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.
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docstr: Random projection matrix.
  
  Args:
      n_components (int): Dimensionality of the target projection space.
      n_features (int): Dimentionality of the original source space.
  
  Returns:
      Tensor: Matrix of shape (n_components, n_features).
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code: def _make_random_matrix(self, n_components: int, n_features: int):
      """Random projection matrix.
  
      Args:
          n_components (int): Dimensionality of the target projection space.
          n_features (int): Dimentionality of the original source space.
  
      Returns:
          Tensor: Matrix of shape (n_components, n_features).
      """
      raise NotImplementedError
  
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 2 for calling the BaseRandomProjection obj's underlying member method code with example usage: obj._make_random_matrix(n_components, n_features) without return types