title: How to get the required shape in numpy.linalg.norm
body: <p>If i have an numpy array</p>
  
  <pre><code>A=[[-4. -4. -4.]    #(6,3)
  [-8. -8. -8.]
  [-1. -1. -1.]
  [-5. -5. -5.]
  [ 2.  2.  2.]
  [-2. -2. -2.]]
  </code></pre>
  
  <p>I need norm of each row as (2,3)
  My solution is:</p>
  
  <pre><code>np.linalg.norm(A,axis=1)
  </code></pre>
  
  <p>My output is </p>
  
  <pre><code>[6.92820323  13.85640646   1.73205081   8.66025404   3.46410162  3.46410162]
  </code></pre>
  
  <p>Required output is:</p>
  
  <pre><code>[[  6.92820323  13.85640646]
  [  1.73205081   8.66025404]
  [  3.46410162   3.46410162]]
  </code></pre>
  
  <p>I want to get the required output just in one step without reshaping the resultant numpy array.because i have a large data set and i have to perform this operation repeatedly.
  Any suggestion ?  </p>