[Bugfix] Fix max_num_batched_tokens for MLA

[mgoin]

Without this change we are stuck with a very short allowed prompt length by default with deepseek models

Before this PR:

vllm serve /home/vllm-dev/DeepSeek-R1 --trust-remote-code --tensor-parallel-size 8
...
WARNING 02-20 17:08:38 scheduler.py:949] Input prompt (100005 tokens) is too long and exceeds limit of 2048

You can get past this manually by setting max_num_batched_tokens, but we should take care of this automatically

vllm serve /home/vllm-dev/DeepSeek-R1 --trust-remote-code --tensor-parallel-size 8 --max-num-batched-tokens 163840

Client:

from openai import OpenAI

openai_api_key = "EMPTY"
openai_api_base = "http://localhost:8000/v1"

client = OpenAI(api_key=openai_api_key, base_url=openai_api_base)
model_id = client.models.list().data[0].id

# Query a prompt of roughly 100k tokens by repeating a simple token.
prompt = ("A " * 100000).strip()
chat_response = client.chat.completions.create(
    model=model_id,
    messages=[{"role": "user", "content": [{"type": "text", "text": prompt}]}],
)
print("Text Chat completion output:", chat_response.choices[0].message.content)

[github-actions]

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