I’m studying a fantastic recent update of PennyLane.

Release notes — PennyLane 0.16.0 documentation

In the version, `qml.specs`

was introduced.

From the release note,

```
dev = qml.device('default.qubit', wires=4)
@qml.qnode(dev, diff_method='parameter-shift')
def circuit(x, y):
qml.RX(x[0], wires=0)
qml.Toffoli(wires=(0, 1, 2))
qml.CRY(x[1], wires=(0, 1))
qml.Rot(x[2], x[3], y, wires=0)
return qml.expval(qml.PauliZ(0)), qml.expval(qml.PauliX(1))
x = np.array([0.05, 0.1, 0.2, 0.3], requires_grad=True)
y = np.array(0.4, requires_grad=False)
specs_func = qml.specs(circuit)
specs_func(x, y)
```

The result is,

```
{...
'num_observables': 2,
'num_diagonalizing_gates': 1,
'num_used_wires': 3,
'depth': 4,
'num_trainable_params': 4,
'num_parameter_shift_executions': 11,
...}
```

My question is , how the “num_parameter_shift_executions” has been calculated?

Since the number of parameters is 4, the number of foward prop would be 2 x num. of params.