class_docstr: Reduce dimensions using PCA.
  
  This nn.Modue subclass reduces the dimensions of the inputs
  specified by `n_components`.
  
  The input is a 2-dimensional `Tensor` of size `batch` x `features`,
  the output is a `Tensor` of size `batch` x `n_components`.
code: def __init__(self, n_components: int = 2):
      super().__init__()
      self.n_components = n_components
      self.register_buffer("mean", None)
      self.register_buffer("comp", None)
  
file_path: TorchDrift/torchdrift/reducers/pca.py
imports: import torch
  from .None import Reducer
  import torchdrift.utils
label_desc: Use image node_id 1 to create a new PCAReducer object from inherited base classes: Reducer with example: obj = PCAReducer(n_components)