class_docstr: Categorical probability distribution
code: def __init__(self, logits, mask_npinf, nsteps, size, is_act_model):
      self.logits = logits
      self.mask_npinf = mask_npinf
      self.nsteps = nsteps
      self.size = size
      self.is_act_model = is_act_model
  
imports: import tensorflow.compat.v1
  from .util import fc
label_desc: Use image node_id 1 to create a new CategoricalPd object from inherited base classes: Pd with example: obj = CategoricalPd(logits, mask_npinf, nsteps, size, is_act_model)