cherry-pick #1675 from 0.9.1-dev to main

Signed-off-by: 22dimensions <[email protected]>

Author: 22dimensions

examples/offline_data_parallel.py

@@ -54,17 +54,16 @@
                     --master-port=13345
 """
 
-import os
-from time import sleep
 import contextlib
 import gc
+import os
+from time import sleep
 
 import torch
-
 from vllm import LLM, SamplingParams
-from vllm.utils import get_open_port
 from vllm.distributed.parallel_state import (  # noqa E402
     destroy_distributed_environment, destroy_model_parallel)
+from vllm.utils import get_open_port
 
 os.environ["VLLM_USE_MODELSCOPE"] = "True"
 os.environ["VLLM_WORKER_MULTIPROC_METHOD"] = "spawn"

tests/ut/test_ascend_config.py

@@ -236,3 +236,90 @@ def test_check_torchair_supported(self):
         for model_type, expected_output in test_cases:
             self.assertEqual(_check_torchair_supported(model_type),
                              expected_output)
+
+    @_clean_up_ascend_config
+    def test_ascend_config_load_error(self):
+        test_vllm_config = VllmConfig()
+        # graph_batch_sizes should be list.
+        with self.assertRaises(TypeError):
+            test_vllm_config.additional_config = {
+                "torchair_graph_config": {
+                    "graph_batch_sizes": "fake_size",
+                },
+                "refresh": True
+            }
+            init_ascend_config(test_vllm_config)
+
+        # graph_batch_sizes_init should not be True when graph_batch_sizes is not empty.
+        with self.assertRaises(ValueError):
+            test_vllm_config.additional_config = {
+                "torchair_graph_config": {
+                    "graph_batch_sizes": [1, 2, 4, 8],
+                    "graph_batch_sizes_init": True,
+                },
+                "refresh": True
+            }
+            init_ascend_config(test_vllm_config)
+
+        # torchair graph only works with deepseek.
+        with self.assertRaises(NotImplementedError):
+            test_vllm_config.additional_config = {
+                "torchair_graph_config": {
+                    "enabled": True,
+                },
+                "refresh": True
+            }
+            init_ascend_config(test_vllm_config)
+        # torchair graph should not be enabled with eager mode
+        with self.assertRaises(RuntimeError):
+            test_vllm_config.additional_config = {
+                "torchair_graph_config": {
+                    "enabled": True,
+                },
+                "refresh": True
+            }
+            init_ascend_config(test_vllm_config)
+
+        # use_cached_graph should not be enabled without torchair graph mode
+        with self.assertRaises(RuntimeError):
+            test_vllm_config.additional_config = {
+                "torchair_graph_config": {
+                    "enabled": False,
+                    "use_cached_graph": True,
+                },
+                "refresh": True
+            }
+            init_ascend_config(test_vllm_config)
+
+        # graph_batch_sizes_init should not be enabled without torchair graph mode
+        with self.assertRaises(RuntimeError):
+            test_vllm_config.additional_config = {
+                "torchair_graph_config": {
+                    "enabled": False,
+                    "graph_batch_sizes_init": True,
+                },
+                "refresh": True
+            }
+            init_ascend_config(test_vllm_config)
+
+        # enable_multistream_mla should not be enabled without torchair graph mode
+        with self.assertRaises(RuntimeError):
+            test_vllm_config.additional_config = {
+                "torchair_graph_config": {
+                    "enabled": False,
+                    "enable_multistream_mla": True,
+                },
+                "refresh": True
+            }
+            init_ascend_config(test_vllm_config)
+
+        # enable_multistream_moe should not be enabled without torchair graph mode
+        with self.assertRaises(RuntimeError):
+            test_vllm_config.additional_config = {
+                "torchair_graph_config": {
+                    "enabled": False,
+                    "enable_multistream_moe": True,
+                },
+                "refresh": True
+            }
+            init_ascend_config(test_vllm_config)

vllm_ascend/ascend_config.py

@@ -76,6 +76,31 @@ def __init__(self, torchair_graph_config):
             raise ValueError(
                 "graph_batch_sizes_init is only valid when graph_batch_sizes is empty"
             )
+        if not self.enabled:
+            if self.use_cached_graph:
+                raise RuntimeError(
+                    "use_cached_graph is valid only when Torchair graph mode is enabled"
+                )
+            if self.graph_batch_sizes:
+                raise RuntimeError(
+                    "graph_batch_sizes is valid only when Torchair graph mode is enabled"
+                )
+            if self.graph_batch_sizes_init:
+                raise RuntimeError(
+                    "graph_batch_sizes_init is valid only when Torchair graph mode is enabled"
+                )
+            if self.enable_multistream_mla:
+                raise RuntimeError(
+                    "enable_multistream_mla is valid only when Torchair graph mode is enabled"
+                )
+            if self.enable_multistream_moe:
+                raise RuntimeError(
+                    "enable_multistream_moe is valid only when Torchair graph mode is enabled"
+                )
+            if self.enable_kv_nz:
+                raise RuntimeError(
+                    "enable_kv_nz is valid only when Torchair graph mode is enabled"
+                )
 
 
 class AscendSchedulerConfig:

vllm_ascend/models/deepseek_v2.py

@@ -313,7 +313,8 @@ def __init__(
         ascend_config = get_ascend_config()
         self.torchair_graph_enabled = ascend_config.torchair_graph_config.enabled
         self.enable_multistream_moe = \
-            ascend_config.torchair_graph_config.enable_multistream_moe
+            ascend_config.torchair_graph_config.enable_multistream_moe and \
+            self.torchair_graph_enabled
 
         self.gate = ReplicatedLinear(config.hidden_size,
                                      config.n_routed_experts,

vllm_ascend/ops/fused_moe.py

@@ -1253,7 +1253,8 @@ def __init__(
 
         self.torchair_graph_enabled = ascend_config.torchair_graph_config.enabled
         self.enable_multistream_moe = \
-            ascend_config.torchair_graph_config.enable_multistream_moe
+            ascend_config.torchair_graph_config.enable_multistream_moe and \
+            self.torchair_graph_enabled
 
         if self.scoring_func != "softmax" and not self.use_grouped_topk:
             raise ValueError("Only softmax scoring function is supported for "