Add more support for intel Gaudi accelerators (#2357)

python/sglang/srt/mem_cache/memory_pool.py

@@ -27,6 +27,7 @@ from typing import List, Tuple, Union
 import torch
 
 from sglang.srt.layers.radix_attention import RadixAttention
+from sglang.srt.utils import get_compiler_backend
 
 logger = logging.getLogger(__name__)
 
@@ -129,6 +130,9 @@ class BaseTokenToKVPool:
         return select_index.to(self.device, non_blocking=True)
 
     def free(self, free_index: torch.Tensor):
+        if free_index.numel() == 0:
+            return
+
         if self.is_not_in_free_group:
             self.free_slots = torch.concat((self.free_slots, free_index.cpu()))
         else:
@@ -234,7 +238,7 @@ class MHATokenToKVPool(BaseTokenToKVPool):
 
 # This compiled version is slower in the unit test
 # python3 -m unittest test_bench_serving.TestBenchServing.test_offline_throughput_non_stream_small_batch_size
-@torch.compile(dynamic=True)
+@torch.compile(dynamic=True, backend=get_compiler_backend())
 def copy_two_array(loc, dst_1, src_1, dst_2, src_2, dtype, store_dtype):
     dst_1[loc] = src_1.to(dtype).view(store_dtype)
     dst_2[loc] = src_2.to(dtype).view(store_dtype)