title: ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() while using csr_matrix
body: <p>I have 4 sparse matrixes with following dimensional:</p>
  
  <pre><code>X_train_content_sparse.shape
  (62313, 100000)
  
  X_train_title_sparse.shape
  (62313, 100000)
  
  X_train_author_sparse.shape
  (62313,31540)
  
  X_train_time_features_sparse.shape
  (62313, 7)
  </code></pre>
  
  <p>And then I stack arrays in sequence horizontally. </p>
  
  <pre><code>X_train_sparse = hstack([X_train_content_sparse, X_train_title_sparse,
                                      X_train_author_sparse, X_train_time_features_sparse])
  </code></pre>
  
  <p>After that I transform this array of sparse matrixes into a sparse matrix.
  I apply <code>csr_matrix(X_train_sparse)</code> and I receive such error:</p>
  
  <blockquote>
    <p>ValueError: The truth value of an array with more than one element is
    ambiguous. Use a.any() or a.all().</p>
  </blockquote>
  
  <pre><code>&gt;X_train_sparse
  array([ &lt;62313x100000 sparse matrix of type '&lt;class 'numpy.float64'&gt;'
      with 68519885 stored elements in Compressed Sparse Row format&gt;,
         &lt;62313x100000 sparse matrix of type '&lt;class 'numpy.float64'&gt;'
      with 795892 stored elements in Compressed Sparse Row format&gt;,
         &lt;62313x31540 sparse matrix of type '&lt;class 'numpy.uint8'&gt;'
      with 62313 stored elements in Compressed Sparse Row format&gt;,
         &lt;62313x7 sparse matrix of type '&lt;class 'numpy.int64'&gt;'
      with 176241 stored elements in Compressed Sparse Row format&gt;], dtype=object)
  </code></pre>