title: Item Assignment Tensorflow 2.0 - TypeError: 'tensorflow.python.framework.ops.EagerTensor' object does not support item assignment
body: <p>I am using Tensorflow 2.0, and am trying to update slices within my tensor.</p>
  
  <p>Using a plain item assignment like in PyTorch, it does not work.</p>
  
  <pre class="lang-py prettyprint-override"><code>import tensorflow as tf
  
  tensor = tf.ones((10, 192, 85))
  tensor[:, :, 0] = tf.math.sigmoid([:, :, 0])
  
  &gt;&gt;&gt; Output
  TypeError: 'tensorflow.python.framework.ops.EagerTensor' object does not support item assignment
  </code></pre>
  
  <p>I see that it is possible to use <code>tf.tensor_scatter_nd_update</code>, but it feels too verbose to be efficient, as I have to separately derive the indices to be updated. Thus, I am not sure if this is the best way to do item assignment in eager tensors (I need the code block below to achieve the simpler "PyTorch 2-liner style" above):</p>
  
  <pre class="lang-py prettyprint-override"><code>import tensorflow as tf
  
  def get_indices(tensor):
    indices = []
    for i in range(tensor.shape[0]):
      for j in range(tensor.shape[1]):
        indices.append([i, j, 0])
    return tf.convert_to_tensor(indices)
  
  tensor = tf.ones((10, 192, 85))
  indices = get_indices(tensor)
  updates = tf.reshape(tf.math.sigmoid(tensor[:, :, 0]), (-1,))
  tensor = tf.tensor_scatter_nd_update(tensor, indices, updates)
  </code></pre>
  
  <p>Is there an easier/more efficient way to do item assignment of <code>EagerTensor</code>s in Tensorflow 2.0?</p>