graphlearn_torch/python/distributed/dist_dataset.py [154:171]:
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    if node_feat_data is not None:
      node_cache_ratio, node_feat, node_feat_id2idx, node_feat_pb = \
        _cat_feature_cache(partition_idx, node_feat_data, self.node_pb)
      self.init_node_features(
        node_feat, node_feat_id2idx, None, node_cache_ratio,
        device_group_list, device, feature_with_gpu, dtype=None
      )
      self._node_feat_pb = node_feat_pb

    # load edge feature partition
    if edge_feat_data is not None:
      edge_cache_ratio, edge_feat, edge_feat_id2idx, edge_feat_pb = \
        _cat_feature_cache(partition_idx, edge_feat_data, self.edge_pb)
      self.init_edge_features(
        edge_feat, edge_feat_id2idx, edge_cache_ratio,
        device_group_list, device, feature_with_gpu, dtype=None
      )
      self._edge_feat_pb = edge_feat_pb
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graphlearn_torch/python/distributed/dist_table_dataset.py [328:345]:
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    if node_feat_data is not None:
      node_cache_ratio, node_feat, node_feat_id2idx, node_feat_pb = \
        _cat_feature_cache(partition_idx, node_feat_data, self.node_pb)
      self.init_node_features(
        node_feat, node_feat_id2idx, None, node_cache_ratio,
        device_group_list, device, feature_with_gpu, dtype=None
      )
      self._node_feat_pb = node_feat_pb

    # load edge feature
    if edge_feat_data is not None:
      edge_cache_ratio, edge_feat, edge_feat_id2idx, edge_feat_pb = \
        _cat_feature_cache(partition_idx, edge_feat_data, self.edge_pb)
      self.init_edge_features(
        edge_feat, edge_feat_id2idx, edge_cache_ratio,
        device_group_list, device, feature_with_gpu, dtype=None
      )
      self._edge_feat_pb = edge_feat_pb
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