), reason="requires CUDA device")),
+        pytest.param(
+            "mps", marks=pytest.mark.skipif(not torch.backends.mps.is_available(), reason="requires MPS device")
+        ),
+    ],
+)
+def test_set_parameter_layer_to(device: str):
+    """Test moving SetParameterLayer to different device/dtype."""
+
+    target_weight = torch.randn(8, 4)
+    layer = SetParameterLayer(param_name="weight", weight=target_weight)
+
+    # SetParameterLayer should be initialized on CPU.
+    assert layer.weight.device.type == "cpu"  # type: ignore
+
+    # Move to device.
+    layer.to(device=torch.device(device))
+    assert layer.weight.device.type == device  # type: ignore
+
+
+def test_set_parameter_layer_calc_size():
+    """Test calculating parameter size of SetParameterLayer"""
+    param = torch.randn(4, 8)
+    layer = SetParameterLayer(param_name="weight", weight=param)
+
+    # Size should be number of elements * bytes per element
+    expected_size = param.nelement() * param.element_size()
+    assert layer.calc_size() == expected_size