[Misc] Drop deepseek patch (#6288)

We patched deepseek before since we notice asserterror raised by
transformers. Now due to transformers upgrade, the patch looks useless
now. Let's remove it.

- vLLM version: v0.14.1
- vLLM main:
dc917cceb8

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>

vllm_ascend/patch/__init__.py

@@ -42,7 +42,7 @@
 #    Future Plan:
 #       Find a better way to support tensor alignment for 310p without this patch.
 #
-# ** 3. File: platform/patch_mamba_config.py**
+# ** 2. File: platform/patch_mamba_config.py**
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 #   1. `vllm.model_executor.models.config.HybridAttentionMambaModelConfig.verify_and_update_config`
 #    Why:
@@ -54,7 +54,7 @@
 #    Future Plan:
 #       Remove this patch when vLLM merges the PR.
 #
-# ** 4. File: platform/patch_multiproc_executor.py**
+# ** 3. File: platform/patch_multiproc_executor.py**
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 #   1. `vllm.v1.executor.multiproc_executor.MultiprocExecutor`
 #    Why:
@@ -67,7 +67,7 @@
 #    Future Plan:
 #       Remove this patch when vLLM fix the issue.
 #
-# ** 5. File: platform/patch_sched_yield.py**
+# ** 4. File: platform/patch_sched_yield.py**
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 #   1. `vllm.distributed.utils.USE_SCHED_YIELD`
 #    Why:
@@ -79,7 +79,7 @@
 #    Future Plan:
 #       Remove this patch when vLLM merge the PR.
 #
-# ** 6. File: platform/patch_balance_schedule.py**
+# ** 5. File: platform/patch_balance_schedule.py**
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 #   1. `vllm.v1.engine.core.EngineCoreProc.run_engine_core`
 #      `vllm.v1.core.sched.scheduler.Scheduler`
@@ -97,20 +97,7 @@
 # * Worker Patch:
 # ===============
 #
-# ** 1. File: worker/patch_deepseek.py **
+# ** 1. File: worker/patch_distributed.py **
-# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-#   1. `DeepseekV2Model.forward`
-#    Why:
-#       getattr(self.config, "llama_4_scaling", None) will raise AttributeError
-#       on npu with graph mode.
-#    How：
-#       catch the AttributeError and set llama_4_scaling to None.
-#    Related PR (if no, explain why):
-#       No, this is a bug in vLLM Ascend
-#    Future Plan:
-#       Find the root cause of this bug and fix it in vLLM Ascend.
-#
-# ** 2. File: worker/patch_distributed.py **
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 #   1. `vllm.distributed.parallel_state.GroupCoordinator`
 #    Why:
@@ -125,7 +112,7 @@
 #       Remove this patch when the refactor of all2all manager is done.
 #       Remove this patch when vLLM support all_reduce as customop.
 #
-# ** 3. File: worker/patch_minicpm.py **
+# ** 2. File: worker/patch_minicpm.py **
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 #   1. `vllm.model_executor.models.minicpm.MiniCPMAttention.forward`
 #    Why:
@@ -139,7 +126,7 @@
 #    Future Plan:
 #       Keep this patch in vllm-ascend.
 #
-# ** 4. File: worker/patch_multimodal_merge.py**
+# ** 3. File: worker/patch_multimodal_merge.py**
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 #   1. `vllm.model_executor.models.utils._merge_multimodal_embeddings`
 #    Why:
@@ -151,7 +138,7 @@
 #    Future Plan:
 #       Identify this pattern in torch-npu and remove this patch.
 #
-# ** 5. File: worker/patch_roberta.py **
+# ** 4. File: worker/patch_roberta.py **
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 #   1. `vllm.model_executor.models.bert `
 #    Why:
@@ -163,7 +150,7 @@
 #    Future Plan:
 #       Revert this when CANN support shift aclnn operation
 #
-# ** 6. File: worker/patch_triton.py**
+# ** 5. File: worker/patch_triton.py**
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 #   1. `vllm.model_executor.layers.mamba.ops`, `vllm.model_executor.layers.fla.ops`,
 #      `vllm.v1.worker.gpu.sample.gumbel.gumbel_sample`
@@ -176,7 +163,7 @@
 #    Future Plan:
 #       Remove this patch when vLLM support the dispatch function.
 #
-# ** 7. File: worker/patch_qwen3_next_mtp.py**
+# ** 6. File: worker/patch_qwen3_next_mtp.py**
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 #   1. `vllm.v1.worker.utils.bind_kv_cache`
 #    Why:
@@ -189,7 +176,7 @@
 #    Future Plan:
 #       Remove this patch after discussing with vllm community and adapting bind_kv_cache to npu.
 #
-# ** 8. File: worker/patch_module.py**
+# ** 7. File: worker/patch_module.py**
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 #   1. `vllm.v1.attention.backends.gdn_attn.torch.argsort`
 #    Why:
@@ -205,7 +192,7 @@
 #       Remove this patch when bool is supported in 'torch.argsort' func of npu.
 #       Make 'torch.argsort' in `vllm.v1.attention.backends.gdn_attn` be stable.
 #
-# ** 9. File: worker/patch_rejection_sampler.py**
+# ** 8. File: worker/patch_rejection_sampler.py**
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 #   1. `vllm.v1.sample.rejection_sampler`
 #    Why:
@@ -221,7 +208,7 @@
 #           to override them, then delete the patch file `worker/patch_rejection_sampler.py`.
 #       2. make these functions as costom op, then remove AscendRejectionSampler
 #
-# ** 10.File: worker/patch_qwen3_next.py**
+# ** 9.File: worker/patch_qwen3_next.py**
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 #   1. `vllm.model_executor.models.qwen3_next.Qwen3NextGatedDeltaNet.forward`
 #    Why:
@@ -233,7 +220,7 @@
 #    Future Plan:
 #       Remove this patch when vLLM support these operators.
 #
-# ** 11. File: worker/patch_qwen3_next.py**
+# ** 10. File: worker/patch_qwen3_next.py**
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 #   1. `vllm.model_executor.models.qwen3_next.Qwen3NextGatedDeltaNet._forward_core`
 #    Why:
@@ -255,7 +242,7 @@
 #    Future Plan:
 #       Remove this patch when vLLM support these operators.
 #
-# ** 12. File: worker/patch_v2_eagle.py**
+# ** 11. File: worker/patch_v2_eagle.py**
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 #   1. `vllm.v1.worker.gpu.spec_decode.eagle.EagleSpeculator.propose`
 #    Why:
@@ -267,7 +254,7 @@
 #    Future Plan:
 #       Remove this patch when cann fix the gather bug.
 #
-# ** 13. File: worker/patch_unquantized_gemm.py**
+# ** 12. File: worker/patch_unquantized_gemm.py**
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 #   1. `vllm.model_executor.layers.utils.default_unquantized_gemm`
 #    Why:

vllm_ascend/patch/worker/__init__.py

@@ -25,7 +25,6 @@ import vllm_ascend.patch.platform.patch_sched_yield  # noqa
 import vllm_ascend.patch.worker.patch_unquantized_gemm  # noqa
 import vllm_ascend.patch.worker.patch_bert  # noqa
 import vllm_ascend.patch.worker.patch_distributed  # noqa
-import vllm_ascend.patch.worker.patch_deepseek  # noqa
 import vllm_ascend.patch.worker.patch_multimodal_merge  # noqa
 import vllm_ascend.patch.worker.patch_minicpm  # noqa
 import vllm_ascend.patch.worker.patch_rope  # noqa

vllm_ascend/patch/worker/patch_deepseek.py

@@ -1,60 +0,0 @@
-from itertools import islice
-
-import torch
-from vllm.distributed import get_pp_group
-from vllm.model_executor.models.deepseek_v2 import (DeepseekV2Model,
-                                                    _get_llama_4_scaling)
-from vllm.sequence import IntermediateTensors
-
-
-def forward(
-    self,
-    input_ids,
-    positions,
-    intermediate_tensors,
-    inputs_embeds,
-):
-    if get_pp_group().is_first_rank:
-        if inputs_embeds is not None:
-            hidden_states = inputs_embeds
-        else:
-            hidden_states = self.embed_input_ids(input_ids)
-        residual = None
-    else:
-        assert intermediate_tensors is not None
-        hidden_states = intermediate_tensors["hidden_states"]
-        residual = intermediate_tensors["residual"]
-
-    # Compute llama 4 scaling once per forward pass if enabled
-    # Note(wxy): This is a hack fix to avoid graph mode error for torch 2.8
-    # We'll find a better way to remove this patch.
-    try:
-        llama_4_scaling_config = getattr(self.config, "llama_4_scaling")
-    except AttributeError:
-        llama_4_scaling_config = None
-    llama_4_scaling: torch.Tensor | None
-    if llama_4_scaling_config is not None:
-        llama_4_scaling = _get_llama_4_scaling(
-            original_max_position_embeddings=llama_4_scaling_config[
-                "original_max_position_embeddings"],
-            scaling_beta=llama_4_scaling_config["beta"],
-            positions=positions,
-        )
-    else:
-        llama_4_scaling = None
-
-    for layer in islice(self.layers, self.start_layer, self.end_layer):
-        hidden_states, residual = layer(positions, hidden_states, residual,
-                                        llama_4_scaling)
-
-    if not get_pp_group().is_last_rank:
-        return IntermediateTensors({
-            "hidden_states": hidden_states,
-            "residual": residual
-        })
-
-    hidden_states, _ = self.norm(hidden_states, residual)
-    return hidden_states
-
-
-DeepseekV2Model.forward = forward