code: def commutator(A: torch.Tensor, B: torch.Tensor) -> torch.Tensor:
      """Compute the commutator of two matrices.
  
      Parameters
      ----------
      A : torch.Tensor
          The first matrix.
      B : torch.Tensor
          The second matrix.
  
      Returns
      -------
      torch.Tensor
          The commutator of the two matrices.
  
      Examples
      --------
      >>> A = torch.tensor([[1, 2], [3, 4]])
      >>> B = torch.tensor([[5, 6], [7, 8]])
      >>> commutator(A, B)
      tensor([[ -4, -12],
              [ 12,   4]])
      """
      return torch.matmul(A, B) - torch.matmul(B, A)
  
file_path: deepchem/deepchem/utils/equivariance_utils.py
imports: import math
  from typing import Optional
  import torch
label_desc: Use image node_id 5 for calling a global function with example usage: commutator(A, B) and returns: unknown