Remove mxnet kr

JeanKossaifi · Feb 26, 2021 · Dec 24, 2020 · Dec 25, 2020 · Dec 25, 2020 · Dec 25, 2020
commit c5fb2353dfdd0c3877840322180a99351400da7e
diff --git a/tensorly/backend/mxnet_backend.py b/tensorly/backend/mxnet_backend.py
@@ -306,59 +306,6 @@ def sort(tensor, axis, descending = False):
 
         return mx.ndarray.sort(tensor, axis=axis, is_ascend = is_ascend)
 
-    def kr(self, matrices, weights=None, mask=None):
-        """Khatri-Rao product of a list of matrices
-
-        This can be seen as a column-wise kronecker product.
-
-        Parameters
-        ----------
-        matrices : list of tensors
-            List of 2D tensors with the same number of columns, i.e.::
-
-                for i in len(matrices):
-                    matrices[i].shape = (n_i, m)
-
-        Returns
-        -------
-        khatri_rao_product : tensor of shape ``(prod(n_i), m)``
-            Where ``prod(n_i) = prod([m.shape[0] for m in matrices])`` (i.e. the
-            product of the number of rows of all the matrices in the product.)
-
-        Notes
-        -----
-        Mathematically:
-
-        .. math::
-            \\text{If every matrix } U_k \\text{ is of size } (I_k \\times R),\\\\
-            \\text{Then } \\left(U_1 \\bigodot \\cdots \\bigodot U_n \\right) \\\\
-            text{ is of size } (\\prod_{k=1}^n I_k \\times R)
-        """
-        # TODO: Remove this once mxnet.np is stable (as it provides einsum)
-        if len(matrices) < 2:
-            raise ValueError('kr requires a list of at least 2 matrices, but {} '
-                            'given.'.format(len(matrices)))
-
-        n_col = self.shape(matrices[0])[1]
-        for i, e in enumerate(matrices[1:]):
-            if not i:
-                if weights is None:
-                    res = matrices[0]
-                else:
-                    res = matrices[0]*self.reshape(weights, (1, -1))
-            s1, s2 = self.shape(res)
-            s3, s4 = self.shape(e)
-            if not s2 == s4 == n_col:
-                raise ValueError('All matrices should have the same number of columns.')
-
-            a = self.reshape(res, (s1, 1, s2))
-            b = self.reshape(e, (1, s3, s4))
-            res = self.reshape(a * b, (-1, n_col))
-
-        m = self.reshape(mask, (-1, 1)) if mask is not None else 1
-
-        return res*m
-
 
 for name in ['float64', 'float32', 'int64', 'int32']:
     MxnetBackend.register_method(name, getattr(numpy, name))