code: def complex_mul_t(x: Tensor, y: Tensor) -> Tensor:
      """
      Compute complex-valued multiplication. Supports Ndim inputs with last dim equal to 2 (real/imaginary channels)
  
      Args:
          x: Input tensor with 2 channels in the last dimension representing real and imaginary parts.
          y: Input tensor with 2 channels in the last dimension representing real and imaginary parts.
  
      Returns:
          Complex multiplication of x and y
      """
      if x.shape[-1] != 2 or y.shape[-1] != 2:
          raise ValueError(
              f"last dim must be 2, but x.shape[-1] is {x.shape[-1]} and y.shape[-1] is {y.shape[-1]}."
          )
  
      real_part = x[..., 0] * y[..., 0] - x[..., 1] * y[..., 1]
      imag_part = x[..., 0] * y[..., 1] + x[..., 1] * y[..., 0]
  
      return torch.stack((real_part, imag_part), dim=-1)
  
file_path: MONAI/monai/apps/reconstruction/complex_utils.py
imports: from __future__ import annotations
  import re
  import numpy
  import torch
  from torch import Tensor
  from monai.config.type_definitions import NdarrayOrTensor
  from monai.utils.type_conversion import convert_to_numpy, convert_to_tensor
label_desc: Use image node_id 4 for calling a global function with example usage: complex_mul_t(x, y) and returns: torch