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List dims module functionality in the docs
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docs/source/api.rst

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api/backends
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api/misc
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api/testing
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api/dims
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------------------
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Dimensionality

docs/source/api/dims.rst

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.. _api_dims:
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Dims
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====
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.. warning:: This module is experimental and may contain critical breaks. API changes are expected in future releases.
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This submodule contains functions for defining distributions and operations that use explicit dimensions.
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The module is presented in :ref:`dims_module`.
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.. toctree::
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dims/model
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dims/math
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dims/distributions
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dims/transforms
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*************
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Distributions
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*************
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Scalar distributions
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====================
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.. currentmodule:: pymc.dims
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.. autosummary::
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:toctree: generated/
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:template: distribution.rst
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Flat
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HalfFlat
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Normal
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HalfNormal
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LogNormal
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StudentT
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HalfStudentT
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Cauchy
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HalfCauchy
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Beta
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Laplace
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Gamma
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InverseGamma
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Vector distributions
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====================
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.. currentmodule:: pymc.dims
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.. autosummary::
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:toctree: generated/
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:template: distribution.rst
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Categorical
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MvNormal
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ZeroSumNormal

docs/source/api/dims/math.rst

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***************************************
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Mathematical operations with dimensions
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***************************************
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This module wraps all the mathematical operations defined in :ref:`pytensor.xtensor.math <pytensor:libdoc_xtensor_math>`.
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It includes a ``linalg`` submodule that wraps all the operations defined in :ref:`pytensor.xtensor.linalg <pytensor:libdoc_xtensor_linalg>`.
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Operations defined at the module level in :ref:`pytensor.xtensor <pytensor:libdoc_xtensor_module_function>` are available at the ``pymc.dims`` module level.

docs/source/api/dims/model.rst

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******************
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Model constructors
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******************
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.. currentmodule:: pymc.dims
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.. autosummary::
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:toctree: generated/
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Data
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Deterministic
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Potential

docs/source/api/dims/transforms.rst

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***********************
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Distribution Transforms
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***********************
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.. currentmodule:: pymc.dims.transforms
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.. autosummary::
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:toctree: generated/
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LogTransform
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LogOddsTransform
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ZeroSumTransform

docs/source/learn/core_notebooks/dims_module.ipynb

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"id": "17e37649edaa8d0d",
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"metadata": {},
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"source": [
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"(dims_module)=\n",
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"\n",
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"# PyMC dims module"
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]
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},

docs/source/learn/core_notebooks/index.md

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:maxdepth: 1
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pymc_overview
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GLM_linear
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model_comparison
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posterior_predictive
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dimensionality
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pymc_pytensor
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dims_module
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GLM_linear
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Gaussian_Processes
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:::
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