class_docstr: Tests for the sample integration
class_docstr_tok: ["Tests","for","the","sample","integration"]
docstr: Test the return type and shape of sampling multiple wires
  where a rectangular array is expected
docstr_tok: ["Test","the","return","type","and","shape","of","sampling","multiple","wires","where","a","rectangular","array","is","expected"]
code: def test_multi_wire_sample_regular_shape(self):
      """Test the return type and shape of sampling multiple wires
      where a rectangular array is expected"""
  
      @qnode(
          DefaultQubit(),
          diff_method="parameter-shift",
          interface="torch",
      )
      def circuit():
          return (
              qml.sample(qml.PauliZ(0)),
              qml.sample(qml.PauliZ(1)),
              qml.sample(qml.PauliZ(2)),
          )
  
      result = circuit(shots=10)
  
      # If all the dimensions are equal the result will end up to be a proper rectangular array
      assert isinstance(result, tuple)
      assert tuple(result[0].shape) == (10,)
      assert tuple(result[1].shape) == (10,)
      assert tuple(result[2].shape) == (10,)
      assert result[0].dtype == torch.int64
      assert result[1].dtype == torch.int64
      assert result[2].dtype == torch.int64
  
imports: import numpy
  import pytest
  import pennylane
  from pennylane import qnode
  from pennylane.devices import DefaultQubit
label_desc: Use image node_id 6 for calling the TestSample obj's underlying member method code with example usage: obj.test_multi_wire_sample_regular_shape() and returns: qml,  qml,  qml