class_docstr: Gaussian 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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code: def _make_random_matrix(self, n_components: int, n_features: int):
      components = paddle.Tensor(n_components, n_features)
      paddle.nn.init.normal_(components)
      return components
  
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 the GaussianProjection obj's underlying member method code with example usage: obj._make_random_matrix(n_components, n_features) and returns: components