title: Numpy (n, 1, m) to (n,m)
body: <p>I am working on a problem which involves a batch of 19 tokens each with 400 features. I get the shape (19,1,400) when concatenating two vectors of size (1, 200) into the final feature vector. If I squeeze the 1 out I am left with (19,) but I am trying to get (19,400). I have tried converting to list, squeezing and raveling but nothing has worked.</p>
  
  <p>Is there a way to convert this array to the correct shape?</p>
  
  <pre><code>def attn_output_concat(sample):
    out_h, state_h = get_output_and_state_history(agent.model, sample)
    attns = get_attentions(state_h)
    inner_outputs = get_inner_outputs(state_h)
    if len(attns) != len(inner_outputs):
      print 'Length err'
    else:
      tokens = [np.zeros((400))] * largest
      print(tokens.shape)
      for j, (attns_token, inner_token) in enumerate(zip(attns, inner_outputs)):
        tokens[j] = np.concatenate([attns_token, inner_token], axis=1)
      print(np.array(tokens).shape)
      return tokens
  </code></pre>