title: Operation has type int32 that does not match type int64
body: <p>I am attempting to train some data using a DNN provided by <code>tflearn</code>. My <code>data</code> variable has a shape of <code>(6605, 32)</code> and my <code>labels</code> data has a shape of <code>(6605,)</code> which I reshape below to <code>(6605, 1)</code>...</p>
  <pre><code># Target label used for training
  labels = np.array(data[label], dtype=np.float32)
  
  # Reshape target label from (6605,) to (6605, 1)
  labels = tf.reshape(labels, shape=[-1, 1])
  
  # Data for training minus the target label.
  data = np.array(data.drop(label, axis=1), dtype=np.float32)
  
  # DNN
  net = tflearn.input_data(shape=[None, 32])
  net = tflearn.fully_connected(net, 32)
  net = tflearn.fully_connected(net, 32)
  net = tflearn.fully_connected(net, 1, activation='softmax')
  net = tflearn.regression(net)
  
  # Define model.
  model = tflearn.DNN(net)
  model.fit(data, labels, n_epoch=10, batch_size=16, show_metric=True)
  </code></pre>
  <p>After running this I get two errors, the first is...</p>
  <blockquote>
  <p>ValueError: Tensor conversion requested dtype int64 for Tensor with dtype int32: 'Tensor(&quot;strided_slice/stack_4:0&quot;, shape=(1,), dtype=int32)'</p>
  </blockquote>
  <p>And the second error is...</p>
  <blockquote>
  <p>During handling of the above exception, another exception occurred:</p>
  <p>TypeError: Input 'strides' of 'StridedSlice' Op has type int32 that does not match type int64 of argument 'begin'.</p>
  </blockquote>
  <p>I can't figure out how to solve the issue. So one approach I took was changing the <code>dtype</code> for <code>labels</code> and <code>data</code> to <code>int64</code>...</p>
  <pre><code># Target label used for training
  labels = np.array(data[label], dtype=np.int64)
  
  # Reshape target label from (6605,) to (6605, 1)
  labels = tf.reshape(labels, shape=[-1, 1])
  
  # Data for training minus the target label.
  data = np.array(data.drop(label, axis=1), dtype=np.int64)
  </code></pre>
  <p>But if I do this I still get the same errors. How can I fix this?</p>