Important miscellaneous v4 updates

.github/workflows/pytest.yml

@@ -31,7 +31,6 @@ jobs:
             --ignore=pymc3/tests/test_mixture.py
             --ignore=pymc3/tests/test_model_graph.py
             --ignore=pymc3/tests/test_modelcontext.py
-            --ignore=pymc3/tests/test_models_linear.py
             --ignore=pymc3/tests/test_parallel_sampling.py
             --ignore=pymc3/tests/test_profile.py
             --ignore=pymc3/tests/test_random.py
@@ -42,7 +41,6 @@ jobs:
             --ignore=pymc3/tests/test_tracetab.py
             --ignore=pymc3/tests/test_tuning.py
             --ignore=pymc3/tests/test_types.py
-            --ignore=pymc3/tests/test_util.py
             --ignore=pymc3/tests/test_variational_inference.py
             --ignore=pymc3/tests/test_sampling_jax.py
             --ignore=pymc3/tests/test_dist_math.py
@@ -53,11 +51,11 @@ jobs:
             --ignore=pymc3/tests/test_updates.py
             --ignore=pymc3/tests/test_examples.py
             --ignore=pymc3/tests/test_glm.py
+            --ignore=pymc3/tests/test_glm_utils.py
+            --ignore=pymc3/tests/test_glm_linear.py
             --ignore=pymc3/tests/test_gp.py
             --ignore=pymc3/tests/test_model.py
             --ignore=pymc3/tests/test_model_func.py
-            --ignore=pymc3/tests/test_model_helpers.py
-            --ignore=pymc3/tests/test_models_utils.py
             --ignore=pymc3/tests/test_ode.py
             --ignore=pymc3/tests/test_posdef_sym.py
             --ignore=pymc3/tests/test_quadpotential.py
@@ -79,15 +77,15 @@ jobs:
             pymc3/tests/test_distributions_random.py
             pymc3/tests/test_examples.py
             pymc3/tests/test_glm.py
+            pymc3/tests/test_glm_utils.py
             pymc3/tests/test_gp.py
             pymc3/tests/test_model.py
             pymc3/tests/test_model_func.py
-            pymc3/tests/test_model_helpers.py
-            pymc3/tests/test_models_utils.py
             pymc3/tests/test_ode.py
             pymc3/tests/test_posdef_sym.py
             pymc3/tests/test_quadpotential.py
             pymc3/tests/test_shape_handling.py
+            pymc3/tests/test_step.py
 
       fail-fast: false
     runs-on: ${{ matrix.os }}

docs/source/Probability_Distributions.rst

@@ -117,20 +117,15 @@ For example, the gamma distribution is positive-valued. If we define one for a m
     with pm.Model() as model:
         g = pm.Gamma('g', 1, 1)
 
-We notice a modified variable inside the model ``vars`` attribute, which holds the free variables in the model.
+We notice a modified variable inside the model ``value_vars`` attribute.  These variables represent the values of each random variable in the model's log-likelihood.
 
 ::
 
-    >>> model.vars
+    >>> model.value_vars
     [g_log__]
 
-As the name suggests, the variable ``g`` has been log-transformed, and this is the space over which sampling takes place.
+As the name suggests, the variable ``g`` has been log-transformed, and this is the space over which posterior sampling takes place.
 
-The original variable is simply treated as a deterministic variable, since the value of the transformed variable is simply back-transformed when a sample is drawn in order to recover the original variable. Hence, ``g`` resides in the ``model.deterministics`` list.
-
-::
-
-    >>> model.deterministics
-    [g]
+The value of the transformed variable is simply back-transformed when a sample is drawn in order to recover the original variable.
 
 By default, auto-transformed variables are ignored when summarizing and plotting model output.

docs/source/developer_guide.rst

@@ -414,8 +414,8 @@ initialised within the same model) as input, for example:
         z = pm.Normal('z', 0., 10., shape=10)
         x = pm.Normal('x', z, 1., shape=10)
 
-    print(m.test_point)
-    print(m.dict_to_array(m.test_point))  # ==> m.bijection.map(m.test_point)
+    print(m.initial_point)
+    print(m.dict_to_array(m.initial_point))  # ==> m.bijection.map(m.initial_point)
     print(m.bijection.rmap(np.arange(20)))
 
 
@@ -707,7 +707,7 @@ list of CompoundStep in a for-loop for one sample circle.
 
 For each sampler, it implements a ``step.step`` method to perform MH
 updates. Each time a dictionary (``point`` in ``PyMC3`` land, same
-structure as ``model.test_point``) is passed as input and output a new
+structure as ``model.initial_point``) is passed as input and output a new
 dictionary with the free\_RVs being sampled now has a new value (if
 accepted, see
 `here <https://github.com/pymc-devs/pymc3/blob/6d07591962a6c135640a3c31903eba66b34e71d8/pymc3/step_methods/compound.py#L27>`__