[Refactor] AttentionBuilder inherit from base class in vllm (#5916)

### What this PR does / why we need it?

This PR makes `AscendMLAMetadataBuilder` and `AscendSFAMetadataBuilder`
properly inherit from the base class `MLACommonMetadataBuilder` in vllm
by adding `super().__init__()` calls.

**Changes:**
- Add `super().__init__()` call in `AscendMLAMetadataBuilder.__init__()`
- Add `super().__init__()` call in `AscendSFAMetadataBuilder.__init__()`
- Extract `ascend_chunked_prefill_workspace_size()` to
`vllm_ascend/attention/utils.py` to avoid code duplication
- Override `determine_chunked_prefill_workspace_size()` to support
Ascend-specific 128k tokens workspace size (vs 64k in parent class)
- Update unit tests to mock parent class `__init__` for proper isolation

**Why we need it:**
- Follow proper Python inheritance patterns by calling
`super().__init__()`
- Reduce code duplication by reusing parent class initialization logic
- Better maintainability as parent class changes will be automatically
inherited

Part of issue #5463 item 10

### Does this PR introduce _any_ user-facing change?

No, this is an internal refactoring that does not change any user-facing
behavior.

Signed-off-by: lico67373 <918688502@qq.com>

vllm_ascend/attention/sfa_v1.py

@@ -20,6 +20,7 @@ from vllm_ascend.attention.attention_mask import AttentionMaskBuilder
 from vllm_ascend.attention.attention_v1 import AscendAttentionState
 from vllm_ascend.attention.mla_v1 import MAX_O_PROJ_PREFETCH_SIZE, MLAPO_MAX_SUPPORTED_TOKENS
 from vllm_ascend.attention.utils import (AscendCommonAttentionMetadata,
+                                         ascend_chunked_prefill_workspace_size,
                                          maybe_save_kv_layer_to_connector,
                                          trans_rope_weight, transdata,
                                          wait_for_kv_layer_from_connector)
@@ -131,7 +132,6 @@ class AscendSFAMetadataBuilder(MLACommonMetadataBuilder[AscendSFAMetadata]):
     understand this class
     """
 
-    # _attn_mask_builder = None
     def __init__(
         self,
         kv_cache_spec,
@@ -141,11 +141,11 @@ class AscendSFAMetadataBuilder(MLACommonMetadataBuilder[AscendSFAMetadata]):
         metadata_cls: type[AscendSFAMetadata] | None = None,
         supports_dcp_with_varlen: bool = False,
     ):
-        self.metadata_cls = (metadata_cls if metadata_cls is not None else
-                             AscendSFAMetadata)
-        self.vllm_config = vllm_config
-        self.model_config = vllm_config.model_config
-        self.device = device
+        super().__init__(
+            kv_cache_spec, layer_names, vllm_config, device,
+            metadata_cls if metadata_cls is not None else AscendSFAMetadata,
+            supports_dcp_with_varlen)
+
         self.block_size = vllm_config.cache_config.block_size
         self.max_blocks = (vllm_config.model_config.max_model_len +
                            self.block_size - 1) // self.block_size
@@ -169,6 +169,11 @@ class AscendSFAMetadataBuilder(MLACommonMetadataBuilder[AscendSFAMetadata]):
         ), "FlashComm1 is not compatible with FULL_DECODE_ONLY. Please set graph_mode to 'piecewise' or disable FlashComm1."
         self.attn_mask_builder = AttentionMaskBuilder(self.device)
 
+    @staticmethod
+    def determine_chunked_prefill_workspace_size(
+            vllm_config: VllmConfig) -> int:
+        return ascend_chunked_prefill_workspace_size(vllm_config)
+
     @classmethod
     def get_cudagraph_support(
         cls: type["AscendSFAMetadataBuilder"],