https://github.com/epronovost/eincheck

Tensor shape checks inspired by einstein notation
https://github.com/epronovost/eincheck

deep-learning jax numpy pytorch tensor tensorflow

Last synced: about 1 month ago
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Tensor shape checks inspired by einstein notation

• Host: GitHub
• URL: https://github.com/epronovost/eincheck
• Owner: EPronovost
• License: mit
• Created: 2022-10-29T02:38:07.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2024-09-12T04:32:30.000Z (2 months ago)
• Last Synced: 2024-10-11T00:22:12.854Z (about 1 month ago)
• Topics: deep-learning, jax, numpy, pytorch, tensor, tensorflow
• Language: Python
• Homepage:
• Size: 203 KB
• Stars: 3
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# eincheck

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Tensor shape checks inspired by einstein notation

## Overview

This library has three main functions:

* `check_shapes` takes tuples of `(Tensor, shape)` and checks that all the Tensors match the shapes

```

check_shapes((x, "i 3"), (y, "i 3"))

```

* `check_func` is a function decorator to check the input and output shapes of a function

```

@check_func("*i x, *i y -> *i (x + y)")

def concat(a, b):

    return np.concatenate([a, b], -1)

```

* `check_data` is a class decorator to check the fields of a data class

```

@check_data(start="i 2", end="i 2")

class LineSegment2D(NamedTuple):

    start: torch.Tensor

    end: torch.Tensor

```

For more info, [read the docs!](https://eincheck.readthedocs.io/en/main)