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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def add_jpeg_decoding(module_spec):
 """Adds operations that perform JPEG decoding and resizing to the graph.. Args: module_spec: The hub.ModuleSpec for the image module being used. Returns: Tensors for the node to feed JPEG data into, and the output of the preprocessing steps. """

  input_height, input_width = hub.get_expected_image_size(module_spec)
  input_depth = hub.get_num_image_channels(module_spec)
  jpeg_data = tf.placeholder(tf.string, name='DecodeJPGInput')
  decoded_image = tf.image.decode_jpeg(jpeg_data, channels=input_depth)
  # Convert from full range of uint8 to range [0,1] of float32.
  decoded_image_as_float = tf.image.convert_image_dtype(decoded_image,
                                                        tf.float32)
  decoded_image_4d = tf.expand_dims(decoded_image_as_float, 0)
  resize_shape = tf.stack([input_height, input_width])
  resize_shape_as_int = tf.cast(resize_shape, dtype=tf.int32)
  resized_image = tf.image.resize_bilinear(decoded_image_4d,
                                           resize_shape_as_int)
  return jpeg_data, resized_image