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A small wrapper around pytest_regressions for Tensors

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tensor_regression

A small wrapper to simplify using pytest_regressions with Tensors.

This adds the following to pytest_regressions:

  • Simple Tensor statistics (min, max, mean, std, shape, dtype, device, hash, etc.) are generated and saved in a .yaml file.
    • The simple statistics are used as a pre-check before comparing the full tensors.
    • These yaml files can be saved with git without having to worry about accidentally saving huge files.
  • Full tensors are moved to CPU and saved in a .npy file (same as ndarrays_regression), and these .npy files are gitignored.
  • Adds a --gen-missing argument (default True) which will generate any missing regression files without raising error, as opposed to pytest-regression's --regen-all which regenerates all regression files.

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