pymc-devs/pytensor
View on GitHubPyTensor allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays.
- Stars
- 644
- Forks
- 208
- Open beginner issues
- 4
- Indexed issues
- 341
- Avg merge
- 2d 14h
- Merged PRs (30d)
- 16
- Dominant language
- Python
- License
- No license data
- Last GitHub push
- Sep 18, 2026
- Latest indexed
- Sep 19, 2026
- Contributing guide
- Contributing guide
- Code of conduct
- Code of conduct
- Beginner labels
- help wanted
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Difficulty 2/5 1-3 hours Newbie friendliness 78/100
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Difficulty 5/5 Over a week Newbie friendliness 45/100
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enhancement refactor
Difficulty 4/5 3-5 days Newbie friendliness 55/100
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bug indexing mlx
Difficulty 2/5 1-3 hours Newbie friendliness 78/100
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enhancement linalg numba
Difficulty 3/5 1-2 days Newbie friendliness 84/100
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OpFromGraph shape inference vectorization
Difficulty 3/5 1-2 days Newbie friendliness 68/100
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graph rewriting performance vectorization
Difficulty 3/5 1-2 days Newbie friendliness 68/100
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graph rewriting linalg performance
Difficulty 2/5 1-3 hours Newbie friendliness 78/100
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bug
Difficulty 3/5 1-2 days Newbie friendliness 48/100
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maintenance refactor
Difficulty 4/5 3-5 days Newbie friendliness 50/100
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Difficulty 2/5 1-3 hours Newbie friendliness 84/100
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bug gradients indexing mlx
Difficulty 3/5 1-2 days Newbie friendliness 68/100
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enhancement help wanted linalg mlx
Difficulty 5/5 Over a week Newbie friendliness 30/100
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backend compatibility bug mlx
Difficulty 3/5 1-2 days Newbie friendliness 70/100
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Difficulty 5/5 Over a week Newbie friendliness 35/100
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numba performance
Difficulty 4/5 3-5 days Newbie friendliness 50/100
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bug shape inference
Difficulty 3/5 1-2 days Newbie friendliness 68/100
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bug torch
Difficulty 2/5 1-3 hours Newbie friendliness 72/100
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enhancement graph rewriting performance scan
Difficulty 3/5 1-2 days Newbie friendliness 58/100
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Difficulty 4/5 3-5 days Newbie friendliness 55/100
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Difficulty 2/5 1-3 hours Newbie friendliness 68/100
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Difficulty 2/5 1-3 hours Newbie friendliness 76/100
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Difficulty 2/5 1-3 hours Newbie friendliness 72/100
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bug
Difficulty 4/5 3-5 days Newbie friendliness 45/100
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Difficulty 4/5 3-5 days Newbie friendliness 48/100
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Difficulty 4/5 3-5 days Newbie friendliness 55/100
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numba performance request discussion
Difficulty 5/5 Over a week Newbie friendliness 48/100
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Difficulty 5/5 Over a week Newbie friendliness 35/100
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bug
Difficulty 4/5 3-5 days Newbie friendliness 58/100
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bug
Difficulty 4/5 3-5 days Newbie friendliness 52/100
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Difficulty 1/5 Under an hour Newbie friendliness 86/100
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Difficulty 4/5 3-5 days Newbie friendliness 52/100
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backend compatibility help wanted
Difficulty 5/5 Over a week Newbie friendliness 35/100
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enhancement graph rewriting memory opt numba performance
Difficulty 4/5 3-5 days Newbie friendliness 48/100
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gradients numba request discussion
Difficulty 4/5 3-5 days Newbie friendliness 48/100
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Op implementation
Difficulty 5/5 Over a week Newbie friendliness 35/100
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Difficulty 4/5 3-5 days Newbie friendliness 55/100
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docs
Difficulty 1/5 Under an hour Newbie friendliness 68/100
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indexing Op implementation
Difficulty 4/5 3-5 days Newbie friendliness 48/100
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enhancement
Difficulty 3/5 1-2 days Newbie friendliness 50/100
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graph rewriting performance
Difficulty 4/5 3-5 days Newbie friendliness 48/100
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graph rewriting
Difficulty 4/5 3-5 days Newbie friendliness 48/100
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graph rewriting needs info Op implementation
Difficulty 5/5 Over a week Newbie friendliness 35/100
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beginner friendly graph rewriting
Difficulty 3/5 1-2 days Newbie friendliness 74/100
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Add CAReduce(DimShuffle(x)) -> CAReduce(x) rewrite when DimShuffle is a no-op for the reduction Opengraph rewriting
Difficulty 3/5 1-2 days Newbie friendliness 45/100
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docs
Difficulty 2/5 1-3 hours Newbie friendliness 65/100
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performance
Difficulty 4/5 3-5 days Newbie friendliness 48/100
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enhancement mlx
Difficulty 5/5 Over a week Newbie friendliness 45/100
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enhancement mlx
Difficulty 4/5 3-5 days Newbie friendliness 58/100