}

func getResourceLimits(cpu, memory string) core.ResourceList {
	res := core.ResourceList{}
	res[core.ResourceCPU] = resource.MustParse(cpu)
	res[core.ResourceMemory] = resource.MustParse(memory)
	return res
}

func getResources(cpu, memory, storage string) core.ResourceList {
	res := core.ResourceList{}
	if cpu != "" {
		res[core.ResourceCPU] = resource.MustParse(cpu)
	}
	if memory != "" {

              }
            ],
            "description": "Data is the serialized representation of the state."
          },
          "kind": {

Ong, Marshal Hayes, Martin Pool, matthieudelaro, mdfaijul, mholzel, Michael
Zhou, Ming Li, Minmin Sun, Myungjoo Ham, MyungsungKwak, Naman Kamra, Peng Yu,
Penghao Cen, Phil, Raghuraman-K, resec, Rohin Mohanadas, Sandeep N Gupta, Scott
Tseng, seaotterman, Seo Sanghyeon, Sergei Lebedev, Ted Chang, terrytangyuan, Tim
H, tkunic, Tod, vihanjain, Yan Facai (颜发才), Yin Li, Yong Tang, Yukun Chen,
Yusuke Yamada

  );

  let results = (outs
    Res<TF_Float32Tensor, [{A 4D Tensor for output data.}]>:$y,
    Res<TF_Float32Tensor, [{A 1D Tensor for the computed batch mean, to be used by TensorFlow
to compute the running mean.}]>:$batch_mean,
    Res<TF_Float32Tensor, [{A 1D Tensor for the computed batch variance, to be used by
TensorFlow to compute the running variance.}]>:$batch_variance,