title: Quantization not yet supported for op: 'DEQUANTIZE' for tensorflow 2.x
body: <p>I am conducting QAT by keras on a resnet model and I got this problem while converting to tflite full integer model. I have tried the newest version tf-nightly, but it does not solve the problem.
  I use quantization annotated model for Batch Normalization quantization during QAT</p>
  <p><a href="https://i.stack.imgur.com/mJOR6.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/mJOR6.png" alt="The annotate model" /></a></p>
  <p>Here is the code I use to convert my model:</p>
  <pre><code>converter = tf.lite.TFLiteConverter.from_keras_model(layer)
  def representative_dataset_gen():
      for _ in range(50):
          batch = next(train_generator)
          img = np.expand_dims(batch[0][0],0).astype(np.float32)
          yield [img]
  converter.optimizations = [tf.lite.Optimize.DEFAULT]
  converter.representative_dataset = representative_dataset_gen
  converter.target_spec.supported_ops = [
    tf.lite.OpsSet.TFLITE_BUILTINS_INT8
  ]
  converter.experimental_new_converter = True
  
  # converter.target_spec.supported_types = [tf.int8]
  converter.inference_input_type = tf.int8  # or tf.uint8
  converter.inference_output_type = tf.int8  # or tf.uint8
  quantized_tflite_model = converter.convert()
  with open(&quot;test_try_v2.tflite&quot;, 'wb') as f:
      f.write(quantized_tflite_model)
  </code></pre>
  <p>if I bypass this error by adding <code>tf.lite.OpsSet.TFLITE_BUILTINS</code> to &quot;target_spec.supported_ops&quot;, I still got this DEQUANTIZE problem at edge_tpu compiler</p>
  <pre><code>ERROR: :61 op_context.input-&gt;type == kTfLiteUInt8 || op_context.input-&gt;type == kTfLiteInt8 || op_context.input-&gt;type == kTfLiteInt16 || op_context.input-&gt;type == kTfLiteFloat16 was not true.
  ERROR: Node number 3 (DEQUANTIZE) failed to prepare.
  
  ERROR: :61 op_context.input-&gt;type == kTfLiteUInt8 || op_context.input-&gt;type == kTfLiteInt8 || op_context.input-&gt;type == kTfLiteInt16 || op_context.input-&gt;type == kTfLiteFloat16 was not true.
  ERROR: Node number 3 (DEQUANTIZE) failed to prepare.
  </code></pre>