title: Trying to compute softmax values, getting AttributeError: 'list' object has no attribute 'T'
body: <p>First off, here is my code: </p>
  
  <pre><code>"""Softmax."""
  
  scores = [3.0, 1.0, 0.2]
  
  import numpy as np
  
  def softmax(x):
      """Compute softmax values for each sets of scores in x."""
      num = np.exp(x)
      score_len = len(x)
      y = [0] * score_len
      for index in range(1,score_len):
          y[index] = (num[index])/(sum(num))
      return y
  
  print(softmax(scores))
  
  # Plot softmax curves
  import matplotlib.pyplot as plt
  x = np.arange(-2.0, 6.0, 0.1)
  scores = np.vstack([x, np.ones_like(x), 0.2 * np.ones_like(x)])
  
  plt.plot(x, softmax(scores).T, linewidth=2)
  plt.show()
  </code></pre>
  
  <p>Now looking at <a href="https://stackoverflow.com/questions/5741372/syntax-in-python-t">this</a> question, I can tell that T is the transpose of my list. However, I seem to be getting the error: </p>
  
  <blockquote>
    <p>AttributeError: 'list' object has no attribute 'T'</p>
  </blockquote>
  
  <p>I do not understand what's going on here. Is my understanding of this entire situation wrong. I'm trying to get through the Google Deep Learning course and I thought that I could Python by implementing the programs, but I could be wrong. I currently know a lot of other languages like C and Java, but new syntax always confuses me. </p>