diff --git a/vllm/worker/hpu_model_runner.py b/vllm/worker/hpu_model_runner.py
index f2875194e93a0..4d717858eddb6 100644
--- a/vllm/worker/hpu_model_runner.py
+++ b/vllm/worker/hpu_model_runner.py
@@ -317,18 +317,19 @@ def _set_block_mapping(self, metadata, batch_size, device, dtype):
         mask = mask >= metadata.block_usage.unsqueeze(-1)
         attn_bias = (torch.zeros_like(mask, dtype=dtype).masked_fill_(
             mask, -math.inf))
-        if is_fake_hpu():
-            # Unfortunately one_hot on CPU doesn't handle
-            # out of bounds classes. We need to mask those
-            # values manually
-            oob_values = metadata.block_mapping.lt(0)
-            block_mapping = metadata.block_mapping.masked_fill(oob_values, 0)
-            block_mapping = torch.nn.functional.one_hot(block_mapping,
+
+        if not is_fake_hpu() and htorch.utils.internal.is_lazy():
+            block_mapping = torch.nn.functional.one_hot(metadata.block_mapping,
                                                         num_classes=batch_size)
-            block_mapping.masked_fill_(oob_values.unsqueeze(-1), 0)
         else:
-            block_mapping = torch.nn.functional.one_hot(metadata.block_mapping,
+            # Unfortunately one_hot on CPU/torch.compile mode/eager mode
+            # doesn't handle out of bounds classes,
+            # so we convert all negative values to 0.
+            block_mapping = torch.nn.functional.relu(metadata.block_mapping)
+            block_mapping = torch.nn.functional.one_hot(block_mapping,
                                                         num_classes=batch_size)
+            oob_values = metadata.block_mapping.lt(0)
+            block_mapping.masked_fill_(oob_values.unsqueeze(-1), 0)
         block_mapping = block_mapping.to(dtype)
         metadata = metadata._replace(block_mapping=block_mapping,
                                      attn_bias=attn_bias)