# qml.math.get_interface¶

get_interface(*values)[source]

Determines the correct framework to dispatch to given a tensor-like object or a sequence of tensor-like objects.

Parameters

*values (tensor_like) – variable length argument list with single tensor-like objects

Returns

the name of the interface

Return type

str

To determine the framework to dispatch to, the following rules are applied:

• Tensors that are incompatible (such as Torch, TensorFlow and Jax tensors) cannot both be present.

• Autograd tensors may be present alongside Torch, TensorFlow and Jax tensors, but Torch, TensorFlow and Jax take precendence; the autograd arrays will be treated as non-differentiable NumPy arrays. A warning will be raised suggesting that vanilla NumPy be used instead.

• Vanilla NumPy arrays and SciPy sparse matrices can be used alongside other tensor objects; they will always be treated as non-differentiable constants.

Warning

get_interface defaults to "numpy" whenever Python built-in objects are passed. I.e. a list or tuple of torch tensors will be identified as "numpy":

>>> get_interface([torch.tensor([1]), torch.tensor([1])])
"numpy"


The correct usage in that case is to unpack the arguments get_interface(*[torch.tensor([1]), torch.tensor([1])]).