[GSoC] Add e2e test for `tune` api with LLM hyperparameter optimization #1259

Job	Run time
e2e (v1.29.2, long-running-resume,from-volume-resume,median-stop)	16m 20s
e2e (v1.29.2, grid,bayesian-optimization,tpe,multivariate-tpe,cma-es,hyperband)	18m 59s
e2e (v1.29.2, file-metrics-collector,pytorchjob-mnist)	15m 7s
e2e (v1.29.2, median-stop-with-json-format,file-metrics-collector-with-json-format)	12m 3s
e2e (v1.30.7, long-running-resume,from-volume-resume,median-stop)	15m 5s
e2e (v1.30.7, grid,bayesian-optimization,tpe,multivariate-tpe,cma-es,hyperband)	22m 0s
e2e (v1.30.7, file-metrics-collector,pytorchjob-mnist)	12m 56s
e2e (v1.30.7, median-stop-with-json-format,file-metrics-collector-with-json-format)	15m 15s
e2e (v1.31.3, long-running-resume,from-volume-resume,median-stop)	14m 34s
e2e (v1.31.3, grid,bayesian-optimization,tpe,multivariate-tpe,cma-es,hyperband)	20m 52s
e2e (v1.31.3, file-metrics-collector,pytorchjob-mnist)	13m 26s
e2e (v1.31.3, median-stop-with-json-format,file-metrics-collector-with-json-format)	12m 33s
	3h 9m 10s

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