feature: Add Exponential distribution to autoreparameterization dispatch table

Author: ferrine

pymc_experimental/model/transforms/autoreparam.py

@@ -246,6 +246,44 @@ def _(
     return vip_rep
 
 
+@_vip_reparam_node.register
+def _(
+    op: pm.Exponential,
+    node: Apply,
+    name: str,
+    dims: List[Variable],
+    transform: Optional[Transform],
+    lam: pt.TensorVariable,
+) -> ModelDeterministic:
+    rng, size, scale = node.inputs
+    scale_centered = scale**lam
+    scale_noncentered = scale ** (1 - lam)
+    vip_rv_ = pm.Exponential.dist(
+        scale=scale_centered,
+        size=size,
+        rng=rng,
+    )
+    vip_rv_value_ = vip_rv_.clone()
+    vip_rv_.name = f"{name}::tau_"
+    if transform is not None:
+        vip_rv_value_.name = f"{vip_rv_.name}_{transform.name}__"
+    else:
+        vip_rv_value_.name = vip_rv_.name
+    vip_rv = model_free_rv(
+        vip_rv_,
+        vip_rv_value_,
+        transform,
+        *dims,
+    )
+
+    vip_rep_ = scale_noncentered * vip_rv
+
+    vip_rep_.name = name
+
+    vip_rep = model_deterministic(vip_rep_, *dims)
+    return vip_rep
+
+
 def vip_reparametrize(
     model: pm.Model,
     var_names: Sequence[str],