[Perf] Support FP8 KV cache for Flashinfer MLA Sparse (#35891)

tools/pre_commit/generate_attention_backend_docs.py

@@ -49,6 +49,11 @@ MLA_ATTENTION_FILE = (
 # Backends to skip during doc generation
 SKIP_BACKENDS = {"CUSTOM", "TORCH_SDPA"}
 
+BACKEND_KV_DTYPE_EXCLUDES: dict[str, set[str]] = {
+    # fp8 is an alias for fp8_ds_mla for FlashMLA Sparse
+    "FLASHMLA_SPARSE": {"fp8"},
+}
+
 
 def is_relevant_file(filepath: str) -> bool:
     """Check if a file matches any of the relevant patterns."""
@@ -546,10 +551,19 @@ def analyze_backend(backend_name: str, class_path: str) -> dict[str, Any] | None
             tree, impl_class_name, "can_return_lse_for_decode", False, file_path
         )
 
+    kv_cache_dtypes = parse_kv_cache_dtypes(class_node)
+    if backend_name in BACKEND_KV_DTYPE_EXCLUDES:
+        excluded = BACKEND_KV_DTYPE_EXCLUDES[backend_name]
+        kv_cache_dtypes = ", ".join(
+            d
+            for d in (d.strip() for d in kv_cache_dtypes.split(","))
+            if d not in excluded
+        )
+
     return {
         "name": backend_name,
         "dtypes": parse_supported_dtypes(class_node),
-        "kv_cache_dtypes": parse_kv_cache_dtypes(class_node),
+        "kv_cache_dtypes": kv_cache_dtypes,
         "block_sizes": parse_block_sizes(class_node),
         "head_sizes": parse_head_sizes(class_node),
         "attn_types": parse_attention_types(class_node),