code: def exp(op, coeff=1, num_steps=None, id=None):
      """Take the exponential of an Operator times a coefficient.
  
      Args:
          base (~.operation.Operator): The Operator to be exponentiated
          coeff (float): a scalar coefficient of the operator
          num_steps (int): The number of steps used in the decomposition of the exponential operator,
              also known as the Trotter number. If this value is `None` and the Suzuki-Trotter
              decomposition is needed, an error will be raised.
          id (str): id for the Exp operator. Default is None.
  
      Returns:
         :class:`Exp`: An :class:`~.operation.Operator` representing an operator exponential.
  
      .. note::
  
          This operator supports a batched base, a batched coefficient and a combination of both:
  
          >>> op = qml.exp(qml.RX([1, 2, 3], wires=0), coeff=4)
          >>> qml.matrix(op).shape
          (3, 2, 2)
          >>> op = qml.exp(qml.RX(1, wires=0), coeff=[1, 2, 3])
          >>> qml.matrix(op).shape
          (3, 2, 2)
          >>> op = qml.exp(qml.RX([1, 2, 3], wires=0), coeff=[4, 5, 6])
          >>> qml.matrix(op).shape
          (3, 2, 2)
  
          But it doesn't support batching of operators:
  
          >>> op = qml.exp([qml.RX(1, wires=0), qml.RX(2, wires=0)], coeff=4)
          AttributeError: 'list' object has no attribute 'batch_size'
  
      **Example**
  
      This symbolic operator can be used to make general rotation operators:
  
      >>> x = np.array(1.23)
      >>> op = qml.exp( qml.PauliX(0), -0.5j * x)
      >>> qml.math.allclose(op.matrix(), qml.RX(x, wires=0).matrix())
      True
  
      This can even be used for more complicated generators:
  
      >>> t = qml.PauliX(0) @ qml.PauliX(1) + qml.PauliY(0) @ qml.PauliY(1)
      >>> isingxy = qml.exp(t, 0.25j * x)
      >>> qml.math.allclose(isingxy.matrix(), qml.IsingXY(x, wires=(0,1)).matrix())
      True
  
      If the coefficient is purely imaginary and the base operator is Hermitian, then
      the gate can be used in a circuit, though it may not be supported by the device and
      may not be differentiable.
  
      >>> @qml.qnode(qml.device('default.qubit', wires=1))
      ... def circuit(x):
      ...     qml.exp(qml.PauliX(0), -0.5j * x)
      ...     return qml.expval(qml.PauliZ(0))
      >>> print(qml.draw(circuit)(1.23))
      0: ──Exp─┤  <Z>
  
      If the base operator is Hermitian and the coefficient is real, then the ``Exp`` operator
      can be measured as an observable:
  
      >>> obs = qml.exp(qml.PauliZ(0), 3)
      >>> @qml.qnode(qml.device('default.qubit', wires=1))
      ... def circuit():
      ...     return qml.expval(obs)
      >>> circuit()
      tensor(20.08553692, requires_grad=True)
  
      """
      return Exp(op, coeff, num_steps=num_steps, id=id)
  
imports: from typing import List
  from warnings import warn
  import numpy
  from scipy.sparse.linalg import expm
  import pennylane
  from pennylane import math
  from pennylane.math import expand_matrix
  from pennylane.operation import AnyWires, DecompositionUndefinedError, GeneratorUndefinedError, Operation, Operator, OperatorPropertyUndefined, Tensor
  from pennylane.ops.qubit import Hamiltonian
  from pennylane.wires import Wires
  from .sprod import SProd
  from .sum import Sum
  from .symbolicop import ScalarSymbolicOp
label_desc: Use image node_id 1 for calling a global function with example usage: exp(op, coeff, num_steps, id) and returns: Exp