class_docstr: A wrapper for torch.linalg.eigh to avoid complex eigenvalues for degenerate case.
  
  Examples
  --------
  >>> import torch
  >>> import numpy as np
  >>> from deepchem.utils.differentiation_utils import LinearOperator
  >>> A = LinearOperator.m(torch.rand(2, 2))
  >>> evals, evecs = degen_symeig.apply(A.fullmatrix())
  >>> evals.shape
  torch.Size([2])
  >>> evecs.shape
  torch.Size([2, 2])
docstr: Calculate the eigenvalues and eigenvectors of a symmetric matrix.
  
  Parameters
  ----------
  A: torch.Tensor
      The symmetric matrix to be diagonalized. Shape: ``(*BA, q, q)``.
  
  Returns
  -------
  eival: torch.Tensor
      Eigenvalues of the linear operator.
  eivec: torch.Tensor
      Eigenvectors of the linear operator.
docstr_tok: ["Calculate","the","eigenvalues","and","eigenvectors","of","a","symmetric","matrix",".","Parameters","--","--","--","--","--","A",":","torch.Tensor","The","symmetric","matrix","to","be","diagonalized",".","Shape",":","``","(","*","BA",",","q",",","q",")","``",".","Returns","--","--","--","-","eival",":","torch.Tensor","Eigenvalues","of","the","linear","operator",".","eivec",":","torch.Tensor","Eigenvectors","of","the","linear","operator","."]
code: def forward(ctx, A):
      """Calculate the eigenvalues and eigenvectors of a symmetric matrix.
  
      Parameters
      ----------
      A: torch.Tensor
          The symmetric matrix to be diagonalized. Shape: ``(*BA, q, q)``.
  
      Returns
      -------
      eival: torch.Tensor
          Eigenvalues of the linear operator.
      eivec: torch.Tensor
          Eigenvectors of the linear operator.
  
      """
      eival, eivec = torch.linalg.eigh(A)
      ctx.save_for_backward(eival, eivec)
      return eival, eivec
  
file_path: deepchem/deepchem/utils/differentiation_utils/symeig.py
imports: import torch
  from typing import Optional, Sequence, Tuple, Union
  from deepchem.utils.differentiation_utils import LinearOperator
  import functools
  from deepchem.utils.pytorch_utils import tallqr, to_fortran_order
  from deepchem.utils.differentiation_utils import get_bcasted_dims
label_desc: Use image node_id 1 for calling the degen_symeig obj's underlying member method code with example usage: obj.forward(ctx, A) and returns: eival,  eivec