[Refactor] remove some metadata variables in attention_v1. (#5160)

RFC: https://github.com/vllm-project/vllm-ascend/issues/4629

Reason:

The metadata data class contains an excessive number of variables. We
will inherit the metadata of the community and simultaneously remove
some variables that are no longer needed at present.

Todo:
1. remove attn_state partly.

- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c

---------

Signed-off-by: weijinqian_v1 <weijinqian@huawei.com>
Co-authored-by: weijinqian_v1 <weijinqian@huawei.com>

vllm_ascend/attention/utils.py

@@ -1,9 +1,10 @@
 from dataclasses import dataclass
+from functools import lru_cache
 from typing import Any, List, Optional
 
 import torch
 import torch.nn.functional as F
-from vllm.config import VllmConfig
+from vllm.config import VllmConfig, get_current_vllm_config
 from vllm.distributed.kv_transfer import (get_kv_transfer_group,
                                           has_kv_transfer_group,
                                           is_v1_kv_transfer_group)
@@ -26,6 +27,13 @@ def using_paged_attention(runtime_shape: int, vllm_config: VllmConfig) -> bool:
     return runtime_shape in get_ascend_config().pa_shape_list
 
 
+@lru_cache(maxsize=1)
+def enable_cp():
+    prefill_config = get_current_vllm_config().parallel_config
+    return prefill_config.prefill_context_parallel_size > 1 \
+                or prefill_config.decode_context_parallel_size > 1
+
+
 @dataclass
 # class AscendCommonLongSequenceMetadata:
 class AscendPrefillContextParallelMetadata:
@@ -66,7 +74,7 @@ class AscendCommonAttentionMetadata:
     Per-batch attention metadata, shared across layers and backends.
     AttentionMetadataBuilder instances use it to construct per-layer metadata.
 
-    For many of the tensors we keep both GPU and CPU versions.
+    For many of the tensors we keep both NPU and CPU versions.
     """
 
     query_start_loc: torch.Tensor
@@ -109,8 +117,6 @@ class AscendCommonAttentionMetadata:
 
     attn_state: Any = None
 
-    is_only_prefill: bool = False
-
     graph_pad_size: int = -1
 
     # num_input_tokens refers to total number of tokens including
@@ -120,6 +126,8 @@ class AscendCommonAttentionMetadata:
     prefill_context_parallel_metadata: Optional[
         AscendPrefillContextParallelMetadata] = None
 
+    causal: bool = True
+
     # TODO: Remove it when vLLM no longer uses this function.
     def unpadded(self, num_actual_tokens: int,
                  num_actual_reqs: int) -> "AscendCommonAttentionMetadata":
@@ -137,12 +145,12 @@ class AscendCommonAttentionMetadata:
             decode_token_per_req=self.decode_token_per_req,
             block_table_tensor=self.block_table_tensor[:num_actual_reqs],
             slot_mapping=self.slot_mapping[:num_actual_tokens],
+            causal=self.causal,
             actual_seq_lengths_q=self.actual_seq_lengths_q[:num_actual_tokens],
             positions=self.positions[:num_actual_tokens],
             attn_mask=self.attn_mask,
             spec_attn_mask=self.spec_attn_mask,
             attn_state=self.attn_state,
-            is_only_prefill=self.is_only_prefill,
             graph_pad_size=-1,  # It should be -1 when not run in fullgraph mode.
             num_input_tokens=num_actual_tokens,
             prefill_context_parallel_metadata=self.