using rowvar keyword in dpnp.cov #1371
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antonwolfy
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| if not rowvar and x1.shape[0] != 1: | ||
| x1 = x1.get_array() if isinstance(x1, dpnp_array) else x1 | ||
| x1 = dpnp_array._create_from_usm_ndarray(x1.mT) | ||
| x1 = dpnp.astype(x1, dpnp.float64) if x1_desc.dtype != dpnp.float64 else x1 |
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Please test that this works on Iris Xe, or other devices that do not support float64 data type.
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It will not work. @antonwolfy mentioned it is written like this because Numpy by default returns float64 for any input data type. The suggestion was to fix it in a separate ticket since it needs to correct dpnp c++ backend code.
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I've filed #1379 to add support of dpnp.cov on Iris Xe
| x1 = dpnp.astype(x1, dpnp.float64) if x1_desc.dtype != dpnp.float64 else x1 | ||
| x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False) | ||
| elif x1_desc.dtype != dpnp.float64: | ||
| x1 = dpnp.astype(x1, dpnp.float64) |
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Closes #1367
rowvarkeyword is added todpnp.covfunctiondpnp.dpnp_array.dpnp_array._create_from_usm_ndarray(x.get_array().mT)is used since it is faster thandpnp.transpose(x)since dpnp.tarnsport%timeit dpnp.cov(dpnp.dpnp_array.dpnp_array._create_from_usm_ndarray(x.get_array().mT))5.4 ms ± 121 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
%timeit dpnp.cov(dpnp.transpose(x))9.46 ms ± 455 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
%timeit dpnp.cov(x, rowvar=False)5.49 ms ± 352 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)