Here is the documentation of pytorch_geometric.data.Data
PARAMETERS:
x (Tensor, optional) – Node feature matrix with shape [num_nodes, num_node_features]. 
(default: None)

edge_index (LongTensor, optional) – Graph connectivity in COO format with shape [2, 
num_edges]. (default: None)

edge_attr (Tensor, optional) – Edge feature matrix with shape [num_edges, 
num_edge_features]. (default: None)

y (Tensor, optional) – Graph-level or node-level ground-truth labels with arbitrary 
shapes. (default: None)

pos (Tensor, optional) – Node position matrix with shape [num_nodes, num_dimensions]. 
(default: None)

**kwargs (optional) – Additional attributes.

According to this documentation, the shape of X should be of shape [num_nodes, num_node_features]. But what should I do if my node_features is multi-dimensional, for example, images data?