[XPU][Graph Optimization] XPU Support CUDAGraph (#6152)

* support cuda graph

fastdeploy/model_executor/xpu_pre_and_post_process.py

@@ -105,6 +105,7 @@ def xpu_pre_process(
     seq_lens_decoder: Optional[paddle.Tensor] = None,
     is_profiling: bool = False,
     forward_meta=None,
+    use_cudagraph=False,
 ) -> XPUForwardMeta:
     """ """
     max_len = input_ids.shape[1]
@@ -152,7 +153,6 @@ def xpu_pre_process(
             cu_seqlens_k,
         ) = get_padding_offset(input_ids, cum_offsets_now, token_num, seq_lens_this_time)
 
-    share_inputs["ids_remove_padding"] = None  # set this after adjust batch
     share_inputs["cum_offsets"] = cum_offsets
     share_inputs["batch_id_per_token"] = batch_id_per_token
     share_inputs["cu_seqlens_q"] = cu_seqlens_q
@@ -221,11 +221,18 @@ def xpu_pre_process(
 
     adjusted_input = adjusted_input.squeeze(1)
 
-    share_inputs["ids_remove_padding"] = adjusted_input
+    share_inputs["ids_remove_padding"].copy_(adjusted_input, False)
     xpu_forward_meta.ids_remove_padding = adjusted_input
     # Set forward_meta.is_profiling to True to skip init_kv_signal_per_query for attention backends
     xpu_forward_meta.is_profiling = is_profiling
-    return xpu_forward_meta
+    if use_cudagraph:
+        if forward_meta is None:
+            return xpu_forward_meta
+        else:
+            forward_meta.copy_from(xpu_forward_meta)
+            return forward_meta
+    else:
+        return xpu_forward_meta
 
 
 def xpu_process_output(