!7413 Solve the problem with input of Nan in logrithm calculation

Merge pull request !7413 from peixu_ren/custom_bijector

mindspore/nn/probability/distribution/transformed_distribution.py

@@ -84,6 +84,7 @@ class TransformedDistribution(Distribution):
         self.parameter_names = distribution.parameter_names
         self.exp = exp_generic
         self.log = log_generic
+        self.isnan = P.IsNan()
         self.equal_base = P.Equal()
         self.select_base = P.Select()
 
@@ -132,7 +133,10 @@ class TransformedDistribution(Distribution):
         unadjust_prob = self.distribution("log_prob", inverse_value, *args, **kwargs)
         log_jacobian = self.bijector("inverse_log_jacobian", value)
         isneginf = self.equal_base(unadjust_prob, -np.inf)
-        return self.select_base(isneginf, unadjust_prob, unadjust_prob + log_jacobian)
+        isnan = self.equal_base(unadjust_prob + log_jacobian, np.nan)
+        return self.select_base(isneginf,
+                                self.select_base(isnan, unadjust_prob + log_jacobian, unadjust_prob),
+                                unadjust_prob + log_jacobian)
 
     def _prob(self, value, *args, **kwargs):
         return self.exp(self._log_prob(value, *args, **kwargs))