class_docstr: Compute "energy" concentration level for a tensor
  
  Args:
      dim (int):
          The dimension to measure.
      top_k_percents (List[float]):
          List of percentage values. For each value, the `measure`
          function will compute and return the percentage of "energy"
          concentrated on that top-K percent of values in the dimension
          to measure. Note, this is the opposite of the sparsity percentage.
docstr: Like measure, but do it in FFT frequency domain.
docstr_tok: ["Like","measure",",","but","do","it","in","FFT","frequency","domain","."]
code: def measure_fft(self, in_tensor: Tensor) -> List[Tensor]:
      """Like measure, but do it in FFT frequency domain."""
      return self.measure(torch.fft.fft(in_tensor, dim=self.dim).real)
  
imports: from typing import List
  import torch
  from torch import Tensor
label_desc: Use image node_id 3 for calling the EnergyConcentrationProfile obj's underlying member method code with example usage: obj.measure_fft(in_tensor) and returns: self