message: Update documentation to reflect input/output type support for QAT
diff: @@ -962,12 +962,12 @@ class TFLiteConverterV2(TFLiteFrozenGraphConverterV2):
  device.
  inference_input_type: Data type of the input layer. Note that integer types
  (tf.int8 and tf.uint8) are currently only supported for post training
  - integer quantization. (default tf.float32, must be in {tf.float32,
  - tf.int8, tf.uint8})
  + integer quantization and quantization aware training. (default tf.float32,
  + must be in {tf.float32, tf.int8, tf.uint8})
  inference_output_type: Data type of the output layer. Note that integer
  types (tf.int8 and tf.uint8) are currently only supported for post
  - training integer quantization. (default tf.float32, must be in
  - {tf.float32, tf.int8, tf.uint8})
  + training integer quantization and quantization aware training. (default
  + tf.float32, must be in {tf.float32, tf.int8, tf.uint8})
  experimental_new_converter: Experimental flag, subject to change. Enables
  MLIR-based conversion instead of TOCO conversion. (default True)
  