scikit-learn: TSNE with correlation metric: ValueError: Distance matrix 'X' must be symmetric

from sklearn.manifold import TSNE
import numpy as np
np.random.seed(42)

data = np.random.rand(10, 3)
data[-1, :] = 0

model = TSNE(metric="correlation")
model.fit_transform(data)

TSNE raises an obscure error, when the data set contains rows with a standard deviation 0 and therefore undefined correlations:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-20-658142c1e315> in <module>()
      1 model = TSNE(metric="correlation")
----> 2 res = model.fit_transform(data)
      3 ran = model.fit_transform(ran_data)

/Users/ch/miniconda/envs/sci34/lib/python3.4/site-packages/sklearn/manifold/t_sne.py in fit_transform(self, X, y)
    522             Embedding of the training data in low-dimensional space.
    523         """
--> 524         self.fit(X)
    525         return self.embedding_

/Users/ch/miniconda/envs/sci34/lib/python3.4/site-packages/sklearn/manifold/t_sne.py in fit(self, X, y)
    447         self.training_data_ = X
    448 
--> 449         P = _joint_probabilities(distances, self.perplexity, self.verbose)
    450         if self.init == 'pca':
    451             pca = RandomizedPCA(n_components=self.n_components,

/Users/ch/miniconda/envs/sci34/lib/python3.4/site-packages/sklearn/manifold/t_sne.py in _joint_probabilities(distances, desired_perplexity, verbose)
     52     P = conditional_P + conditional_P.T
     53     sum_P = np.maximum(np.sum(P), MACHINE_EPSILON)
---> 54     P = np.maximum(squareform(P) / sum_P, MACHINE_EPSILON)
     55     return P
     56 

/Users/ch/miniconda/envs/sci34/lib/python3.4/site-packages/scipy/spatial/distance.py in squareform(X, force, checks)
   1479             raise ValueError('The matrix argument must be square.')
   1480         if checks:
-> 1481             is_valid_dm(X, throw=True, name='X')
   1482 
   1483         # One-side of the dimensions is set here.

/Users/ch/miniconda/envs/sci34/lib/python3.4/site-packages/scipy/spatial/distance.py in is_valid_dm(D, tol, throw, name, warning)
   1562                 if name:
   1563                     raise ValueError(('Distance matrix \'%s\' must be '
-> 1564                                      'symmetric.') % name)
   1565                 else:
   1566                     raise ValueError('Distance matrix must be symmetric.')

ValueError: Distance matrix 'X' must be symmetric