[SpecDecode] Support FlashInfer in DraftModelRunner

vllm/spec_decode/draft_model_runner.py

@@ -11,6 +11,17 @@
     from vllm.attention.backends.rocm_flash_attn import (
         ROCmFlashAttentionMetadata as FlashAttentionMetadata)
 
+try:
+    from flashinfer import BatchDecodeWithPagedKVCacheWrapper
+    from flashinfer.decode import CUDAGraphBatchDecodeWithPagedKVCacheWrapper
+    from flashinfer.prefill import BatchPrefillWithPagedKVCacheWrapper
+    FLASHINFER_WORKSPACE_BUFFER_SIZE = 256 * 1024 * 1024
+except ImportError:
+    BatchDecodeWithPagedKVCacheWrapper = None
+    CUDAGraphBatchDecodeWithPagedKVCacheWrapper = None
+    BatchPrefillWithPagedKVCacheWrapper = None
+    FLASHINFER_WORKSPACE_BUFFER_SIZE = 0
+
 from vllm.config import (CacheConfig, DeviceConfig, LoadConfig, LoRAConfig,
                          ModelConfig, MultiModalConfig, ParallelConfig,
                          PromptAdapterConfig, SchedulerConfig)
@@ -79,6 +90,11 @@ def __init__(
             return_hidden_states=return_hidden_states,
         )
 
+        self.flashinfer_decode_workspace_buffer = None
+        self.flashinfer_decode_wrapper = None
+        self.flashinfer_prefill_workspace_buffer = None
+        self.flashinfer_prefill_wrapper = None
+
     def _update_flash_attn_metadata(self, attn_metadata, num_seqs,
                                     num_queries):
         assert isinstance(attn_metadata, FlashAttentionMetadata)
@@ -286,6 +302,37 @@ def execute_model(
                     model_input.prompt_adapter_requests,
                     model_input.prompt_adapter_mapping)
 
+            if self.attn_backend.get_name() == "flashinfer":
+                assert model_input.attn_metadata is not None
+                assert model_input.input_tokens is not None
+                if self.flashinfer_decode_workspace_buffer is None:
+                    self.flashinfer_decode_workspace_buffer = torch.empty(
+                        FLASHINFER_WORKSPACE_BUFFER_SIZE,
+                        dtype=torch.uint8,
+                        device=self.device)
+                    self.flashinfer_decode_wrapper = \
+                        BatchDecodeWithPagedKVCacheWrapper(
+                        self.flashinfer_decode_workspace_buffer, "NHD")
+                    self.flashinfer_prefill_workspace_buffer = torch.empty(
+                        FLASHINFER_WORKSPACE_BUFFER_SIZE,
+                        dtype=torch.uint8,
+                        device=self.device)
+                    self.flashinfer_prefill_wrapper = \
+                        BatchPrefillWithPagedKVCacheWrapper(
+                        self.flashinfer_prefill_workspace_buffer, "NHD")
+
+                model_input.attn_metadata.prefill_wrapper = \
+                    self.flashinfer_prefill_wrapper
+                if model_input.attn_metadata.use_cuda_graph:
+                    batch_size = model_input.input_tokens.shape[0]
+                    model_input.attn_metadata.decode_wrapper = \
+                        self.graph_runners[model_input.
+                        virtual_engine][batch_size].flashinfer_decode_wrapper
+                else:
+                    model_input.attn_metadata.decode_wrapper = \
+                        self.flashinfer_decode_wrapper
+                model_input.attn_metadata.begin_forward()
+
         # Detect exec mode
         assert model_input.attn_metadata is not None
         use_cuda_graph = False