code: def scale_invariant_target_numpy(
      estimate: np.ndarray, target: np.ndarray, eps: float = 1e-8
  ) -> np.ndarray:
      """Calculate convolution-invariant target for a given estimated signal.
  
      Calculate scaled target obtained by solving
  
          min_scale || scale * target - estimate ||^2
  
      Args:
          estimate: one-dimensional estimated signal, shape (T,)
          target: one-dimensional target signal, shape (T,)
          eps: regularization constans
  
      Returns:
          Scaled target signal, shape (T,)
      """
      assert (
          target.ndim == estimate.ndim == 1
      ), f"Only one-dimensional inputs supported"
  
      estimate_dot_target = np.mean(estimate * target)
      target_pow = np.mean(np.abs(target) ** 2)
      scale = estimate_dot_target / (target_pow + eps)
      return scale * target
  
imports: import math
  from typing import Iterable, Optional, Union
  import librosa
  import numpy
  import numpy.typing
  import scipy
  import soundfile
  import torch
  from scipy.spatial.distance import pdist, squareform
  from nemo.utils import logging
label_desc: Use image node_id 17 for calling a global function with example usage: scale_invariant_target_numpy(estimate, target, eps) and returns: unknown