code: def apply_beamforming_vector(
      beamform_vector: Union[torch.Tensor, ComplexTensor],
      mix: Union[torch.Tensor, ComplexTensor],
  ) -> Union[torch.Tensor, ComplexTensor]:
      # (..., C) x (..., C, T) -> (..., T)
      es = einsum("...c,...ct->...t", beamform_vector.conj(), mix)
      return es
  
imports: from typing import List, Union
  import torch
  from packaging.version import parse
  from torch_complex import functional
  from torch_complex.tensor import ComplexTensor
  from espnet2.enh.layers.complex_utils import cat, complex_norm, einsum, inverse, is_complex, is_torch_complex_tensor, matmul, reverse, solve, to_double
label_desc: Use image node_id 6 for calling a global function with example usage: apply_beamforming_vector(beamform_vector, mix) and returns: es