Fix docstrings, enable distr_output in MQRNN

src/gluonts/model/seq2seq/_forking_network.py

@@ -44,8 +44,10 @@ class ForkingSeq2SeqNetworkBase(gluon.HybridBlock):
  encoder to decoder mapping block.
  decoder: Seq2SeqDecoder
  decoder block.
- output
- An instance of DistributionOutput or QuantileOutput to use
+ quantile_output
+ quantile output
+ distr_output
+ distribution output
  context_length: int,
  length of the encoding sequence.
  cardinality: List[int],

src/gluonts/model/seq2seq/_mq_dnn_estimator.py

@@ -101,6 +101,9 @@ class MQCNNEstimator(ForkingSeq2SeqEstimator):
  Optimizing for more quantiles than are of direct interest to you can result
  in improved performance due to a regularizing effect.
  (default: [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9])
+ distr_output
+ DistributionOutput to use. Only one between `quantile` and `distr_output`
+ can be set. (Default: None)
  trainer
  The GluonTS trainer to use for training. (default: Trainer())
  scaling
@@ -175,7 +178,6 @@ def __init__(
  if (quantiles is not None) or (distr_output is not None)
  else [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]
  )
- self.distr_output = distr_output
 
  assert (
  len(self.channels_seq)
@@ -308,7 +310,8 @@ def __init__(
  context_length: Optional[int] = None,
  decoder_mlp_dim_seq: List[int] = None,
  trainer: Trainer = Trainer(),
- quantiles: List[float] = None,
+ quantiles: Optional[List[float]] = None,
+ distr_output: Optional[DistributionOutput] = None,
  scaling: bool = False,
  scaling_decoder_dynamic_feature: bool = False,
  ) -> None:
@@ -328,7 +331,7 @@ def __init__(
  )
  self.quantiles = (
  quantiles
- if quantiles is not None
+ if (quantiles is not None) or (distr_output is not None)
  else [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]
  )
 
@@ -351,12 +354,15 @@ def __init__(
  prefix="decoder_",
  )
 
- quantile_output = QuantileOutput(self.quantiles)
+ quantile_output = (
+ QuantileOutput(self.quantiles) if self.quantiles else None
+ )
 
  super().__init__(
  encoder=encoder,
  decoder=decoder,
  quantile_output=quantile_output,
+ distr_output=distr_output,
  freq=freq,
  prediction_length=prediction_length,
  context_length=context_length,

test/model/seq2seq/test_model.py

@@ -63,7 +63,7 @@ def test_accuracy(
  )
 
  accuracy_test(
- Estimator, hyperparameters, accuracy=0.20 if quantiles else 0.40
+ Estimator, hyperparameters, accuracy=0.20 if quantiles else 0.50
  )