# Device Error with self-written Template **URL:** \ **Category:** PennyLane Help\ **Created:** [April 4, 2024, 2:28pm UTC](https://discuss.pennylane.ai/t/device-error-with-self-written-template/4395 "2024-04-04T14:28:06Z")\ **Posts on this page:** 4\ **Page:** 1
**Author:** ![Pia](https://avatars.discourse-cdn.com/v4/letter/p/6a8cbe/32.png) [@Pia](https://discuss.pennylane.ai/u/Pia)\ **Post date:** [April 4, 2024, 2:28pm UTC](https://discuss.pennylane.ai/t/device-error-with-self-written-template/4395/1 "2024-04-04T14:28:06Z")
Dear Pennylane-Team, I have a question regarding a code-snippit I wrote about \> year ago in pennylane 0.25.1. I updated now my pennylane version to 0.35.1 and run into a problem that I don’t understand. In the following I provide a minimal example where I try to implement my own template. In this minimal example, the template should solely realize an RY-rotation to encode my input. When I run the code I get the following error. When using “default.qubit”: > DeviceError: Operator minimalExample(array([0.78539816]), wires=[0]) not supported on default.qubit and does not provide a decomposition. When using “default.qubit.torch”: > DeviceError: Gate minimalExample not supported on device default.qubit.torch I checked with this example ( [How to add custom gates and templates to PennyLane | PennyLane Blog](https://pennylane.ai/blog/2021/05/how-to-add-custom-gates-and-templates-to-pennylane/)) and can’t find the error. Here is the code: 1. I define the minimal Template Example ```auto import numpy as np import torch import pennylane as qml from pennylane.operation import Operation, AnyWires class minimalExample(Operation): r""" Template of minimal example """ num_wires = AnyWires par_domain = "A" def __init__ (self, features, wires, alpha="Y", varphi="arccos", beta=1.0, id=None): super(). __init__ (features, wires=wires, id=id) @property def num_params(self): return 1 def expand(self): r""" Implements the encoding of the input parameters. """ num_weights = qml.math.shape(features)[0] with qml.tape.QuantumTape() as tape: for i in range(num_weights): qml.RY(features[0], wires=self.wires[i]) return tape ``` 1. I tried to initiate the input values as numpy.array or torch.tensor. When using torch.tensor I used it with default.qubit.torch ```auto inputNumpy = np.array([np.pi / 4]) #inputTorch = torch.tensor([np.pi / 4]) nqubit = 1 dev = qml.device("default.qubit", wires=nqubit) #dev = qml.device("default.qubit.torch", wires=nqubit) @qml.qnode(dev) #@qml.qnode(dev, interface='torch', diff_method='backprop') def qcFkt(inputs, wires): """ QC function that performs encoding via the Templates""" minimalExample(inputs, range(wires)) return [qml.expval(qml.PauliZ(i)) for i in range(wires)] ``` Calling this circuit gives me the described errors. ```auto qcFkt(inputTorch, nqubit) ``` Thank you very much and best regards, Pia ---
**Author:** ![CatalinaAlbornoz](https://yyz2.discourse-cdn.com/flex012/user_avatar/discuss.pennylane.ai/catalinaalbornoz/32/1196_2.png) [@CatalinaAlbornoz](https://discuss.pennylane.ai/u/CatalinaAlbornoz)\ **Post date:** [April 8, 2024, 1:35pm UTC](https://discuss.pennylane.ai/t/device-error-with-self-written-template/4395/2 "2024-04-08T13:35:12Z")
Hi @Pia, thank you for your question. I’m looking into it. ---
**Author:** ![CatalinaAlbornoz](https://yyz2.discourse-cdn.com/flex012/user_avatar/discuss.pennylane.ai/catalinaalbornoz/32/1196_2.png) [@CatalinaAlbornoz](https://discuss.pennylane.ai/u/CatalinaAlbornoz)\ **Post date:** [April 8, 2024, 2:33pm UTC](https://discuss.pennylane.ai/t/device-error-with-self-written-template/4395/3 "2024-04-08T14:33:06Z")
Hi @Pia, The blog that you were looking at was unfortunately outdated. We always update the documentation and the demos when we make a new release, but the blog content remains static to how it was when it was published. Fortunately you can find all of the updated information [here in the docs](https://docs.pennylane.ai/en/stable/development/adding_operators.html)! In your example the issue was that you needed the static method `compute_decomposition`. I’ve added a working code below. I hope this helps! ```auto import numpy as np import torch import pennylane as qml from pennylane.operation import Operation, AnyWires class minimalExample(Operation): r""" Template of minimal example """ num_wires = AnyWires grad_method = "A" def __init__ (self, features, wires, alpha="Y", varphi="arccos", beta=1.0, id=None): super(). __init__ (features, wires=wires, id=id) @property def num_params(self): return 1 @staticmethod def compute_decomposition(features, wires): # Overwriting this method defines the decomposition of the new gate, as it is # called by Operator.decomposition(). # The general signature of this function is (*parameters, wires, **hyperparameters). num_weights = qml.math.shape(features)[0] op_list = [] for i in range(num_weights): op_list.append(qml.RY(features[0], wires=wires[i])) return op_list # inputNumpy = np.array([np.pi / 4]) inputTorch = torch.tensor([np.pi / 4]) nqubit = 1 # dev = qml.device("default.qubit", wires=nqubit) dev = qml.device("default.qubit.torch", wires=nqubit) # @qml.qnode(dev) @qml.qnode(dev, interface='torch', diff_method='backprop') def qcFkt(inputs, wires): """ QC function that performs encoding via the Templates""" minimalExample(inputs, range(wires)) return [qml.expval(qml.PauliZ(i)) for i in range(wires)] qcFkt(inputTorch, nqubit) qml.draw_mpl(qcFkt, expansion_strategy='device')(inputTorch, nqubit) ``` ---
**Author:** ![Pia](https://avatars.discourse-cdn.com/v4/letter/p/6a8cbe/32.png) [@Pia](https://discuss.pennylane.ai/u/Pia)\ **Post date:** [April 9, 2024, 11:26am UTC](https://discuss.pennylane.ai/t/device-error-with-self-written-template/4395/4 "2024-04-09T11:26:52Z")
Thanks, this helped 🙂