Categorize tests/kernels/ based on kernel type (#16799)

Signed-off-by: mgoin <mgoin64@gmail.com>

tests/kernels/core/test_uva.py

@@ -0,0 +1,61 @@
+# SPDX-License-Identifier: Apache-2.0
+import pytest
+import torch
+
+from vllm.utils import get_cuda_view_from_cpu_tensor, is_uva_available
+
+CUDA_DEVICES = [
+    f"cuda:{i}" for i in range(1 if torch.cuda.device_count() == 1 else 2)
+]
+
+
+@pytest.mark.skipif(not is_uva_available(), reason="UVA is not available.")
+@pytest.mark.parametrize("device", CUDA_DEVICES)
+def test_cpu_write(device):
+    torch.set_default_device(device)
+    cpu_tensor = torch.zeros(10,
+                             10,
+                             device="cpu",
+                             pin_memory=True,
+                             dtype=torch.int32)
+    cuda_view = get_cuda_view_from_cpu_tensor(cpu_tensor)
+    assert cuda_view.device.type == "cuda"
+
+    assert cuda_view[0, 0] == 0
+    assert cuda_view[2, 3] == 0
+    assert cuda_view[4, 5] == 0
+
+    cpu_tensor[0, 0] = 1
+    cpu_tensor[2, 3] = 2
+    cpu_tensor[4, 5] = -1
+
+    cuda_view.mul_(2)
+    assert cuda_view[0, 0] == 2
+    assert cuda_view[2, 3] == 4
+    assert cuda_view[4, 5] == -2
+
+
+@pytest.mark.skipif(not is_uva_available(), reason="UVA is not available.")
+@pytest.mark.parametrize("device", CUDA_DEVICES)
+def test_gpu_write(device):
+    torch.set_default_device(device)
+    cpu_tensor = torch.zeros(10,
+                             10,
+                             device="cpu",
+                             pin_memory=True,
+                             dtype=torch.int32)
+    cuda_view = get_cuda_view_from_cpu_tensor(cpu_tensor)
+    assert cuda_view.device.type == "cuda"
+
+    assert cuda_view[0, 0] == 0
+    assert cuda_view[2, 3] == 0
+    assert cuda_view[4, 5] == 0
+
+    cuda_view[0, 0] = 1
+    cuda_view[2, 3] = 2
+    cuda_view[4, 5] = -1
+    cuda_view.mul_(2)
+
+    assert cpu_tensor[0, 0] == 2
+    assert cpu_tensor[2, 3] == 4
+    assert cpu_tensor[4, 5] == -2