add dca and sparse attention support on rocm

vllm/attention/backends/dual_chunk_flash_attn.py

@@ -19,7 +19,12 @@ from vllm.attention.backends.flash_attn import (FlashAttentionBackend,
 from vllm.distributed.parallel_state import get_tensor_model_parallel_rank
 from vllm.logger import init_logger
 from vllm.utils import async_tensor_h2d
-from vllm.vllm_flash_attn import (flash_attn_varlen_func,
+from vllm.platforms import current_platform
+if not current_platform.is_rocm():
+    from vllm.vllm_flash_attn import (flash_attn_varlen_func,
+                                    flash_attn_with_kvcache, sparse_attn_func)
+else:
+    from flash_attn import (flash_attn_varlen_func,
                         flash_attn_with_kvcache, sparse_attn_func)
 
 if TYPE_CHECKING:

vllm/engine/arg_utils.py

@@ -1107,8 +1107,8 @@ class EngineArgs:
                 "Cuda graph is not supported with DualChunkFlashAttention. "
                 "To run the model in eager mode, set 'enforce_eager=True' "
                 "or use '--enforce-eager' in the CLI.")
-            assert current_platform.is_cuda(), (
-                "DualChunkFlashAttention is only supported on CUDA platform.")
+            assert current_platform.is_cuda() or current_platform.is_rocm(), (
+                "DualChunkFlashAttention is only supported on CUDA/ROCM platform.")
             assert not use_v1, (
                 "DualChunkFlashAttention is not supported on V1 engine. "
                 "To run the model in V0 engine, try set 'VLLM_USE_V1=0'")

vllm/platforms/rocm.py

@@ -297,6 +297,11 @@ class RocmPlatform(Platform):
                 logger.info_once("Using Triton backend on V1 engine.")
                 return TRITON_ATTN_VLLM_V1
         
+        if selected_backend == _Backend.DUAL_CHUNK_FLASH_ATTN:
+            logger.info("Using DualChunkFlashAttention backend.")
+            return ("vllm.attention.backends.dual_chunk_flash_attn."
+                    "DualChunkFlashAttentionBackend")
+
         if selected_backend == _Backend.ROCM_FLASH:
             if not cls.has_device_capability(90):
                 # not Instinct series GPUs.