tzrec/datasets/data_parser.py [468:486]:
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            sparse_feature = KeyedJaggedTensor(
                keys=keys,
                values=torch.cat(values, dim=-1),
                lengths=torch.cat(lengths, dim=-1),
                weights=torch.cat(weights, dim=-1)
                if len(dg_has_weight_keys) > 0
                else None,
                stride=lengths[0].size(0),  # input_data['input_batch_size']
                length_per_key=[x.numel() for x in values],
            )
            sparse_features[dg] = sparse_feature
            if len(mulval_keys) > 0:
                sequence_mulval_length = KeyedJaggedTensor(
                    keys=mulval_keys,
                    values=torch.cat(mulval_key_lengths, dim=-1),
                    lengths=torch.cat(mulval_seq_lengths, dim=-1),
                )
                sequence_mulval_lengths[dg] = sequence_mulval_length
        return sparse_features, sequence_mulval_lengths
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tzrec/datasets/data_parser.py [608:626]:
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            sparse_feature = KeyedJaggedTensor(
                keys=keys,
                values=torch.cat(values, dim=-1),
                lengths=torch.cat(lengths, dim=-1),
                weights=torch.cat(weights, dim=-1)
                if len(dg_has_weight_keys) > 0
                else None,
                stride=lengths[0].size(0),  # input_data['input_batch_size']
                length_per_key=[x.numel() for x in values],
            )
            sparse_features[dg] = sparse_feature
            if len(mulval_keys) > 0:
                sequence_mulval_length = KeyedJaggedTensor(
                    keys=mulval_keys,
                    values=torch.cat(mulval_key_lengths, dim=-1),
                    lengths=torch.cat(mulval_seq_lengths, dim=-1),
                )
                sequence_mulval_lengths[dg] = sequence_mulval_length
        return sparse_features, sequence_mulval_lengths
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