Do not make transforms module accessible at root level

Author: ricardoV94

RELEASE-NOTES.md

@@ -38,6 +38,7 @@ All of the above apply to:
 - `pm.sample_prior_predictive`, `pm.sample_posterior_predictive` and `pm.sample_posterior_predictive_w` now return an `InferenceData` object by default, instead of a dictionary (see [#5073](https://github.com/pymc-devs/pymc/pull/5073)).
 - `pm.sample_prior_predictive` no longer returns transformed variable values by default. Pass them by name in `var_names` if you want to obtain these draws (see [4769](https://github.com/pymc-devs/pymc/pull/4769)).
 - `pm.sample(trace=...)` no longer accepts `MultiTrace` or `len(.) > 0` traces ([see 5019#](https://github.com/pymc-devs/pymc/pull/5019)).
+- `transforms` module is no longer accessible ta the root level. It is accessible at `pymc.distributions.transforms` (see[#5347](https://github.com/pymc-devs/pymc/pull/5347)).
 - `logpt`, `logpt_sum`, `logp_elemwiset` and `nojac` variations were removed. Use `Model.logpt(jacobian=True/False, sum=True/False)` instead.
 - `dlogp_nojact` and `d2logp_nojact` were removed. Use `Model.dlogpt` and `d2logpt` with `jacobian=False` instead.
 - `logp`, `dlogp`, and `d2logp` and `nojac` variations were removed. Use `Model.compile_logp`, `compile_dlgop` and `compile_d2logp` with `jacobian` keyword instead.

docs/source/api/distributions/transforms.rst

@@ -2,7 +2,7 @@
 Transformations
 ***************
 
-.. currentmodule:: pymc.transforms
+.. currentmodule:: pymc.distributions.transforms
 
 Transform Instances
 ~~~~~~~~~~~~~~~~~~~

pymc/__init__.py

@@ -55,7 +55,6 @@ def __set_compiler_flags():
 from pymc.blocking import *
 from pymc.data import *
 from pymc.distributions import *
-from pymc.distributions import transforms
 from pymc.exceptions import *
 from pymc.func_utils import find_constrained_prior
 from pymc.math import (

pymc/distributions/transforms.py

@@ -259,12 +259,12 @@ def bounds_fn(*rv_inputs):
 
 log_exp_m1 = LogExpM1()
 log_exp_m1.__doc__ = """
-Instantiation of :class:`pymc.transforms.LogExpM1`
+Instantiation of :class:`pymc.distributions.transforms.LogExpM1`
 for use in the ``transform`` argument of a random variable."""
 
 ordered = Ordered()
 ordered.__doc__ = """
-Instantiation of :class:`pymc.transforms.Ordered`
+Instantiation of :class:`pymc.distributions.transforms.Ordered`
 for use in the ``transform`` argument of a random variable."""
 
 log = LogTransform()
@@ -274,7 +274,7 @@ def bounds_fn(*rv_inputs):
 
 sum_to_1 = SumTo1()
 sum_to_1.__doc__ = """
-Instantiation of :class:`pymc.transforms.SumTo1`
+Instantiation of :class:`pymc.distributions.transforms.SumTo1`
 for use in the ``transform`` argument of a random variable."""
 
 circular = CircularTransform()