[Core] Use CpuGpuBuffer for block table tensors (#24795)

Signed-off-by: Nick Hill <nhill@redhat.com>

tests/v1/worker/test_gpu_input_batch.py

@@ -15,6 +15,7 @@ from vllm.utils import is_pin_memory_available, make_tensor_with_pad
 from vllm.v1.pool.metadata import PoolingMetadata
 from vllm.v1.sample.logits_processor import LogitsProcessors
 from vllm.v1.sample.metadata import SamplingMetadata
+from vllm.v1.utils import CpuGpuBuffer
 from vllm.v1.worker.block_table import BlockTable, MultiGroupBlockTable
 from vllm.v1.worker.gpu_input_batch import CachedRequestState, InputBatch
 
@@ -45,7 +46,7 @@ def _compare_objs(obj1,
 
         is_same = False
         if isinstance(a, torch.Tensor):
-            if (a.numel() == 0 or b.numel() == 0):
+            if a.numel() == 0 or b.numel() == 0:
                 is_same = (a.numel() == 0 and b.numel() == 0)
             elif torch.allclose(a, b):
                 is_same = True
@@ -61,6 +62,8 @@ def _compare_objs(obj1,
             is_same = True  # if we make it here must be same
         elif a == b:
             is_same = True
+        elif isinstance(a, CpuGpuBuffer):
+            is_same = np.allclose(a.np, b.np) and torch.allclose(a.gpu, b.gpu)
         assert is_same, f"Attribute {attr_name} is different"\
             f" in {obj1} and {obj2}: {a} != {b}"