[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/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