[Misc] Remove cruft file in repo (#25678)

Signed-off-by: NickLucche <nlucches@redhat.com>

tests/test_test.py

-# SPDX-License-Identifier: Apache-2.0
-# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
-
-import pytest
-
-from vllm import LLM, envs
-from vllm.sampling_params import SamplingParams
-
-if not envs.VLLM_USE_V1:
-    pytest.skip(
-        "Skipping V1 tests. Rerun with `VLLM_USE_V1=1` to test.",
-        allow_module_level=True,
-    )
-
-
-@pytest.mark.parametrize("model_name", ["Qwen/Qwen2.5-1.5B-Instruct"])
-# TODO TPU will appear busy if we fan-out test params here
-@pytest.mark.parametrize("n_prompts", [1])
-def test_logprobs(model_name: str, n_prompts: int):
-    """
-    Request top logprobs with different sampling settings and check
-    that results contains the requested number, ordered ascendingly.  
-    """
-
-    def check_num_logprobs(logprobs, expected_num: int):
-        for step in logprobs:
-            prev_logp = 1.0
-            # order by rank
-            sorted_step = dict(
-                sorted(step.items(), key=lambda item: item[1].rank))
-
-            if len(step) != expected_num:
-                print("watch out", sorted_step)
-
-            # check results are ordered by prob value
-            # assert len(step) == expected_num
-            for rankno, (tid, logp) in enumerate(sorted_step.items()):
-                assert logp.logprob <= prev_logp
-                prev_logp = logp.logprob
-                assert logp.rank == rankno + 1
-
-    llm = LLM(model_name,
-              enforce_eager=False,
-              max_num_seqs=1,
-              max_model_len=128,
-              max_num_batched_tokens=128)
-    prompts = [
-        "Write a short story about a robot that dreams for the first time."
-    ] * n_prompts
-    greedy_sampling_params = SamplingParams(temperature=0.0, max_tokens=64,\
-         logprobs=4)
-    regular_sampling_params = SamplingParams(temperature=0.4, max_tokens=64,\
-         logprobs=4)
-    topkp_sampling_params = SamplingParams(temperature=0.4, max_tokens=64,\
-         logprobs=4, top_k=12, top_p=0.5)
-
-    for sp in [greedy_sampling_params, regular_sampling_params, \
-               topkp_sampling_params]:
-        output = llm.generate(prompts, sp)
-        for o in output:
-            check_num_logprobs(o.outputs[0].logprobs, 4)