[Misc] format patch to make the code clear

tests/singlecard/spec_decode/test_spec_decode_worker.py

@@ -589,7 +589,6 @@ def test_empty_input_batch(k: int, batch_size: int,
 
 @pytest.mark.parametrize("acceptance_sampler_method",
                          ["rejection_sampler", "typical_acceptance_sampler"])
-@pytest.mark.skip_global_cleanup
 def test_init_device(acceptance_sampler_method: str):
     """Verify SpecDecodeWorker invokes proposer/scorer worker init_device, as
     well as other GPU initialization.
@@ -646,7 +645,6 @@ def test_initialize_cache(acceptance_sampler_method):
 @pytest.mark.parametrize('draft_kv_size_bytes', [0, 2 * 2 * 768, 2 * 2 * 4096])
 @pytest.mark.parametrize("acceptance_sampler_method",
                          ["rejection_sampler", "typical_acceptance_sampler"])
-@pytest.mark.skip_global_cleanup
 def test_determine_num_available_blocks(available_gpu_blocks: int,
                                         available_cpu_blocks: int,
                                         target_cache_block_size_bytes: int,
@@ -685,7 +683,6 @@ def test_determine_num_available_blocks(available_gpu_blocks: int,
 @pytest.mark.parametrize('target_cache_block_size_bytes',
                          [2 * 2 * 4096, 2 * 2 * 8192])
 @pytest.mark.parametrize('draft_kv_size_bytes', [0, 2 * 2 * 768, 2 * 2 * 4096])
-@pytest.mark.skip_global_cleanup
 def test_split_num_cache_blocks_evenly(available_gpu_blocks: int,
                                        target_cache_block_size_bytes: int,
                                        draft_kv_size_bytes: int):

vllm_ascend/__init__.py

@@ -18,14 +18,12 @@
 
 def register():
     """Register the NPU platform."""
-
     return "vllm_ascend.platform.NPUPlatform"
 
 
 def register_model():
     # fix pytorch schema check error, remove this line after pytorch
     # is upgraded to 2.7.0
     import vllm_ascend.patch.worker.patch_common.patch_utils  # noqa: F401
-
-    from .models import register_model
+    from vllm_ascend.models import register_model
     register_model()

vllm_ascend/models/__init__.py

@@ -2,12 +2,15 @@
 
 
 def register_model():
-    from .deepseek_mtp import CustomDeepSeekMTP  # noqa: F401
-    from .deepseek_v2 import CustomDeepseekV2ForCausalLM  # noqa: F401
-    from .deepseek_v2 import CustomDeepseekV3ForCausalLM  # noqa: F401
-    from .qwen2_5_vl import \
+    from vllm_ascend.models.deepseek_mtp import CustomDeepSeekMTP  # noqa: F401
+    from vllm_ascend.models.deepseek_v2 import \
+        CustomDeepseekV2ForCausalLM  # noqa: F401
+    from vllm_ascend.models.deepseek_v2 import \
+        CustomDeepseekV3ForCausalLM  # noqa: F401
+    from vllm_ascend.models.qwen2_5_vl import \
         AscendQwen2_5_VLForConditionalGeneration  # noqa: F401
-    from .qwen2_vl import AscendQwen2VLForConditionalGeneration  # noqa: F401
+    from vllm_ascend.models.qwen2_vl import \
+        AscendQwen2VLForConditionalGeneration  # noqa: F401
 
     ModelRegistry.register_model(
         "DeepSeekMTPModel",

vllm_ascend/models/deepseek_mtp.py

@@ -37,7 +37,7 @@
 from vllm.model_executor.sampling_metadata import SamplingMetadata
 from vllm.sequence import IntermediateTensors
 
-from .deepseek_v2 import CustomDeepseekV2DecoderLayer
+from vllm_ascend.models.deepseek_v2 import CustomDeepseekV2DecoderLayer
 
 
 class CustomDeepSeekMultiTokenPredictorLayer(DeepSeekMultiTokenPredictorLayer):

vllm_ascend/patch/__init__.py

@@ -88,16 +88,39 @@
 #
 # * Worker Patch:
 # ===============
+# ** File: worker/patch_common/patch_utils.py **
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+#   1. `vllm.utils.direct_register_custom_op`
+#    Why:
+#       direct_register_custom_op requires pytorch version >= 2.7.0,
+#       but vllm-ascend only support pytorch version 2.5.1
+#    How：
+#       Convert annotation type to typing type for 2.5.1 backward compatibility
+#    Related PR (if no, explain why):
+#       No related PR, it's the change in vllm-ascend.
+#    Future Plan:
+#       Update pytorch and torch-npu to 2.7.0 in the future.
+# ** File: worker/patch_common/patch_cache_engine.py **
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+#   1. `vllm.worker.cache_engine.CacheEngine._allocate_kv_cache`
+#    Why:
+#       Add graph_mode optimization for kv cache allocation.
+#    How：
+#       If graph_mode is enabled, add layer_kv_cache_nope and layer_kv_cache_pe to the kv_cache.
+#    Related PR (if no, explain why):
+#       Need a PR to vllm to fix the issue.
+#    Future Plan:
+#       Revert it when the related pr is merged in vllm.
 # ** File: worker/patch_common/patch_metrics.py **
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-#   1. `vllm.spec_decode.metrics.AsyncMetricsCollector.maybe_collect_rejsample_metrics`
+#   1. `vllm.spec_decode.metrics.AsyncMetricsCollector._copy_rejsample_metrics_async`
 #    Why:
 #       There are cuda hard code (current_platform.is_cuda_alike()) in
-#       `AsyncMetricsCollector.maybe_collect_rejsample_metrics`
+#       `AsyncMetricsCollector._copy_rejsample_metrics_async`
 #    How：
 #       Change to use `current_platform.Event` to determine whether to return None
-#    Related PR (if no, explain why): 1. refused by vllm. 2. vllm doesn't support 3. prepare to submit....
-#       https://github.com/vllm-project/vllm/pull/14411
+#    Related PR (if no, explain why):
+#       Need a PR to vllm to fix the issue.
 #    Future Plan:
 #       Revert it when the related pr is merged in vllm.
 #
@@ -110,7 +133,7 @@
 #       However float32 is not supported in cann rope op, thus we keep this patch
 #    How：
 #       Removed the dtype convert operations in forward
-#    Related PR (if no, explain why): 1. refused by vllm. 2. vllm doesn't support 3. prepare to submit....
+#    Related PR (if no, explain why):
 #       NO, only for npu due to rope op.
 #    Future Plan:
 #       Keep this patch in vllm-ascend.
@@ -126,7 +149,7 @@
 #       - support attention metadata register to the set supported spec decode
 #       - offer a api in platform to determine whether spec decode is supported,
 #         and deprecate is_cuda_alike in it.
-#    Related PR (if no, explain why): 1. refused by vllm. 2. vllm doesn't support 3. prepare to submit....
+#    Related PR (if no, explain why):
 #       - https://github.com/vllm-project/vllm/pull/15195
 #       - https://github.com/vllm-project/vllm-ascend/pull/395
 #    Future Plan:
@@ -138,7 +161,7 @@
 #       vLLM `Remove Sampler from Model Code` so vllm-ascend needs adapt to this change.
 #    How：
 #       Use vLLM 0.8.4 method to patch it.
-#    Related PR (if no, explain why): 1. refused by vllm. 2. vllm doesn't support 3. prepare to submit....
+#    Related PR (if no, explain why):
 #       - https://github.com/vllm-project/vllm/pull/15195
 #       - https://github.com/vllm-project/vllm-ascend/pull/395
 #    Future Plan:
@@ -153,7 +176,7 @@
 #           `FlashAttentionMetadata`
 #    How：
 #       ditto
-#    Related PR (if no, explain why): 1. refused by vllm. 2. vllm doesn't support 3. prepare to submit....
+#    Related PR (if no, explain why):
 #       - https://github.com/vllm-project/vllm/pull/15195
 #       - https://github.com/vllm-project/vllm-ascend/pull/395
 #    Future Plan:

vllm_ascend/patch/worker/patch_common/__init__.py

@@ -18,6 +18,7 @@
 # patch_utils should be the first import, because it will be used by other
 # patch files.
 import vllm_ascend.patch.worker.patch_common.patch_utils  # noqa isort:skip
+import vllm_ascend.patch.worker.patch_common.patch_cache_engine  # noqa
 import vllm_ascend.patch.worker.patch_common.patch_distributed  # noqa
 import vllm_ascend.patch.worker.patch_common.patch_metrics  # noqa
 import vllm_ascend.patch.worker.patch_common.patch_minicpm  # noqa

vllm_ascend/worker/cache_engine.py → vllm_ascend/patch/worker/patch_common/patch_cache_engine.py

@@ -1,7 +1,5 @@
 #
 # Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
-# This file is a part of the vllm-ascend project.
-# Adapted from vllm-project/vllm/vllm/worker/model_runner.py
 # Copyright 2023 The vLLM team.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");

vllm_ascend/patch/worker/patch_common/patch_metrics.py

@@ -15,13 +15,9 @@
 # limitations under the License.
 #
 
-from typing import Callable
-
 import torch
 from vllm.spec_decode.metrics import AsyncMetricsCollector
 
-Timer = Callable[[], float]
-
 
 def _copy_rejsample_metrics_async(self) -> torch.npu.Event:
     """

vllm_ascend/quantization/quant_config.py

@@ -38,8 +38,7 @@
 from vllm.model_executor.utils import set_weight_attrs
 
 from vllm_ascend.ops.fused_moe import AscendUnquantizedFusedMoEMethod
-
-from .quantizer import AscendQuantizer
+from vllm_ascend.quantization.quantizer import AscendQuantizer
 
 
 @register_quantization_config("ascend")

vllm_ascend/quantization/quantizer.py

@@ -22,11 +22,12 @@
 
 from vllm.logger import logger
 
-from .func_wrapper import (wrapper_load_model, wrapper_rmsnorm_forward_oot,
-                           wrapper_rmsnorm_init)
-from .w8a8 import AscendW8A8LinearMethod
-from .w8a8_dynamic import (AscendW8A8DynamicFusedMoEMethod,
-                           AscendW8A8DynamicLinearMethod)
+from vllm_ascend.quantization.func_wrapper import (wrapper_load_model,
+                                                   wrapper_rmsnorm_forward_oot,
+                                                   wrapper_rmsnorm_init)
+from vllm_ascend.quantization.w8a8 import AscendW8A8LinearMethod
+from vllm_ascend.quantization.w8a8_dynamic import (
+    AscendW8A8DynamicFusedMoEMethod, AscendW8A8DynamicLinearMethod)
 
 CUSTOMIZED_QUANTIZER_TYPE: List[str] = []
 

vllm_ascend/utils.py

@@ -24,7 +24,7 @@
 from packaging.version import InvalidVersion, Version
 from vllm.logger import logger
 
-import vllm_ascend.envs as envs
+from vllm_ascend import envs
 
 if TYPE_CHECKING:
     from vllm.config import VllmConfig

vllm_ascend/worker/__init__.py

@@ -14,4 +14,3 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 #
-import vllm_ascend.worker.cache_engine  # noqa