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Do not make transforms module accessible at root level
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Diff for: RELEASE-NOTES.md

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@@ -38,6 +38,7 @@ All of the above apply to:
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- `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)).
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- `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)).
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- `pm.sample(trace=...)` no longer accepts `MultiTrace` or `len(.) > 0` traces ([see 5019#](https://github.com/pymc-devs/pymc/pull/5019)).
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- `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)).
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- `logpt`, `logpt_sum`, `logp_elemwiset` and `nojac` variations were removed. Use `Model.logpt(jacobian=True/False, sum=True/False)` instead.
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- `dlogp_nojact` and `d2logp_nojact` were removed. Use `Model.dlogpt` and `d2logpt` with `jacobian=False` instead.
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- `logp`, `dlogp`, and `d2logp` and `nojac` variations were removed. Use `Model.compile_logp`, `compile_dlgop` and `compile_d2logp` with `jacobian` keyword instead.

Diff for: docs/source/api/distributions/transforms.rst

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Transformations
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***************
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5-
.. currentmodule:: pymc.transforms
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.. currentmodule:: pymc.distributions.transforms
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Transform Instances
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~~~~~~~~~~~~~~~~~~~

Diff for: pymc/__init__.py

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

Diff for: pymc/distributions/transforms.py

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

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