title: TypeError: unhashable type: 'numpy.ndarray' Tensorflow
body: <p>I'm working on adapting one of the MNIST tensorflow tutorials, and I receive this TypeError. According to <a href="https://stackoverflow.com/questions/38109489/how-to-test-a-model-in-tensor-flow">this question</a> you have to use a placeholder in the dictionary key because numpy arrays are mutable. I believe I'm doing that, but I'm still receiving this error.</p>
  <pre><code># Network Parameters
  n_input = 44100 # length of FFT
  n_classes = 6 # 6 instrument classes
  dropout = 0.75 # Dropout, probability to keep units
  
  # TF Graph input
  x = tf.placeholder(tf.float32, [None, n_input])
  y = tf.placeholder(tf.float32, [None, n_classes])
  keep_prob = tf.placeholder(tf.float32)
  </code></pre>
  <p>I fill up my batches and then pass them to the session.</p>
  <pre><code>for file_name in os.listdir('./Input_FFTs'):
      if file_name.endswith('.txt'):
          path = './Input_FFTs/' + file_name
          y, x = getData(path)
          batch_ys[count] = y
          batch_xs[count] = x
          count += 1
  sess.run(optimizer, feed_dict={x: batch_xs, y: batch_ys,
                                     keep_prob: dropout})
  </code></pre>
  <p>When I print and check the sizes of batch_xs and batch_ys, they are [batch_size, 44100] and [batch_size, 6] with the correct data. These match the expected sizes of the x and y placeholders.</p>
  <p>Can anyone tell me what the problem may be?</p>
  <p>Thank you!</p>