Address latest review comments from RicardoV94

pymc3/distributions/continuous.py

@@ -20,6 +20,7 @@
 
 from typing import List, Optional, Tuple, Union
 
+import aesara
 import aesara.tensor as at
 import numpy as np
 
@@ -4106,7 +4107,7 @@ def make_node(self, x, h, z):
         z = at.as_tensor_variable(floatX(z))
         shape = broadcast_shape(x, h, z)
         broadcastable = [] if not shape else [False] * len(shape)
-        return Apply(self, [x, h, z], [at.TensorType(np.float64, broadcastable)()])
+        return Apply(self, [x, h, z], [at.TensorType(aesara.config.floatX, broadcastable)()])
 
     def perform(self, node, ins, outs):
         x, h, z = ins[0], ins[1], ins[2]
@@ -4200,12 +4201,12 @@ class PolyaGamma(PositiveContinuous):
 
     @classmethod
     def dist(cls, h=1.0, z=0.0, **kwargs):
-        hh = at.as_tensor_variable(floatX(h))
-        zz = at.as_tensor_variable(floatX(z))
+        h = at.as_tensor_variable(floatX(h))
+        z = at.as_tensor_variable(floatX(z))
 
-        msg = f"The variable {hh} specified for PolyaGamma has non-positive "
+        msg = f"The variable {h} specified for PolyaGamma has non-positive "
         msg += "values, making it unsuitable for this parameter."
-        Assert(msg)(hh, at.all(at.gt(hh, 0.0)))
+        Assert(msg)(h, at.all(at.gt(h, 0.0)))
 
         return super().dist([h, z], **kwargs)