From 1d001bf0ab36417ebdf87567cd72fad6209d749e Mon Sep 17 00:00:00 2001
From: "hasnain3257@gmail.com" <hasnain3257@gmail.com>
Date: Fri, 24 Nov 2023 12:33:35 +0100
Subject: [PATCH] Update RVTransform

---
 pymc_experimental/utils/prior.py | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/pymc_experimental/utils/prior.py b/pymc_experimental/utils/prior.py
index 962b01bc0..30d4e9507 100644
--- a/pymc_experimental/utils/prior.py
+++ b/pymc_experimental/utils/prior.py
@@ -19,12 +19,12 @@
 import numpy as np
 import pymc as pm
 import pytensor.tensor as pt
-from pymc.logprob.transforms import RVTransform
+from pymc.logprob.transforms import Transform
 
 
 class ParamCfg(TypedDict):
     name: str
-    transform: Optional[RVTransform]
+    transform: Optional[Transform]
     dims: Optional[Union[str, Tuple[str]]]
 
 
@@ -44,14 +44,14 @@ class FlatInfo(TypedDict):
     info: List[VarInfo]
 
 
-def _arg_to_param_cfg(key, value: Optional[Union[ParamCfg, RVTransform, str, Tuple]] = None):
+def _arg_to_param_cfg(key, value: Optional[Union[ParamCfg, Transform, str, Tuple]] = None):
     if value is None:
         cfg = ParamCfg(name=key, transform=None, dims=None)
     elif isinstance(value, Tuple):
         cfg = ParamCfg(name=key, transform=None, dims=value)
     elif isinstance(value, str):
         cfg = ParamCfg(name=value, transform=None, dims=None)
-    elif isinstance(value, RVTransform):
+    elif isinstance(value, Transform):
         cfg = ParamCfg(name=key, transform=value, dims=None)
     else:
         cfg = value.copy()
@@ -62,7 +62,7 @@ def _arg_to_param_cfg(key, value: Optional[Union[ParamCfg, RVTransform, str, Tup
 
 
 def _parse_args(
-    var_names: Sequence[str], **kwargs: Union[ParamCfg, RVTransform, str, Tuple]
+    var_names: Sequence[str], **kwargs: Union[ParamCfg, Transform, str, Tuple]
 ) -> Dict[str, ParamCfg]:
     results = dict()
     for var in var_names:
@@ -133,7 +133,7 @@ def prior_from_idata(
     name="trace_prior_",
     *,
     var_names: Sequence[str] = (),
-    **kwargs: Union[ParamCfg, RVTransform, str, Tuple]
+    **kwargs: Union[ParamCfg, Transform, str, Tuple]
 ) -> Dict[str, pt.TensorVariable]:
     """
     Create a prior from posterior using MvNormal approximation.
@@ -153,7 +153,7 @@ def prior_from_idata(
         Inference data with posterior group
     var_names: Sequence[str]
         names of variables to take as is from the posterior
-    kwargs: Union[ParamCfg, RVTransform, str, Tuple]
+    kwargs: Union[ParamCfg, Transform, str, Tuple]
         names of variables with additional configuration, see more in Examples
 
     Examples