code: def get_power(signal, dim=-2) -> torch.Tensor:
      """Calculates power for `signal`
  
      Args:
          signal : Single frequency signal
              with shape (F, C, T).
          axis: reduce_mean axis
      Returns:
          Power with shape (F, T)
  
      """
      power = signal.real**2 + signal.imag**2
      power = power.mean(dim=dim)
      return power
  
file_path: espnet/espnet2/enh/layers/wpe.py
imports: from typing import Tuple, Union
  import torch
  import torch.nn.functional
  import torch_complex.functional
  from packaging.version import parse
  from torch_complex.tensor import ComplexTensor
  from espnet2.enh.layers.complex_utils import einsum, matmul, reverse
label_desc: Use image node_id 2 for calling a global function with example usage: get_power(signal, dim) and returns: power