class_docstr: Test that the ZXZ decomposition is correct.
class_docstr_tok: ["Test","that","the","ZXZ","decomposition","is","correct","."]
docstr: Test that a one-qubit operation in Torch is correctly decomposed.
docstr_tok: ["Test","that","a","one-qubit","operation","in","Torch","is","correctly","decomposed","."]
code: def test_zxz_decomposition_torch(self, U, expected_params):
      """Test that a one-qubit operation in Torch is correctly decomposed."""
  
      import torch
  
      U = torch.tensor(U, dtype=torch.complex128)
      _test_decomposition(U, "ZXZ", typeof_gates_zxz, expected_params)
  
imports: from functools import reduce
  import pytest
  from gate_data import I, Z, S, T, H, X, Y, CNOT, SWAP
  import pennylane
  from pennylane import numpy
  from pennylane.wires import Wires
  from pennylane.ops.op_math.decompositions import one_qubit_decomposition
  from pennylane.ops.op_math.decompositions import two_qubit_decomposition
  from pennylane.ops.op_math.decompositions.two_qubit_unitary import _convert_to_su4, _su2su2_to_tensor_products, _compute_num_cnots
label_desc: Use image node_id 2 for calling the TestQubitUnitaryZXZDecomposition obj's underlying member method code with example usage: obj.test_zxz_decomposition_torch(U, expected_params) without return types