code: def plot_tsne(X, y, colormap=plt.cm.Paired):
      plt.figure(figsize=(8, 6))
  
      # clean the figure
      plt.clf()
  
      tsne = TSNE()
      X_embedded = tsne.fit_transform(X)
      plt.scatter(
          X_embedded[:, 0], X_embedded[:, 1], c=y, cmap=colormap
      )
  
      plt.xticks(())
      plt.yticks(())
  
      plt.show()
  
imports: from sklearn.manifold import TSNE
  import metric_learn
  import numpy
  from sklearn.datasets import make_classification, make_regression
  import matplotlib.pyplot
label_desc: Use image node_id 1 for calling a global function with example usage: plot_tsne(X, y, colormap) without return types