class_docstr: Tests for the expand_matrix helper function.
class_docstr_tok: ["Tests","for","the","expand_matrix","helper","function","."]
docstr: Tests differentiation in torch by computing the Jacobian of
  the expanded matrix with respect to the canonical matrix.
docstr_tok: ["Tests","differentiation","in","torch","by","computing","the","Jacobian","of","the","expanded","matrix","with","respect","to","the","canonical","matrix","."]
code: def test_torch(self, i, base_matrix, tol):
      """Tests differentiation in torch by computing the Jacobian of
      the expanded matrix with respect to the canonical matrix."""
      import torch
  
      base_matrix = torch.tensor(base_matrix, requires_grad=True)
      jac = torch.autograd.functional.jacobian(
          self.func_for_autodiff, base_matrix
      )
  
      assert np.allclose(jac, self.expected_autodiff[i], atol=tol)
  
imports: from functools import reduce
  import numpy
  import pytest
  from gate_data import CNOT, II, SWAP, I, Toffoli
  from scipy.sparse import csr_matrix
  import pennylane
  from pennylane import numpy
label_desc: Use image node_id 10 for calling the TestExpandMatrix obj's underlying member method code with example usage: obj.test_torch(i, base_matrix, tol) without return types