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class CoorderMeesho(BaseData): r""" The content of the CoorderMeesho dataset includes the following: - ``num_classes``: The number of classes: :math:`2`. - ``num_vertices``: The number of vertices: :math:`66,790`. - ``num_edges``: The number of edges: :math:`27528`. - ``dim_features``: The dimension of features: :math:`10`. - ``features``: The vertex feature matrix. ``torch.Tensor`` with size :math:`(66, 790 \times 10)`. - ``edge_list``: The edge list. ``List`` with length :math:`27528`. - ``labels``: The label list. ``torch.LongTensor`` with size :math:`(66,790, )`. - ``train_mask``: The train mask. ``torch.BoolTensor`` with size :math:`(66,790, )`. - ``val_mask``: The validation mask. ``torch.BoolTensor`` with size :math:`(66,790, )`. - ``test_mask``: The test mask. ``torch.BoolTensor`` with size :math:`(66,790, )`. Args: ``data_root`` (``str``, optional): The ``data_root`` has stored the data. If set to ``None``, this function will auto-download from server and save into the default direction ``~/.dhg/datasets/``. Defaults to ``None``. """ def __init__(self, data_root: Optional[str] = None) -> None: super().__init__("coorder_meesho", data_root) self._content = { "num_classes": 2, "num_vertices": 66790, "num_edges": 27528, "dim_features": 10, "features": { "upon": [{"filename": features, "md5": "1b00a68b983d48bd57e7203d905da27a",}], "loader": load_from_pickle, "preprocess": [to_tensor, partial(norm_ft, ord=1)], }, "edge_list": { "upon": [{"filename": edge_list, "md5": "4492346f6776ab5f57fd2f85fb1e8fcd",}], "loader": load_from_pickle, }, "labels": { "upon": [{"filename": labels, "md5": "a972ba9aa9045ea9d6ca3e6a1f6022e5",}], "loader": load_from_pickle, "preprocess": [to_long_tensor], }, "train_mask": { "upon": [{"filename": train_mask, "md5": "8a05bd0e00183c64824b20e0bb28e65f",}], "loader": load_from_pickle, "preprocess": [to_bool_tensor], }, "val_mask": { "upon": [{"filename": val_mask, "md5": "eef08c056ac2fa3353cce714ea95907b",}], "loader": load_from_pickle, "preprocess": [to_bool_tensor], }, "test_mask": { "upon": [{"filename": val_mask, "md5": "a870dae84a8e0aa9aebad4bde1231857",}], "loader": load_from_pickle, "preprocess": [to_bool_tensor], }, }
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