class_docstr: Generates Glussian clusters for binary classes
class_docstr_tok: ["Generates","Glussian","clusters","for","binary","classes"]
code: def __init__(self, n_samples=5000, n_features=20):
      self.n_samples = n_samples
      self.n_features = n_features
      x, x_test, y, y_test = GaussianClusters.generate_data(
          n_samples, n_features
      )
      self.x, self.y = x, y
      self.x_test, self.y_test = x_test, y_test
  
file_path: CrypTen/benchmarks/data.py
imports: import os
  from pathlib import Path
  import crypten
  import PIL
  import torch
  import torch.nn.functional
  from sklearn.datasets import make_classification
  from sklearn.model_selection import train_test_split
  from torchvision import transforms
label_desc: Use image node_id 1 to create a new GaussianClusters object  with example: obj = GaussianClusters(n_samples, n_features)