code: def hyperparameters(dsinfo):
      return dict(
          ctx="cpu",
          epochs=1,
          learning_rate=1e-2,
          hybridize=True,
          context_length=dsinfo.prediction_length,
          num_forking=1,
          num_batches_per_epoch=1,
          quantiles=[0.1, 0.5, 0.9],
          use_symbol_block_predictor=True,
      )
  
file_path: gluonts/test/mx/model/seq2seq/test_model.py
imports: import pytest
  from gluonts.mx import MQCNNEstimator, MQRNNEstimator
  from gluonts.mx.distribution import GaussianOutput, ISQFOutput
  from gluonts.testutil.dummy_datasets import make_dummy_datasets_with_features
label_desc: Use image node_id 1 for calling a global function with example usage: hyperparameters(dsinfo) and returns: dict