outputs of the 🤗 Transformers version multiple times against the intermediate outputs of the original implementation of
brand_new_bert in which case an efficient debugging environment of the original repository is absolutely
important. Here is some advice is to make your debugging environment as efficient as possible.
Find the best way of debugging intermediate results. Is the original repository written in PyTorch? Then you should
  probably take the time to write a longer script that decomposes the original model into smaller sub-components to
  retrieve intermediate values. Is the original repository written in Tensorflow 1? Then you might have to rely on
  TensorFlow print operations like tf.print to output
  intermediate values. Is the original repository written in Jax? Then make sure that the model is not jitted when
