- tensor_annotations VS dex-lang
- tensor_annotations VS torchtyping
- tensor_annotations VS miniF2F
- tensor_annotations VS TablaM
- tensor_annotations VS tiny-cuda-nn
- tensor_annotations VS MindsDB
- tensor_annotations VS FL
- tensor_annotations VS einops
- tensor_annotations VS jaxtyping
- tensor_annotations VS hasktorch
Tensor_annotations Alternatives
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einops
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
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jaxtyping
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tensor_annotations reviews and mentions
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[D] Have their been any attempts to create a programming language specifically for machine learning?
Not really an answer to your question, but there are Python packages that try to solve the problem of tensor shapes that you mentioned, e.g. https://github.com/patrick-kidger/torchtyping or https://github.com/deepmind/tensor_annotations
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Matrix Multiplication Inches Closer to Mythic Goal
I've explored this space quite a bit. In my view, static checking should be the goal.
https://github.com/deepmind/tensor_annotations and tsastanley seem to be the most far along. I've developed a mypy plugin that does similarly off of the "Named Tensor" dynamic feature (which isn't well supported yet), but haven't released it yet.
Stats
google-deepmind/tensor_annotations is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of tensor_annotations is Python.
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