| |
| |
| @@ -322,7 +322,7 @@ |
| recycle_idx, |
| compute_loss=compute_loss): |
| if self.config.resample_msa_in_recycling: |
| - num_ensemble = batch_size // (self.config.num_recycle + 1) |
| + num_ensemble = batch_size |
| def slice_recycle_idx(x): |
| start = recycle_idx * num_ensemble |
| size = num_ensemble |
| @@ -341,53 +341,16 @@ |
| compute_loss=compute_loss, |
| ensemble_representations=ensemble_representations) |
| |
| - if self.config.num_recycle: |
| - emb_config = self.config.embeddings_and_evoformer |
| - prev = { |
| - 'prev_pos': jnp.zeros( |
| - [num_residues, residue_constants.atom_type_num, 3]), |
| - 'prev_msa_first_row': jnp.zeros( |
| - [num_residues, emb_config.msa_channel]), |
| - 'prev_pair': jnp.zeros( |
| - [num_residues, num_residues, emb_config.pair_channel]), |
| - } |
| - |
| - if 'num_iter_recycling' in batch: |
| - # Training time: num_iter_recycling is in batch. |
| - # The value for each ensemble batch is the same, so arbitrarily taking |
| - # 0-th. |
| - num_iter = batch['num_iter_recycling'][0] |
| - |
| - # Add insurance that we will not run more |
| - # recyclings than the model is configured to run. |
| - num_iter = jnp.minimum(num_iter, self.config.num_recycle) |
| - else: |
| - # Eval mode or tests: use the maximum number of iterations. |
| - num_iter = self.config.num_recycle |
| - |
| - body = lambda x: (x[0] + 1, # pylint: disable=g-long-lambda |
| - get_prev(do_call(x[1], recycle_idx=x[0], |
| - compute_loss=False))) |
| - if hk.running_init(): |
| - # When initializing the Haiku module, run one iteration of the |
| - # while_loop to initialize the Haiku modules used in `body`. |
| - _, prev = body((0, prev)) |
| - else: |
| - _, prev = hk.while_loop( |
| - lambda x: x[0] < num_iter, |
| - body, |
| - (0, prev)) |
| - else: |
| - prev = {} |
| - num_iter = 0 |
| + emb_config = self.config.embeddings_and_evoformer |
| + ret = do_call(prev=batch.pop("prev"), recycle_idx=0) |
| + ret["prev"] = get_prev(ret) |
| |
| - ret = do_call(prev=prev, recycle_idx=num_iter) |
| if compute_loss: |
| ret = ret[0], [ret[1]] |
| |
| if not return_representations: |
| del (ret[0] if compute_loss else ret)['representations'] # pytype: disable=unsupported-operands |
| - return ret |
| + return ret, (None, None) |
| |
| |
| class TemplatePairStack(hk.Module): |
| @@ -1730,9 +1693,7 @@ |
| True, |
| name='prev_msa_first_row_norm')( |
| batch['prev_msa_first_row']) |
| - msa_activations = jax.ops.index_add(msa_activations, 0, |
| - prev_msa_first_row) |
| - |
| + msa_activations = msa_activations.at[0].add(prev_msa_first_row) |
| if 'prev_pair' in batch: |
| pair_activations += hk.LayerNorm([-1], |
| True, |
|
|
