code: def johnson_lindenstrauss_min_dim(n_samples: int, eps: float = 0.1):
      """Find a 'safe' number of components to randomly project to.
  
      Ref eqn 2.1 https://cseweb.ucsd.edu/~dasgupta/papers/jl.pdf
  
      Args:
          n_samples (int): Number of samples used to compute safe components
          eps (float, optional): Minimum distortion rate. Defaults to 0.1.
      """
  
      denominator = (eps**2 / 2) - (eps**3 / 3)
      return (4 * np.log(n_samples) / denominator).astype(np.int64)
  
imports: import warnings
  from typing import Optional
  import paddle
  from paddle import Tensor
  import numpy
  from sklearn.utils.random import sample_without_replacement
label_desc: Use image node_id 1 for calling a global function with example usage: johnson_lindenstrauss_min_dim(n_samples, eps) and returns: unknown