Trying to compute softmax values, getting AttributeError: 'list' object has no attribute 'T'
<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>