class_docstr: Base module for Random Projection using Paddle operations.
  
  Args:
      eps (float, optional): Minimum distortion rate parameter for calculating
          Johnson-Lindenstrauss minimum dimensions. Defaults to 0.1.
      random_state (Optional[int], optional): Uses the seed to set the random
          state for sample_without_replacement function. Defaults to None.
class_docstr_tok: ["Base","module","for","Random","Projection","using","Paddle","operations",".","Args",":","eps","(","float",",","optional",")",":","Minimum","distortion","rate","parameter","for","calculating","Johnson-Lindenstrauss","minimum","dimensions",".","Defaults","to","0.1.","random_state","(","Optional","[","int","]",",","optional",")",":","Uses","the","seed","to","set","the","random","state","for","sample_without_replacement","function",".","Defaults","to","None","."]
code: def __init__(
      self,
      n_components="auto",
      eps: float = 0.1,
      random_state: Optional[int] = None,
  ) -> None:
      self.n_components = n_components
      self.n_components_: int
      self.random_matrix: Tensor
      self.eps = eps
      self.random_state = random_state
  
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 to create a new BaseRandomProjection object  with example: obj = BaseRandomProjection(n_components, eps, random_state)