[GSoC] Add e2e test for `tune` api with LLM hyperparameter optimization #1097

Job	Run time
e2e (v1.27.11, long-running-resume,from-volume-resume,median-stop)	20m 51s
e2e (v1.27.11, grid,bayesian-optimization,tpe,multivariate-tpe,cma-es,hyperband)	23m 31s
e2e (v1.27.11, file-metrics-collector,pytorchjob-mnist)	17m 53s
e2e (v1.27.11, median-stop-with-json-format,file-metrics-collector-with-json-format)	20m 20s
e2e (v1.28.7, long-running-resume,from-volume-resume,median-stop)	18m 56s
e2e (v1.28.7, grid,bayesian-optimization,tpe,multivariate-tpe,cma-es,hyperband)	24m 41s
e2e (v1.28.7, file-metrics-collector,pytorchjob-mnist)	17m 56s
e2e (v1.28.7, median-stop-with-json-format,file-metrics-collector-with-json-format)	15m 46s
e2e (v1.29.2, long-running-resume,from-volume-resume,median-stop)	20m 10s
e2e (v1.29.2, grid,bayesian-optimization,tpe,multivariate-tpe,cma-es,hyperband)	25m 23s
e2e (v1.29.2, file-metrics-collector,pytorchjob-mnist)	17m 59s
e2e (v1.29.2, median-stop-with-json-format,file-metrics-collector-with-json-format)	18m 9s
	4h 1m 35s

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