Add NotImplementedError to v1 cpu runner

.gitignore

@@ -136,6 +136,7 @@ venv/
 ENV/
 env.bak/
 venv.bak/
+.envrc
 
 # Spyder project settings
 .spyderproject

tests/v1/worker/test_cpu_model_runner.py

@@ -0,0 +1,36 @@
+import pytest
+import torch
+
+from vllm.v1.worker.cpu_model_runner import CPUModelRunner
+from vllm.config import (ModelConfig, SchedulerConfig, CacheConfig,
+                         ParallelConfig, VllmConfig, DeviceConfig)
+
+DEVICE = torch.device("cpu")
+
+def get_vllm_config():
+    model_config = ModelConfig(
+        model="facebook/opt-125m",
+        tokenizer="facebook/opt-125m",
+    )
+    device_config = DeviceConfig(
+        device="cpu",
+    )
+    cache_config = CacheConfig()
+    scheduler_config = SchedulerConfig()
+    parallel_config = ParallelConfig()
+    vllm_config = VllmConfig(
+        model_config=model_config,
+        cache_config=cache_config,
+        scheduler_config=scheduler_config,
+        parallel_config=parallel_config,
+        device_config=device_config,
+    )
+    return vllm_config
+
+@pytest.fixture
+def model_runner():
+    return CPUModelRunner(get_vllm_config(), DEVICE)
+
+def test_execute_model(model_runner: CPUModelRunner):
+    with pytest.raises(NotImplementedError):
+        model_runner.execute_model(None)

vllm/v1/worker/cpu_model_runner.py

@@ -1,13 +1,15 @@
 # SPDX-License-Identifier: Apache-2.0
 from contextlib import contextmanager
-from typing import Any
+from typing import  Any, Optional, Union
 
 import torch
 
 from vllm.config import VllmConfig
 from vllm.logger import init_logger
 from vllm.model_executor.model_loader import get_model
 from vllm.v1.worker.gpu_model_runner import GPUModelRunner
+from vllm.sequence import IntermediateTensors
+from vllm.v1.outputs import  ModelRunnerOutput
 
 logger = init_logger(__name__)
 
@@ -69,6 +71,13 @@ def _init_device_properties(self) -> None:
     def _sync_device(self) -> None:
         pass
 
+    @torch.inference_mode()
+    def execute_model(
+        self,
+        scheduler_output,
+        intermediate_tensors: Optional[IntermediateTensors] = None,
+    ) -> Union[ModelRunnerOutput, IntermediateTensors]:
+        raise NotImplementedError
 
 @contextmanager
 def _set_global_compilation_settings():