code: def get_hyper(hyper):
      """Sweeps over datasets."""
      # pylint: disable=line-too-long
      c100 = lambda **kw: task(
          hyper,
          "cifar100",
          "train[:98%%]",
          "train[98%%:]",
          n_cls=100,
          **kw,
      )
      c10 = lambda **kw: task(
          hyper,
          "cifar10",
          "train[:98%%]",
          "train[98%%:]",
          n_cls=10,
          **kw,
      )
      pet = lambda **kw: task(
          hyper,
          "oxford_iiit_pet",
          "train[:90%%]",
          "train[90%%:]",
          n_cls=37,
          **kw,
      )
      flower = lambda **kw: task(
          hyper,
          "oxford_flowers102",
          "train[:90%%]",
          "train[90%%:]",
          n_cls=102,
          **kw,
      )
      # pylint: enable=line-too-long
  
      return hyper.product(
          [
              hyper.chainit(
                  [
                      c100(
                          h_res=448, l_res=384, steps=10_000, warmup=500
                      ),
                      c10(
                          h_res=448, l_res=384, steps=10_000, warmup=500
                      ),
                      pet(h_res=448, l_res=384, steps=500, warmup=100),
                      flower(
                          h_res=448, l_res=384, steps=500, warmup=100
                      ),
                  ]
              ),
              hyper.sweep(
                  "config.schedule.all.lr_configs.base_learning_rate",
                  [0.03, 0.01, 0.003, 0.001],
              ),
          ]
      )
  
imports: import ml_collections
label_desc: Use image node_id 4 for calling a global function with example usage: get_hyper(hyper) and returns: hyper