From e1ba7f84e6fb147f5466611e1b78d5d1bfb743d2 Mon Sep 17 00:00:00 2001
From: Ricardo <ricardo.vieira1994@gmail.com>
Date: Thu, 3 Feb 2022 12:22:48 +0100
Subject: [PATCH 1/2] Move test_sample_deterministic to TestSample class and
 rename it to test_deterministic_of_unobserved

---
 pymc/tests/test_sampling.py | 22 +++++++++++++---------
 1 file changed, 13 insertions(+), 9 deletions(-)

diff --git a/pymc/tests/test_sampling.py b/pymc/tests/test_sampling.py
index 7c8be684fad..86fdaf6de26 100644
--- a/pymc/tests/test_sampling.py
+++ b/pymc/tests/test_sampling.py
@@ -313,6 +313,19 @@ def test_exceptions(self):
             with pytest.raises(NotImplementedError):
                 xvars = [t["mu"] for t in trace]
 
+    def test_deterministic_of_unobserved(self):
+        with pm.Model() as model:
+            x = pm.HalfNormal("x", 1)
+            y = pm.Deterministic("y", x + 100)
+            idata = pm.sample(
+                chains=1,
+                tune=10,
+                draws=50,
+                compute_convergence_checks=False,
+            )
+
+        np.testing.assert_allclose(idata.posterior["y"], idata.posterior["x"] + 100)
+
 
 def test_sample_find_MAP_does_not_modify_start():
     # see https://github.com/pymc-devs/pymc/pull/4458
@@ -1220,15 +1233,6 @@ def test_sample_from_xarray_posterior(self, point_list_arg_bug_fixture):
             pp = pm.sample_posterior_predictive(idat.posterior, var_names=["d"])
 
 
-def test_sample_deterministic():
-    with pm.Model() as model:
-        x = pm.HalfNormal("x", 1)
-        y = pm.Deterministic("y", x + 100)
-        idata = pm.sample(chains=1, draws=50, compute_convergence_checks=False)
-
-    np.testing.assert_allclose(idata.posterior["y"], idata.posterior["x"] + 100)
-
-
 class TestDraw(SeededTest):
     def test_univariate(self):
         with pm.Model():

From ae835f56c8b970b267b34a4d63f1548725417ac3 Mon Sep 17 00:00:00 2001
From: Ricardo <ricardo.vieira1994@gmail.com>
Date: Thu, 3 Feb 2022 12:40:21 +0100
Subject: [PATCH 2/2] Replace RVs by respective value variables in the graph of
 untransformed variables

This fixes incorrect behavior, where deterministic projection from transformed (sampling) to untransformed space would be nonsensical when transforms depend on other graph variables
---
 pymc/model.py               | 10 +++++++---
 pymc/tests/test_sampling.py | 11 +++++++++++
 2 files changed, 18 insertions(+), 3 deletions(-)

diff --git a/pymc/model.py b/pymc/model.py
index aa6a8bfbadf..7ffa5f6d74d 100644
--- a/pymc/model.py
+++ b/pymc/model.py
@@ -900,10 +900,11 @@ def value_vars(self):
     @property
     def unobserved_value_vars(self):
         """List of all random variables (including untransformed projections),
-        as well as deterministics used as inputs and outputs of the the model's
+        as well as deterministics used as inputs and outputs of the model's
         log-likelihood graph
         """
         vars = []
+        untransformed_vars = []
         for rv in self.free_RVs:
             value_var = self.rvs_to_values[rv]
             transform = getattr(value_var.tag, "transform", None)
@@ -912,13 +913,16 @@ def unobserved_value_vars(self):
                 # each transformed variable
                 untrans_value_var = transform.backward(value_var, *rv.owner.inputs)
                 untrans_value_var.name = rv.name
-                vars.append(untrans_value_var)
+                untransformed_vars.append(untrans_value_var)
             vars.append(value_var)
 
+        # Remove rvs from untransformed values graph
+        untransformed_vars, _ = rvs_to_value_vars(untransformed_vars, apply_transforms=True)
+
         # Remove rvs from deterministics graph
         deterministics, _ = rvs_to_value_vars(self.deterministics, apply_transforms=True)
 
-        return vars + deterministics
+        return vars + untransformed_vars + deterministics
 
     @property
     def basic_RVs(self):
diff --git a/pymc/tests/test_sampling.py b/pymc/tests/test_sampling.py
index 86fdaf6de26..d145631eb83 100644
--- a/pymc/tests/test_sampling.py
+++ b/pymc/tests/test_sampling.py
@@ -23,6 +23,7 @@
 import numpy as np
 import numpy.testing as npt
 import pytest
+import scipy.special
 
 from aesara import shared
 from arviz import InferenceData
@@ -326,6 +327,16 @@ def test_deterministic_of_unobserved(self):
 
         np.testing.assert_allclose(idata.posterior["y"], idata.posterior["x"] + 100)
 
+    def test_transform_with_rv_depenency(self):
+        # Test that untransformed variables that depend on upstream variables are properly handled
+        with pm.Model() as m:
+            x = pm.HalfNormal("x", observed=1)
+            transform = pm.transforms.IntervalTransform(lambda *inputs: (inputs[-2], inputs[-1]))
+            y = pm.Uniform("y", lower=0, upper=x, transform=transform)
+            trace = pm.sample(tune=10, draws=50, return_inferencedata=False, random_seed=336)
+
+        assert np.allclose(scipy.special.expit(trace["y_interval__"]), trace["y"])
+
 
 def test_sample_find_MAP_does_not_modify_start():
     # see https://github.com/pymc-devs/pymc/pull/4458