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import copy
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import warnings
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from collections import defaultdict
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- import struct
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+ import platform
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import inspect
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import numpy as np
@@ -555,10 +555,11 @@ def _more_tags(self):
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return {'multioutput' : True }
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- class _UnstableOn32BitMixin (object ):
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- """Mark estimators that are non-determinstic on 32bit. """
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+ class _UnstableArchMixin (object ):
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+ """Mark estimators that are non-determinstic on 32bit or PowerPC """
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def _more_tags (self ):
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- return {'non_deterministic' : _IS_32BIT }
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+ return {'non_deterministic' : (
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+ _IS_32BIT or platform .machine ().startswith (('ppc' , 'powerpc' )))}
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def is_classifier (estimator ):
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from .pls_ import _PLS
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- from ..base import _UnstableOn32BitMixin
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+ from ..base import _UnstableArchMixin
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__all__ = ['CCA' ]
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- class CCA (_PLS , _UnstableOn32BitMixin ):
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+ class CCA (_PLS , _UnstableArchMixin ):
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"""CCA Canonical Correlation Analysis.
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CCA inherits from PLS with mode="B" and deflation_mode="canonical".
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from scipy .sparse import eye , csr_matrix
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from scipy .sparse .linalg import eigsh
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- from ..base import BaseEstimator , TransformerMixin , _UnstableOn32BitMixin
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+ from ..base import BaseEstimator , TransformerMixin , _UnstableArchMixin
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from ..utils import check_random_state , check_array
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from ..utils .extmath import stable_cumsum
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from ..utils .validation import check_is_fitted
@@ -519,7 +519,7 @@ def locally_linear_embedding(
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class LocallyLinearEmbedding (BaseEstimator , TransformerMixin ,
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- _UnstableOn32BitMixin ):
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+ _UnstableArchMixin ):
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"""Locally Linear Embedding
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Read more in the :ref:`User Guide <locally_linear_embedding>`.
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