class_docstr: DistributionOutput class for the Incremental (Spline) Quantile Function
  Parameters
  ----------
  num_pieces
      number of spline pieces for each spline
      ISQF reduces to IQF when num_pieces = 1
  qk_x
      List containing the x-positions of quantile knots
  tol
      tolerance for numerical safeguarding
class_docstr_tok: ["DistributionOutput","class","for","the","Incremental","(","Spline",")","Quantile","Function","Parameters","--","--","--","--","--","num_pieces","number","of","spline","pieces","for","each","spline","ISQF","reduces","to","IQF","when","num_pieces","=","1","qk_x","List","containing","the","x-positions","of","quantile","knots","tol","tolerance","for","numerical","safeguarding"]
code: def event_shape(self) -> Tuple:
      return ()
  
imports: from typing import Dict, List, Optional, Tuple
  import torch
  import torch.nn.functional
  from torch.distributions import AffineTransform, TransformedDistribution
  from gluonts.core.component import validated
  from .distribution_output import DistributionOutput
label_desc: Use image node_id 5 for calling the ISQFOutput obj's underlying member method code with example usage: obj.event_shape() and returns: 