RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility

I have this error for trying to load a saved SVM model. I have tried uninstalling sklearn, NumPy and SciPy, reinstalling the latest versions all-together again (using pip). I am still getting this error. Why?

    In [1]: import sklearn; print sklearn.__version__
    In [3]: import numpy; print numpy.__version__
    In [5]: import scipy; print scipy.__version__
    In [7]: import pandas; print pandas.__version__

    In [10]: clf = joblib.load('model/trained_model.pkl')
    RuntimeWarning                            Traceback (most recent call last)
    <ipython-input-10-5e5db1331757> in <module>()
    ----> 1 clf = joblib.load('sentiment_classification/model/trained_model.pkl')

    /usr/local/lib/python2.7/dist-packages/sklearn/externals/joblib/numpy_pickle.pyc in load(filename, mmap_mode)
        573                     return load_compatibility(fobj)
    --> 575                 obj = _unpickle(fobj, filename, mmap_mode)
        577     return obj

    /usr/local/lib/python2.7/dist-packages/sklearn/externals/joblib/numpy_pickle.pyc in _unpickle(fobj, filename, mmap_mode)
        505     obj = None
        506     try:
    --> 507         obj = unpickler.load()
        508         if unpickler.compat_mode:
        509             warnings.warn("The file '%s' has been generated with a "

    /usr/lib/python2.7/pickle.pyc in load(self)
        862             while 1:
        863                 key = read(1)
    --> 864                 dispatch[key](self)
        865         except _Stop, stopinst:
        866             return stopinst.value

    /usr/lib/python2.7/pickle.pyc in load_global(self)
       1094         module = self.readline()[:-1]
       1095         name = self.readline()[:-1]
    -> 1096         klass = self.find_class(module, name)
       1097         self.append(klass)
       1098     dispatch[GLOBAL] = load_global

    /usr/lib/python2.7/pickle.pyc in find_class(self, module, name)
       1128     def find_class(self, module, name):
       1129         # Subclasses may override this
    -> 1130         __import__(module)
       1131         mod = sys.modules[module]
       1132         klass = getattr(mod, name)

    /usr/local/lib/python2.7/dist-packages/sklearn/svm/ in <module>()
         11 # License: BSD 3 clause (C) INRIA 2010
    ---> 13 from .classes import SVC, NuSVC, SVR, NuSVR, OneClassSVM, LinearSVC, \
         14         LinearSVR
         15 from .bounds import l1_min_c

    /usr/local/lib/python2.7/dist-packages/sklearn/svm/ in <module>()
          2 import numpy as np
    ----> 4 from .base import _fit_liblinear, BaseSVC, BaseLibSVM
          5 from ..base import BaseEstimator, RegressorMixin
          6 from ..linear_model.base import LinearClassifierMixin, SparseCoefMixin, \

    /usr/local/lib/python2.7/dist-packages/sklearn/svm/ in <module>()
          6 from abc import ABCMeta, abstractmethod
    ----> 8 from . import libsvm, liblinear
          9 from . import libsvm_sparse
         10 from ..base import BaseEstimator, ClassifierMixin

    __init__.pxd in init sklearn.svm.libsvm (sklearn/svm/libsvm.c:10207)()

    RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 80

UPDATE: OK, by following here, and

    pip uninstall -y scipy scikit-learn
    pip install --no-binary scipy scikit-learn

The error has now gone, though I still have no idea why it occurred in the first place...

According to MAINT: silence Cython warnings about changes dtype/ufunc size. - numpy/numpy:

These warnings are visible whenever you import scipy (or another package) that was compiled against an older numpy than is installed.

and the checks are inserted by Cython (hence are present in any module compiled with it).

Long story short, these warnings should be benign in the particular case ofnumpy , and these messages are filtered out sincenumpy 1.8 (the branch this commit went onto). While scikit-learn 0.18.1 is compiled against numpy 1.6.1.

To filter these warnings yourself , you can do the same as the patch does:

    import warnings
    warnings.filterwarnings("ignore", message="numpy.dtype size changed")
    warnings.filterwarnings("ignore", message="numpy.ufunc size changed")

Of course, you can just recompile all affected modules from source against your localnumpy with pip install --no-binary :all:¹ instead if you have the balls tools for that.

Longer story: the patch's proponent claims there should be no risk specifically with numpy, and 3rd-party packages are intentionally built against older versions:

[Rebuilding everything against current numpy is] not a feasible solution, and certainly shouldn't be necessary. Scipy (as many other packages) is compatible with a number of versions of numpy. So when we distribute scipy binaries, we build them against the lowest supported numpy version (1.5.1 as of now) and they work with 1.6.x, 1.7.x and numpy master as well.

The real correct would be for Cython only to issue warnings when the size of dtypes/ufuncs has changes in a way that breaks the ABI, and be silent otherwise.

As a result, Cython's devs agreed to trust the numpy team with maintaining binary compatibility by hand, so we can probably expect that using versions with breaking ABI changes would yield a specially-crafted exception or some other explicit show-stopper.

¹The previously available --no-use-wheel option has been removed since pip 10.0.0.