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- apply_ufunc gives wrong dtype with dask=parallelized and vectorized=True · 1 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
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622374824 | https://github.com/pydata/xarray/issues/4015#issuecomment-622374824 | https://api.github.com/repos/pydata/xarray/issues/4015 | MDEyOklzc3VlQ29tbWVudDYyMjM3NDgyNA== | mathause 10194086 | 2020-05-01T12:49:42Z | 2020-05-01T12:49:42Z | MEMBER | It works when you set ```python da2 = xr.apply_ufunc( func, da, vectorize=False, dask="parallelized", output_dtypes=[da.dtype], ) or when you pass your own ```python da2 = xr.apply_ufunc( func, da, vectorize=True, dask="parallelized", output_dtypes=[da.dtype], meta=da ) assert da2.dtype == da.dtype, "wrong dtype" ``` This also goes wrong if the DataArray has another dtype, e.g. ```python da = xr.DataArray(np.arange(234).reshape(2,3,4) da = da.chunk(dict(dim_1=1)) da2 = xr.apply_ufunc( func, da, vectorize=True, dask="parallelized", output_dtypes=[da.dtype], ) assert da2.dtype == da.dtype, "wrong dtype" ``` Indeed, the dtype of meta takes precedence over the dtype (https://github.com/dask/dask/blob/25005e19cc30e8b2877d4dadbaef378ee912bdc0/dask/array/core.py#L1022):
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apply_ufunc gives wrong dtype with dask=parallelized and vectorized=True 608974755 |
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