class_docstr: An aggregation operator that takes the feature-wise maximum across a
  set of elements.
  
  .. math::
      \mathrm{max}(\mathcal{X}) = \max_{\mathbf{x}_i \in \mathcal{X}}
      \mathbf{x}_i.
code: def forward(
      self,
      x: Tensor,
      index: Optional[Tensor] = None,
      ptr: Optional[Tensor] = None,
      dim_size: Optional[int] = None,
      dim: int = -2,
  ) -> Tensor:
      return self.reduce(x, index, ptr, dim_size, dim, reduce="max")
  
imports: import math
  from typing import Optional
  import torch
  from torch import Tensor
  from torch.nn import Parameter
  from torch_geometric.nn.aggr import Aggregation
  from torch_geometric.utils import softmax
label_desc: Use image node_id 1 for calling the MaxAggregation obj's underlying member method code with example usage: obj.forward(x, index, ptr, dim_size, dim) and returns: self