class_docstr: Compute cross-channel power spectral density (PSD) matrix.
  
  .. devices:: CPU CUDA
  
  .. properties:: Autograd TorchScript
  
  Args:
      multi_mask (bool, optional): If ``True``, only accepts multi-channel Time-Frequency masks. (Default: ``False``)
      normalize (bool, optional): If ``True``, normalize the mask along the time dimension. (Default: ``True``)
      eps (float, optional): Value to add to the denominator in mask normalization. (Default: ``1e-15``)
code: def __init__(
      self,
      multi_mask: bool = False,
      normalize: bool = True,
      eps: float = 1e-15,
  ):
      super().__init__()
      self.multi_mask = multi_mask
      self.normalize = normalize
      self.eps = eps
  
imports: import warnings
  from typing import Optional, Union
  import torch
  from torch import Tensor
  from torchaudio import functional
label_desc: Use image node_id 1 to create a new PSD object from inherited base classes: torch.nn with example: obj = PSD(multi_mask, normalize, eps)