docstr: Encodes the final boxes from proposals with deltas, using both the
  TensorFlow and the Numpy implementation.
  
  Asserts that both results are equal.
docstr_tok: ["Encodes","the","final","boxes","from","proposals","with","deltas",",","using","both","the","TensorFlow","and","the","Numpy","implementation",".","Asserts","that","both","results","are","equal","."]
code: def _decode(self, proposals, deltas):
      """
      Encodes the final boxes from proposals with deltas, using both the
      TensorFlow and the Numpy implementation.
  
      Asserts that both results are equal.
      """
      proposals_tf = tf.placeholder(tf.float32, shape=proposals.shape)
      deltas_tf = tf.placeholder(tf.float32, shape=deltas.shape)
  
      decoded_tf = decode_tf(proposals_tf, deltas_tf)
      with self.test_session() as sess:
          decoded_tf_val = sess.run(
              decoded_tf,
              feed_dict={
                  proposals_tf: proposals,
                  deltas_tf: deltas,
              },
          )
  
      decoded_np = decode_np(proposals, deltas)
  
      self.assertAllClose(decoded_np, decoded_tf_val)
      return decoded_np
  
file_path: luminoth/luminoth/utils/bbox_transform_test.py
imports: import numpy
  import tensorflow
  from luminoth.utils.bbox_transform import encode, decode, clip_boxes
  from luminoth.utils.bbox_transform_tf import encode, decode, clip_boxes
  from luminoth.utils.test.gt_boxes import generate_gt_boxes
label_desc: Use image node_id 3 for calling the BBoxTransformTest obj's underlying member method code with example usage: obj._decode(proposals, deltas) and returns: decoded_np