[Bugfix] consider related env vars for torch.compiled cache hash (#14953)

Signed-off-by: DefTruth <31974251+DefTruth@users.noreply.github.com>

vllm/compilation/backends.py

@@ -357,6 +357,11 @@ class VllmBackend:
             # graph.
 
             factors = []
+            # 0. factors come from the env, for example, The values of
+            # VLLM_PP_LAYER_PARTITION will affects the computation graph.
+            env_hash = envs.compute_hash()
+            factors.append(env_hash)
+
             # 1. factors come from the vllm_config (it mainly summarizes how the
             #    model is created)
             config_hash = vllm_config.compute_hash()

vllm/envs.py

 # SPDX-License-Identifier: Apache-2.0
 
+import hashlib
 import os
 import tempfile
 from typing import TYPE_CHECKING, Any, Callable, Optional
@@ -651,3 +652,43 @@ def set_vllm_use_v1(use_v1: bool):
             "explicitly by the user. Please raise this as a Github "
             "Issue and explicitly set VLLM_USE_V1=0 or 1.")
     os.environ["VLLM_USE_V1"] = "1" if use_v1 else "0"
+
+
+def compute_hash() -> str:
+    """
+    WARNING: Whenever a new key is added to this environment
+    variables, ensure that it is included in the factors list if
+    it affects the computation graph. For example, different values
+    of VLLM_PP_LAYER_PARTITION will generate different computation
+    graphs, so it is included in the factors list. The env vars that 
+    affect the choice of different kernels or attention backends should
+    also be included in the factors list.
+    """
+    factors: list[Any] = []
+
+    # summarize environment variables
+    def factorize(name: str):
+        if __getattr__(name):
+            factors.append(__getattr__(name))
+        else:
+            factors.append("None")
+
+    # The values of envs may affects the computation graph.
+    # TODO(DefTruth): hash all environment variables?
+    # for key in environment_variables:
+    #     factorize(key)
+    environment_variables_to_hash = [
+        "VLLM_PP_LAYER_PARTITION",
+        "VLLM_MLA_DISABLE",
+        "VLLM_USE_TRITON_FLASH_ATTN",
+        "VLLM_USE_TRITON_AWQ",
+        "VLLM_DP_RANK",
+        "VLLM_DP_SIZE",
+    ]
+    for key in environment_variables_to_hash:
+        if key in environment_variables:
+            factorize(key)
+
+    hash_str = hashlib.md5(str(factors).encode()).hexdigest()
+
+    return hash_str