title: create a function to compute all pairwise cosine similarity of the row vectors in a 2-D matrix using only numpy
body: <p>For example, given matrix</p>
  <pre><code>array([[ 0,  1,  2,  3,  4],
         [ 5,  6,  7,  8,  9],
         [10, 11, 12, 13, 14]])
  </code></pre>
  <p>it should return</p>
  <pre><code>array([[1.        , 0.91465912, 0.87845859],
         [0.91465912, 1.        , 0.99663684],
         [0.87845859, 0.99663684, 1.        ]])
  </code></pre>
  <p>where the <code>(i, j)</code> entry of the result is the cosine similarity between the row vector <code>arr[i]</code> and the row vector <code>arr[j]</code>: <code>cos_sim[i, j] == CosSim(arr[i], arr[j])</code>.</p>
  <p>As usual, the cosine similarity between two vectors  ,  is defined as:
  <a href="https://i.stack.imgur.com/pzbjX.jpg" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/pzbjX.jpg" alt="enter image description here" /></a></p>
  <p>This function should return a np.ndarray of shape (arr.shape[0], arr.shape[0])</p>