class_docstr: A combination for mixed complex & real representations.
code: def forward(
      self, xs: Sequence[torch.FloatTensor]
  ) -> torch.FloatTensor:  # noqa: D102
      if not any(x.is_complex() for x in xs):
          raise ValueError(
              f"{self.__class__} is a combination for complex representations, but none of the inputs was of "
              f"complex data type."
          )
      # split complex; repeat real
      xs_real, xs_imag = list(
          zip(
              *(
                  split_complex(x) if x.is_complex() else (x, x)
                  for x in xs
              )
          )
      )
      # separately combine real and imaginary parts
      x_re = self.real_combination(xs_real)
      x_im = self.imag_combination(xs_imag)
      # combine
      return combine_complex(x_re=x_re, x_im=x_im)
  
imports: import logging
  from abc import ABC, abstractmethod
  from typing import Any, Callable, Iterable, Mapping, Optional, Sequence, Tuple
  import torch
  from class_resolver import ClassResolver, Hint, HintOrType, OptionalKwargs
  from class_resolver.contrib.torch import activation_resolver, aggregation_resolver
  from torch import nn
  from ..utils import ExtraReprMixin, combine_complex, split_complex
label_desc: Use image node_id 2 for calling the ComplexSeparatedCombination obj's underlying member method code with example usage: obj.forward(xs) and returns: combine_complex