src/mlm/scorers.py [482:493]:
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        for batch_id, batch in enumerate(dataloader):

            batch_size = 0

            batch = zip(*[mx.gluon.utils.split_data(batch_compo, len(self._ctxs), batch_axis=0, even_split=False) for batch_compo in batch])

            for ctx_idx, (sent_idxs, token_ids, valid_length, masked_positions, token_masked_ids, normalization) in enumerate(batch):

                ctx = self._ctxs[ctx_idx]
                batch_size += sent_idxs.shape[0]
                token_ids = token_ids.as_in_context(ctx)
                valid_length = valid_length.as_in_context(ctx)
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src/mlm/scorers.py [828:841]:
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        for batch_id, batch in enumerate(dataloader):

            batch_size = 0

            # TODO: Write tests about batching over multiple GPUs and getting the same scores
            # TODO: SEE COMMENT ABOVE REGARDING FIXEDBUCKETSAMPLER
            batch = zip(*[mx.gluon.utils.split_data(batch_compo, len(self._ctxs), batch_axis=0, even_split=False) for batch_compo in batch])

            for ctx_idx, (sent_idxs, token_ids, valid_length, masked_positions, token_masked_ids, normalization) in enumerate(batch):

                ctx = self._ctxs[ctx_idx]
                batch_size += sent_idxs.shape[0]
                token_ids = token_ids.as_in_context(ctx)
                valid_length = valid_length.as_in_context(ctx)
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