Closed sandrlom closed 2 years ago
@sandrlom Thanks! Looks great so far. The only problem is that we still need proper tests. They currently fail because inv
gets called with 1-dimensional array/tensor. Please include a non-trivial example (not just an identity-matrix).
@sandrlom Thanks! Tests fail because of formatting issues (please reformat the code using black / manually fix the issues reported by flake8).
Once tests pass, let's get this merged :)
Merging #48 (1578b94) into master (e593fda) will not change coverage. The diff coverage is
100.00%
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## master #48 +/- ##
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Files 16 16
Lines 1860 1870 +10
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Impacted Files | Coverage Δ | |
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eagerpy/tensor/tensor.py | 100.00% <ø> (ø) |
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eagerpy/framework.py | 100.00% <100.00%> (ø) |
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eagerpy/tensor/jax.py | 100.00% <100.00%> (ø) |
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eagerpy/tensor/numpy.py | 100.00% <100.00%> (ø) |
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eagerpy/tensor/pytorch.py | 100.00% <100.00%> (ø) |
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eagerpy/tensor/tensorflow.py | 100.00% <100.00%> (ø) |
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Thanks @sandrlom
First, thank you for providing this framework. This PR proposes the
inv
function which computes the inverse of an invertible matrix. Let me know if you'd like something changed.