Allow passing numpy arrays to transpose #1258
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velochy
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ricardoV94
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Mar 1, 2025
tests/tensor/test_variable.py
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| assert_array_equal(X.transpose(1, 0).eval({X: x}), x.transpose(1, 0)) | ||
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| # Test handing in lists and np.arrays | ||
| assert_array_equal(X.transpose([1, 0]).eval({X: x}), x.transpose([1, 0])) |
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No need to eval these, having confirmed the above works, you can use assert equal_computations([X.tranpose(array(...))], [X.transpose(list(...))]) that confirms you have the expected graph.
You can even check the two cases at once
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Not sure how checking them at the same time would look like, but fixed code to do equal_computation now.
Also added the tuple alongside list and np.array as that was the third option
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you can have multiple variables in each side of equal_computations, such as equal_computations([var1, var2], [var3, var4]), which will check if var1 is equal to var3 and var2 to var4
ricardoV94
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ricardoV94
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Mar 3, 2025
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Description
Added np.ndarray as a typecheck along tuple and list for dimshuffle so tensor.transpose would accept numpy inputs.
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📚 Documentation preview 📚: https://pytensor--1258.org.readthedocs.build/en/1258/