class_docstr: Test decompositions are generated correctly.
class_docstr_tok: ["Test","decompositions","are","generated","correctly","."]
docstr: Test that the decomposition is computed and queues correctly.
docstr_tok: ["Test","that","the","decomposition","is","computed","and","queues","correctly","."]
code: def test_compute_decomposition(self, seed):
      """Test that the decomposition is computed and queues correctly."""
      coeffs = [1, -0.5, 0.5]
      ops = [qml.Identity(wires=[0, 1]), qml.PauliZ(0), qml.PauliZ(1)]
  
      h = qml.dot(coeffs, ops)
      op = qml.QDrift(h, time=1.23, n=10, seed=seed)
  
      expected_decomp = _sample_decomposition(
          coeffs, ops, 1.23, 10, seed=seed
      )
  
      with qml.tape.QuantumTape() as tape:
          decomp = op.compute_decomposition(
              *op.parameters, **op.hyperparameters
          )
  
      assert (
          decomp == tape.operations
      )  # queue matches decomp with circuit ordering
      assert decomp == list(expected_decomp)
  
imports: import copy
  from functools import reduce
  import pytest
  import pennylane
  from pennylane import numpy
  from pennylane.math import allclose, isclose
  from pennylane.templates.subroutines.qdrift import _sample_decomposition
label_desc: Use image node_id 3 for calling the TestDecomposition obj's underlying member method code with example usage: obj.test_compute_decomposition(seed) without return types