Reapply [Attention] Refactor check_and_update_config (#35122)

Signed-off-by: Matthew Bonanni <mbonanni@redhat.com>

vllm/model_executor/layers/attention/mla_attention.py

@@ -323,11 +323,9 @@ class MLAAttention(nn.Module, AttentionLayerBase):
 
         if cache_config is not None:
             kv_cache_dtype = cache_config.cache_dtype
-            block_size = cache_config.block_size
             calculate_kv_scales = cache_config.calculate_kv_scales
         else:
             kv_cache_dtype = "auto"
-            block_size = 16
             calculate_kv_scales = False
         self.quant_config = quant_config
 
@@ -336,7 +334,6 @@ class MLAAttention(nn.Module, AttentionLayerBase):
             self.head_size,
             dtype,
             kv_cache_dtype,
-            block_size,
             use_mla=True,
             use_sparse=use_sparse,
             num_heads=self.num_heads,
@@ -449,17 +446,24 @@ class MLAAttention(nn.Module, AttentionLayerBase):
         )
 
         # Attributes for forward_impl method
-        self.chunked_prefill_workspace_size = (
-            MLACommonMetadataBuilder.determine_chunked_prefill_workspace_size(
-                get_current_vllm_config()
-            )
-        )
+        self._vllm_config = get_current_vllm_config()
+        self._chunked_prefill_workspace_size: int | None = None
         self._decode_concat_quant_fp8_op = _DecodeConcatQuantFP8(
             static=True,
             group_shape=GroupShape.PER_TENSOR,
             compile_native=True,
         )
 
+    @property
+    def chunked_prefill_workspace_size(self) -> int:
+        if self._chunked_prefill_workspace_size is None:
+            self._chunked_prefill_workspace_size = (
+                MLACommonMetadataBuilder.determine_chunked_prefill_workspace_size(
+                    self._vllm_config
+                )
+            )
+        return self._chunked_prefill_workspace_size
+
     def forward(
         self,
         q: torch.Tensor,