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Change capitalization Pytensor → PyTensor
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.github/ISSUE_TEMPLATE/bug-report.yml

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- type: textarea
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attributes:
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label: "Pytensor version information:"
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label: "PyTensor version information:"
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description: >
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Pytensor Version:
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PyTensor Version:
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Python Version:
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Operating system:
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How did you install pytensor: (conda/pip)

.github/ISSUE_TEMPLATE/config.yml

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contact_links:
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- name: PyMC Discourse
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url: https://discourse.pymc.io/
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about: Ask usage questions about PyMC or Pytensor
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about: Ask usage questions about PyMC or PyTensor

.github/ISSUE_TEMPLATE/documentation.yml

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name: Documentation
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description: Report an issue related to the Pytensor documentation.
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description: Report an issue related to the PyTensor documentation.
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title: "DOC: <Please write a comprehensive title after the 'DOC: ' prefix>"
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labels: [docs]
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.github/ISSUE_TEMPLATE/installation.yml

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name: Post-install/importing issue
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description: Report an issue if you have trouble importing or using Pytensor after installation.
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description: Report an issue if you have trouble importing or using PyTensor after installation.
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title: "<Please write a comprehensive title here>"
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labels: [installation]
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.github/SECURITY.md

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To report a security vulnerability to Pytensor, please go to
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To report a security vulnerability to PyTensor, please go to
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https://tidelift.com/security and see the instructions there.
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.gitignore

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pytensor/generated_version.py.out
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distribute-*.egg
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distribute-*.tar.gz
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Pytensor.suo
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PyTensor.suo
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.ipynb_checkpoints
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.pydevproject
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.ropeproject

CODE_OF_CONDUCT.md

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# Pytensor Code of Conduct
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# PyTensor Code of Conduct
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Like the technical community as a whole, the Pytensor team and community is made
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Like the technical community as a whole, the PyTensor team and community is made
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up of a mixture of professionals and volunteers from all over the world, working
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on every aspect of the mission&mdash;including mentorship, teaching, and connecting
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people.
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the spirit in which it’s intended&mdash;a guide to make it easier to enrich all of
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us and the technical communities in which we participate.
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This code of conduct applies to all spaces managed by the Pytensor project. This
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includes Gitter, mailing lists, the issue tracker, Pytensor events, and any other
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This code of conduct applies to all spaces managed by the PyTensor project. This
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includes Gitter, mailing lists, the issue tracker, PyTensor events, and any other
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forums created by the project team that the community uses for communication.
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In addition, violations of this code outside these spaces may affect a person's
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ability to participate within them.
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excuse for poor behavior and poor manners. We might all experience some
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frustration now and then, but we cannot allow that frustration to turn into a
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personal attack. It’s important to remember that a community where people feel
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uncomfortable or threatened is not a productive one. Members of the Pytensor
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uncomfortable or threatened is not a productive one. Members of the PyTensor
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community should be respectful when dealing with other members as well as with
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people outside the Pytensor community.
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people outside the PyTensor community.
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- __Be careful in the words that you choose.__ We are a community of professionals,
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and we conduct ourselves professionally. Be kind to others. Do not insult or
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then stop.
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- __When we disagree, try to understand why.__ Disagreements, both social and
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technical, happen all the time and Pytensor is no exception. It is important
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technical, happen all the time and PyTensor is no exception. It is important
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that we resolve disagreements and differing views constructively. Remember
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that we’re different. Pytensor benefits from its varied community and
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that we’re different. PyTensor benefits from its varied community and
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people from a wide range of backgrounds. Different people have different
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perspectives on issues. Being unable to understand why someone holds a
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viewpoint doesn’t mean that they’re wrong. Don’t forget that it is human to

CONTRIBUTING.md

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If you want to contribute to Pytensor, have a look at the instructions here:
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If you want to contribute to PyTensor, have a look at the instructions here:
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https://pytensor.readthedocs.io/en/latest/dev_start_guide.html
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## Contribution Expectations
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Archetypes](https://opentechstrategies.com/archetypes) and released under a
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[CC-BY-SA](https://creativecommons.org/licenses/by-sa/4.0/) license.
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The current focus of the Pytensor project is rapid, high quality development of a
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The current focus of the PyTensor project is rapid, high quality development of a
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hackable, pure-Python symbolic tensor library with strong support for graph
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rewrites and transpilation to multiple backends including C,
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[JAX](https://github.com/google/jax>), and
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## Issues and Discussions
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We expect that Github Issues ("issues") indicate work that should be in Pytensor
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We expect that Github Issues ("issues") indicate work that should be in PyTensor
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and can be picked up immediately by a contributor. This includes bugs, which
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indicate something not working as advertised.
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Discussions should be created when the scope or direction of the work, though
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within the stated goals of the Pytensor project, require additional clarification
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within the stated goals of the PyTensor project, require additional clarification
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or consideration before a course of action is chosen.
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For issues a minimal working example (MWE) is strongly recommended when relevant
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(fixing a typo in the documentation does not require a MWE). For discussions,
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MWEs are generally required. All MWEs must be implemented using Pytensor. Please
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do not submit MWEs if they are not implemented in Pytensor. In certain cases,
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pseudocode may be acceptable, but an Pytensor implementation is always preferable.
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MWEs are generally required. All MWEs must be implemented using PyTensor. Please
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do not submit MWEs if they are not implemented in PyTensor. In certain cases,
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pseudocode may be acceptable, but an PyTensor implementation is always preferable.

DESCRIPTION.txt

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Pytensor is a Python library that allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays. It is built on top of NumPy_. Pytensor features:
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PyTensor is a Python library that allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays. It is built on top of NumPy_. PyTensor features:
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* **tight integration with NumPy:** a similar interface to NumPy's. numpy.ndarrays are also used internally in Pytensor-compiled functions.
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* **efficient symbolic differentiation:** Pytensor can compute derivatives for functions of one or many inputs.
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* **tight integration with NumPy:** a similar interface to NumPy's. numpy.ndarrays are also used internally in PyTensor-compiled functions.
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* **efficient symbolic differentiation:** PyTensor can compute derivatives for functions of one or many inputs.
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* **speed and stability optimizations:** avoid nasty bugs when computing expressions such as log(1 + exp(x)) for large values of x.
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* **dynamic C code generation:** evaluate expressions faster.
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* **extensive unit-testing and self-verification:** includes tools for detecting and diagnosing bugs and/or potential problems.

README.rst

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# |v [id K]
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# |TensorConstant{0.0} [id L]
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See `the Pytensor documentation <https://pytensor.readthedocs.io/en/latest/>`__ for in-depth tutorials.
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See `the PyTensor documentation <https://pytensor.readthedocs.io/en/latest/>`__ for in-depth tutorials.
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Installation
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.. |Project Name| replace:: Pytensor
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.. |Project Name| replace:: PyTensor
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.. |Tests Status| image:: https://github.com/pymc-devs/pytensor/workflows/Tests/badge.svg
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:target: https://github.com/pymc-devs/pytensor/actions?query=workflow%3ATests
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.. |Coverage| image:: https://codecov.io/gh/pymc-devs/pytensor/branch/main/graph/badge.svg?token=WVwr8nZYmc

doc/LICENSE.txt

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Contains code from Aesara, Copyright (c) 2021-2022, Aesara Developers.
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All rights reserved.
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theano/scan/*.py[c]: Razvan Pascanu, Frederic Bastien, James Bergstra, Pascal Lamblin, Arnaud Bergeron, PyMC Developers, Pytensor Developers, (c) 2010, Universite de Montreal
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theano/scan/*.py[c]: Razvan Pascanu, Frederic Bastien, James Bergstra, Pascal Lamblin, Arnaud Bergeron, PyMC Developers, PyTensor Developers, (c) 2010, Universite de Montreal
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theano/tensor/sharedvar.py: James Bergstra, (c) 2010, Universite de Montreal, 3-clause BSD License
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theano/gradient.py: James Bergstra, Razvan Pascanu, Arnaud Bergeron, Ian Goodfellow, PyMC Developers, Pytensor Developers, (c) 2011, Universite de Montreal, 3-clause BSD License
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theano/gradient.py: James Bergstra, Razvan Pascanu, Arnaud Bergeron, Ian Goodfellow, PyMC Developers, PyTensor Developers, (c) 2011, Universite de Montreal, 3-clause BSD License
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theano/compile/monitormode.py: this code was initially copied from the 'pyutools' package by its original author, and re-licensed under Theano's license.
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Contains frozendict code from slezica’s python-frozendict(https://github.com/slezica/python-frozendict/blob/master/frozendict/__init__.py), Copyright (c) 2012 Santiago Lezica. All rights reserved.
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* Redistributions in binary form must reproduce the above copyright
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notice, this list of conditions and the following disclaimer in the
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documentation and/or other materials provided with the distribution.
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* Neither the name of Pytensor, Theano, nor the names of its contributors may be
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* Neither the name of PyTensor, Theano, nor the names of its contributors may be
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used to endorse or promote products derived from this software without
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specific prior written permission.
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doc/acknowledgement.rst

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* The developers of `NumPy <http://numpy.scipy.org/>`_. Theano is based on its ndarray object and uses much of its implementation.
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* The developers of `SciPy <http://scipy.org/>`_. Our sparse matrix support uses their sparse matrix objects. We also reuse other parts.
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* The developers of `Theano <https://github.com/Theano/Theano>`_
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* All `Pytensor contributors <https://github.com/pymc-devs/pytensor/graphs/contributors>`_.
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* All `PyTensor contributors <https://github.com/pymc-devs/pytensor/graphs/contributors>`_.
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* All Theano users that have given us feedback.
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* Our random number generator implementation on CPU and GPU uses the MRG31k3p algorithm that is described in:
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doc/conf.py

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project = "Pytensor"
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copyright = "Pytensor Developers, 2021; PyMC Developers, 2020-2021; 2008--2019, LISA lab"
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project = "PyTensor"
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copyright = "PyTensor Developers, 2021; PyMC Developers, 2020-2021; 2008--2019, LISA lab"
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("index", "pytensor.tex", "PyTensor Documentation", "PyTensor Developers", "manual"),
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doc/core_development_guide.rst

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Core Development Guide
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=======================
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The documentation of the core components of Pytensor is still a work in
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The documentation of the core components of PyTensor is still a work in
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* :ref:`pytensor_type` -- Tutorial for writing a new type in Pytensor. It
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* :ref:`pytensor_type` -- Tutorial for writing a new type in PyTensor. It
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* :ref:`views_and_inplace` -- This is somewhere between extending PyTensor and
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* :ref:`graph_rewriting` -- Tutorial on how graph rewriting works in PyTensor.
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* :ref:`pipeline` -- Describes the steps of compiling an Pytensor Function.
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* :ref:`pipeline` -- Describes the steps of compiling an PyTensor Function.
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* :ref:`sandbox_randnb` -- Description of how Pytensor deals with random
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* :ref:`sparse` -- Description of the ``sparse`` type in PyTensor.

doc/dev_start_guide.rst

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Resources
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See Also
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You can now test your environment/code by running ``pytest`` in the project's root

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