code: def get_feature_configs():
      input_features = [
          {"name": "x", "type": "number"},
      ]
      output_features = [
          {
              "name": "y",
              "type": "number",
              "loss": {"type": "mean_squared_error"},
              "decoder": {
                  "num_fc_layers": 2,
                  "fc_output_size": 64,
              },
          }
      ]
  
      return input_features, output_features
  
imports: from collections import namedtuple
  import numpy
  import pandas
  from sklearn.model_selection import train_test_split
label_desc: Use image node_id 1 for calling a global function with example usage: get_feature_configs() and returns: input_features,  output_features