title: How to create a TF Dataset from a tuple of tensor? (and best practices)
body: <p>I'm having some problems with the creation of a custom Dataset.
  Right now i managed to get a generator function:</p>
  <pre><code>def dataset_generator():
  for path in pathlist_img:
      img, labels = process_path(path)
      yield img, labels 
  </code></pre>
  <p>It returns two tensorflow tensor: the first one of shape=(720, 1280, 3), dtype=uint8, and the second one of shape=(?, 14), dtype=float32, where &quot;?&quot; means that it depends on the image (it's an object detection dataset, so the number of instances recognized isn't fixed).</p>
  <p>I would like to have a Dataset with my images associated with my labels, so that's why im yielding tuples.</p>
  <p>The problem is that my dataset</p>
  <pre><code>dataset = tf.data.Dataset.from_generator(dataset_generator, ((tf.uint8, tf.uint8, tf.uint8),(tf.float32, tf.float32)))
  </code></pre>
  <p>it's just a</p>
  <pre><code>&lt;FlatMapDataset shapes: ((&lt;unknown&gt;, &lt;unknown&gt;, &lt;unknown&gt;), (&lt;unknown&gt;, &lt;unknown&gt;)), types: ((tf.uint8, tf.uint8, tf.uint8), (tf.float32, tf.float32))&gt;
  </code></pre>
  <p>And doesn't seem to contain anything, or at least i cant get anything out of it.</p>
  <p>Is there some best practices to build a Dataset from images and labels file?
  How can i fix the problem?</p>