[v1] reduce graph capture time for piecewise cudagraph (#10059)

Signed-off-by: youkaichao <youkaichao@gmail.com>

vllm/compilation/backends.py

 import copy
 import dataclasses
 import operator
+from contextlib import ExitStack
 from typing import Any, Callable, Dict, List, Optional, Set, Tuple, Union
+from unittest.mock import patch
 
 import torch
 import torch.fx as fx
@@ -503,6 +505,18 @@ class PiecewiseBackend:
             entry.input_addresses = input_addresses
             cudagraph = torch.cuda.CUDAGraph()
 
+            with ExitStack() as stack:
+                if not self.is_first_graph:
+                    # during every model forward, we will capture
+                    # many pieces of cudagraphs (roughly one per layer).
+                    # running gc again and again across layers will
+                    # make the cudagraph capture very slow.
+                    # therefore, we only run gc for the first graph,
+                    # and disable gc for the rest of the graphs.
+                    stack.enter_context(patch("gc.collect", lambda: None))
+                    stack.enter_context(
+                        patch("torch.cuda.empty_cache", lambda: None))
+
                 # mind-exploding: carefully manage the reference and memory.
                 with torch.cuda.graph(cudagraph, pool=self.graph_pool):
                     # `output` is managed by pytorch's cudagraph pool