chore: import upstream snapshot with attribution

tests/lora/test_layers_utils.py

@@ -0,0 +1,39 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+import pytest
+import torch
+from torch import nn
+
+from vllm.lora.layers.utils import _get_lora_device
+
+pytestmark = pytest.mark.skip_global_cleanup
+
+
+def _param() -> nn.Parameter:
+    return nn.Parameter(torch.empty(1), requires_grad=False)
+
+
+def test_get_lora_device_unquantized():
+    base_layer = nn.Module()
+    base_layer.weight = _param()
+    assert _get_lora_device(base_layer) == base_layer.weight.device
+
+
+def test_get_lora_device_gptq_awq():
+    base_layer = nn.Module()
+    base_layer.qweight = _param()
+    assert _get_lora_device(base_layer) == base_layer.qweight.device
+
+
+def test_get_lora_device_ark_linear():
+    base_layer = nn.Module()
+    base_layer.ark_linear = nn.Module()
+    base_layer.ark_linear.qweight = _param()
+    assert _get_lora_device(base_layer) == base_layer.ark_linear.qweight.device
+
+
+def test_get_lora_device_unsupported_raises():
+    base_layer = nn.Module()
+    with pytest.raises(ValueError, match="Unsupported base layer"):
+        _get_lora_device(base_layer)