[v1] AttentionMetadata for each layer (#17394)

Signed-off-by: Chen Zhang <zhangch99@outlook.com>

vllm/v1/attention/backends/flashinfer.py

@@ -18,6 +18,7 @@ from vllm.config import (VllmConfig, get_current_vllm_config,
                          get_layers_from_vllm_config)
 from vllm.logger import init_logger
 from vllm.v1.attention.backends.flash_attn import use_cascade_attention
+from vllm.v1.attention.backends.utils import CommonAttentionMetadata
 
 if TYPE_CHECKING:
     from vllm.v1.core.sched.output import SchedulerOutput
@@ -394,16 +395,15 @@ class FlashInferMetadataBuilder:
                 )
 
     def build(self, num_reqs: int, num_actual_tokens: int, max_query_len: int,
-              common_prefix_len: int):
+              common_prefix_len: int,
+              common_attn_metadata: CommonAttentionMetadata):
         assert self._num_decodes + self._num_prefills == num_reqs
         assert (self._num_decode_tokens +
                 self._num_prefill_tokens == num_actual_tokens)
         page_size = self.runner.block_size
         device = self.runner.device
-        qo_indptr = self.runner.query_start_loc_cpu[:num_reqs + 1].to(
-            self.runner.device, non_blocking=True)
-        seq_lens = self.runner.seq_lens_cpu[:num_reqs].to(self.runner.device,
-                                                          non_blocking=True)
+        qo_indptr = common_attn_metadata.query_start_loc
+        seq_lens = common_attn_metadata.seq_lens
         block_table = (
             self.runner.input_batch.block_table.get_device_tensor()[:num_reqs])
         slot_mapping = self.runner.slot_mapping_cpu[:num_actual_tokens].to(