code: def compute_pc(x: np.ndarray, npc: int = 1) -> np.ndarray:
      """Compute the principal components. DO NOT MAKE THE DATA ZERO MEAN!
  
      :param x: X[i,:] is a data point
      :param npc: number of principal components to remove
      :return: component_[i,:] is the i-th pc
  
      This has been adapted from the SIF paper code: `https://openreview.net/pdf?id=SyK00v5xx`.
      """
      svd: TruncatedSVD = TruncatedSVD(
          n_components=npc, n_iter=7, random_state=0
      )
      svd.fit(x)
      return svd.components_
  
file_path: cltk/src/cltk/embeddings/sentence.py
imports: from typing import Dict, List, Tuple, Union, ValuesView
  import numpy
  from sklearn.decomposition import TruncatedSVD
  from cltk.core import Sentence
label_desc: Use image node_id 2 for calling a global function with example usage: compute_pc(x, npc) and returns: svd