class_docstr: Concatenate with padding operating on pairs to combine with rev-nets.
class_docstr_tok: ["Concatenate","with","padding","operating","on","pairs","to","combine","with","rev-nets","."]
code: def reverse(
      self, output, weights=(), state=(), new_state=(), rng=None
  ):
      del state, new_state, rng, weights
      assert self._mode != "predict", "cannot reverse in predict mode"
      vecs_ed1, vecs_ed2, toks_e, toks_d = output
      vecs_d = _StripFromConcatenateWithPadding(
          vecs_ed1, toks_e, toks_d
      )
      mask_e = toks_e != 0
      mask_e_float = mask_e.astype(jnp.float32)
      vecs_e1 = (
          vecs_ed1[:, : toks_e.shape[1], :] * mask_e_float[:, :, None]
      )
      vecs_e2 = (
          vecs_ed2[:, : toks_e.shape[1], :] * mask_e_float[:, :, None]
      )
      return vecs_e1, vecs_e2, vecs_d, mask_e, toks_e, toks_d
  
imports: from trax import fastmath
  from trax import layers
  from trax.fastmath import numpy
  from trax.models.research import configurable_transformer
label_desc: Use image node_id 4 for calling the ConcatWithPadding2 obj's underlying member method code with example usage: obj.reverse(output, weights, state, new_state, rng) and returns: vecs_e1,  vecs_e2,  vecs_d,  mask_e,  toks_e,  toks_d