class_docstr: Categorical distribution with support [shift, shift + K] instead of [0, K].
  
  Simply a thin wrapper around Categorical which takes a user provided minimal
  value and shifts the minimum value using the provided value. This distribution
  allows policies where the user provides an action_spec range, e.g. QPolicy, to
  honor it, by offsetting the sampled value.
class_docstr_tok: ["Categorical","distribution","with","support","[","shift",",","shift","+","K","]","instead","of","[","0",",","K","]",".","Simply","a","thin","wrapper","around","Categorical","which","takes","a","user","provided","minimal","value","and","shifts","the","minimum","value","using","the","provided","value",".","This","distribution","allows","policies","where","the","user","provides","an","action_spec","range",",","e.g",".","QPolicy",",","to","honor","it",",","by","offsetting","the","sampled","value","."]
docstr: Probability density/mass function.
docstr_tok: ["Probability","density\/mass","function","."]
code: def prob(self, value, name="prob"):
      """Probability density/mass function."""
      value -= self._shift
      return super(ShiftedCategorical, self).prob(value, name)
  
file_path: agents/tf_agents/distributions/shifted_categorical.py
imports: import tensorflow
  import tensorflow_probability
label_desc: Use image node_id 3 for calling the ShiftedCategorical obj's underlying member method code with example usage: obj.prob(value, name) and returns: super