code: def args(dsinfo):
      common_hp = dict(
          ctx="cpu",
          epochs=1,
          hybridize=True,
          num_batches_per_epoch=1,
      )
      return {
          "generic": {
              "estimator": NBEATSEstimator,
              "args": {"num_stacks": 2},
              **common_hp,
          },
          "interpretable": {
              "estimator": NBEATSEstimator,
              "args": {
                  "num_stacks": 2,
                  "num_blocks": [3],
                  "widths": [256, 2048],
                  "sharing": [True],
                  "stack_types": ["T", "S"],
                  **common_hp,
              },
          },
          "ensemble": {
              "estimator": NBEATSEnsembleEstimator,
              "args": {
                  "meta_context_length": [2 * dsinfo.prediction_length],
                  "meta_loss_function": ["MAPE"],
                  "meta_bagging_size": 2,
                  "num_stacks": 3,
                  **common_hp,
              },
          },
      }
  
imports: import pytest
  from gluonts.mx.model.n_beats import NBEATSEnsembleEstimator, NBEATSEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: args(dsinfo) and returns: dict