text: from rllab.misc.instrument import VariantGenerator, variant
  
  class VG(VariantGenerator):
    
      @variant
      def seed(self):
          return [30]
  
      @variant
      def fast_batch_size(self):
          return [3]
          #performance is better with 50
      @variant
      def fast_learning_rate(self):
          #For LSBaseline
          #return [0]
  
          #For Maesn
          return [0.5]
      
      @variant
      def meta_batch_size(self):
          return [20]
  
      @variant
      def meta_learning_rate(self):
          return [0.01]
  
      @variant
      def kl_weighting(self):
          return [0.1 ]
          #return [0 , 0.01, 0.05 , 0.1]
  
      @variant
      def latent_dim(self):
          return [2]
  
      @variant
      def init_std(self):
          return [1]
  
      @variant
      def exp_name(self , fast_batch_size , fast_learning_rate , meta_batch_size , meta_learning_rate , kl_weighting , latent_dim , init_std , seed):
          yield  'fbs_'+str(fast_batch_size)+'_flr_'+str(fast_learning_rate)+'_mbs_'+str(meta_batch_size)+'_mlr_'+str(meta_learning_rate)+'_kl_'+str(kl_weighting)+ \
          '_ldim_'+str(latent_dim)+'_initStd_'+str(init_std)+'_seed_'+str(seed)
  