port deepseekv2 and mtp to main branch (#429)

### What this PR does / why we need it?
This PR ports all the deepseek graph mode code and mtp code from v0.7.3
to the main branch
---------

Signed-off-by: SidaoY <1024863041@qq.com>
Signed-off-by: linfeng-yuan <1102311262@qq.com>
Signed-off-by: Yizhou Liu <liuyizhou5@h-partners.com>
Signed-off-by: mengwei805 <mengwei25@huawei.com>
Signed-off-by: libaokui <libaokui@huawei.com>
Signed-off-by: q00832892 <qiaoyang19@huawei.com>
Signed-off-by: ganyi <pleaplusone.gy@gmail.com>
Co-authored-by: SidaoY <1024863041@qq.com>
Co-authored-by: linfeng-yuan <1102311262@qq.com>
Co-authored-by: Yizhou Liu <liuyizhou5@h-partners.com>
Co-authored-by: mengwei805 <mengwei25@huawei.com>
Co-authored-by: libaokui <libaokui@huawei.com>

examples/dp_offline/data_parallel.py

@@ -0,0 +1,86 @@
+#
+# 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/examples/offline_inference/data_parallel.py
+# SPDX-License-Identifier: Apache-2.0
+# usage:
+# python examples/offline_inference_data_parallel.py
+# we need to have a launcher to create multiple data parallel
+# ranks. And each rank will create a vLLM instance to process its own prompts.
+
+import gc
+import os
+
+VLLM_ENABLE_GRAPGH_MODE = os.environ.get("VLLM_ENABLE_GRAPH_MODE") == "1"
+
+
+def main():
+    dp_rank = int(os.environ['RANK'])
+    local_rank = int(os.environ['LOCAL_RANK'])
+    dp_size = int(os.environ['WORLD_SIZE'])
+    master_addr = os.environ['MASTER_ADDR']
+    master_port = os.environ['MASTER_PORT']
+    tp_size = 4
+    etp_size = 2
+
+    os.environ["VLLM_DP_RANK"] = str(dp_rank)
+    os.environ["VLLM_DP_SIZE"] = str(dp_size)
+    os.environ["VLLM_DP_MASTER_IP"] = master_addr
+    os.environ["VLLM_DP_MASTER_PORT"] = master_port
+    os.environ["ASCEND_RT_VISIBLE_DEVICES"] = ",".join(
+        str(i)
+        for i in range(local_rank * tp_size, (local_rank + 1) * tp_size))
+
+    import torch
+    import torch_npu  # noqa
+    from vllm import LLM, SamplingParams
+    from vllm.distributed.parallel_state import (
+        destroy_distributed_environment, destroy_model_parallel)
+
+    prompts = [
+        "Hello, my name is",
+        "The president of the United States is",
+        "The capital of France is",
+        "The future of AI is",
+    ] * 4
+
+    promts_per_rank = len(prompts) // dp_size
+    start = dp_rank * promts_per_rank
+    end = start + promts_per_rank
+    prompts = prompts[start:end]
+    if len(prompts) == 0:
+        prompts = ["Placeholder"]
+    print(f"DP rank {dp_rank} needs to process {len(prompts)} prompts")
+    num_seqs = len(prompts)
+
+    sampling_params = SamplingParams(temperature=0.8,
+                                     top_p=0.95,
+                                     max_tokens=4,
+                                     min_tokens=4)
+    # Create an LLM.
+    llm = LLM(
+        model="deepseek-ai/DeepSeek-V2-Lite-Chat",
+        tensor_parallel_size=tp_size,
+        trust_remote_code=True,
+        expert_tensor_parallel_size=etp_size,
+        max_model_len=4096,
+        max_num_seqs=num_seqs,
+        compilation_config=1 if VLLM_ENABLE_GRAPGH_MODE else 0,
+    )
+
+    outputs = llm.generate(prompts, sampling_params)
+    for output in outputs:
+        prompt = output.prompt
+        generated_text = output.outputs[0].text
+        print(f"DP rank {dp_rank}, Prompt: {prompt!r}, "
+              f"Generated text: {generated_text!r}")
+
+    del llm
+    destroy_model_parallel()
+    destroy_distributed_environment()
+    gc.collect()
+    torch.npu.empty_cache()
+
+
+if __name__ == "__main__":
+    main()

examples/dp_offline/run_dp.sh

@@ -0,0 +1,21 @@
+export HCCL_IF_IP=${local_ip}
+export GLOO_SOCKET_IFNAME=${ifname}
+export TP_SOCKET_IFNAME=${ifname}
+export HCCL_SOCKET_IFNAME=${ifname}
+
+# dp_size = node_size * dp_per_node
+node_size=1
+node_rank=0
+dp_per_node=2
+master_addr=127.0.0.1
+master_port=12345
+
+rm -rf ./.torchair_cache/
+rm -rf ./dynamo_*
+rm -rf /root/ascend/log/debug/plog/*
+export VLLM_ENABLE_GRAPH_MODE=0
+export VLLM_ENABLE_MC2=0
+
+torchrun --nproc_per_node ${dp_per_node} --nnodes ${node_size} \
+    --node_rank ${node_rank} --master_addr ${master_addr} --master_port ${master_port} \
+    data_parallel.py