title: Vectorized implementation for `numpy.random.multivariate_normal`
body: <p>I am trying to use <code>numpy.random.multivariate_normal</code> to generate multiple samples where each sample is drawn from a multivariate Normal distribution with a different <code>mean</code> and <code>cov</code>. For example, if I would like to draw 2 samples, I tried</p>
  
  <pre><code>from numpy import random as rand
  
  means = np.array([[-1., 0.], [1., 0.]])
  covs = np.array([np.identity(2) for k in xrange(2)]) 
  rand.multivariate_normal(means, covs)
  </code></pre>
  
  <p>but this results in <code>ValueError: mean must be 1 dimensional</code>. Do I have to do a for loop for this? I thought that for functions like <code>rand.binomial</code> this is possible.</p>