A small wrapper around pytest_regressions for Tensors
Project description
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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