tensorcircuit.interfaces.tensortrans

general function for interfaces transformation

tensorcircuit.interfaces.tensortrans.args_to_tensor(f: Callable[[...], Any], argnums: Union[int, Sequence[int]] = 0, tensor_as_matrix: bool = False, gate_to_tensor: bool = False, gate_as_matrix: bool = True, qop_to_tensor: bool = False, qop_as_matrix: bool = True, cast_dtype: bool = True) → Callable[[...], Any]

Function decorator that automatically convert inputs to tensors on current backend

Example

tc.set_backend("jax")

@partial(
tc.interfaces.args_to_tensor,
argnums=[0, 1, 2],
gate_to_tensor=True,
qop_to_tensor=True,
)
def f(a, b, c, d):
    return a, b, c, d

f(
[tc.Gate(np.ones([2, 2])), tc.Gate(np.ones([2, 2, 2, 2]))],
tc.QuOperator.from_tensor(np.ones([2, 2, 2, 2, 2, 2])),
np.ones([2, 2, 2, 2]),
tf.zeros([1, 2]),
)

# ([DeviceArray([[1.+0.j, 1.+0.j],
#        [1.+0.j, 1.+0.j]], dtype=complex64),
# DeviceArray([[1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j],
#             [1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j],
#             [1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j],
#             [1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j]], dtype=complex64)],
# DeviceArray([[1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j,
#             1.+0.j],
#             [1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j,
#             1.+0.j],
#             [1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j,
#             1.+0.j],
#             [1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j,
#             1.+0.j],
#             [1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j,
#             1.+0.j],
#             [1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j,
#             1.+0.j],
#             [1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j,
#             1.+0.j],
#             [1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j,
#             1.+0.j]], dtype=complex64),
# DeviceArray([[[[1.+0.j, 1.+0.j],
#                 [1.+0.j, 1.+0.j]],

#             [[1.+0.j, 1.+0.j],
#                 [1.+0.j, 1.+0.j]]],


#             [[[1.+0.j, 1.+0.j],
#                 [1.+0.j, 1.+0.j]],

#             [[1.+0.j, 1.+0.j],
#                 [1.+0.j, 1.+0.j]]]], dtype=complex64),
# <tf.Tensor: shape=(1, 2), dtype=float32, numpy=array([[0., 0.]], dtype=float32)>)

参数

• f (Callable[..., Any]) -- the wrapped function whose arguments in argnums position are expected to be tensor format

• argnums (Union[int, Sequence[int]], optional) -- position of args under the auto conversion, defaults to 0

• tensor_as_matrix (bool, optional) -- try reshape all input tensor as matrix with shape rank 2, defaults to False

• gate_to_tensor (bool, optional) -- convert Gate to tensor, defaults to False

• gate_as_matrix (bool, optional) -- reshape tensor from Gate input as matrix, defaults to True

• qop_to_tensor (bool, optional) -- convert QuOperator to tensor, defaults to False

• qop_as_matrix (bool, optional) -- reshape tensor from QuOperator input as matrix, defaults to True

• cast_dtype (bool, optional) -- whether cast to backend dtype, defaults to True

返回

The wrapped function

返回类型

Callable[..., Any]

tensorcircuit.interfaces.tensortrans.gate_to_matrix(t: tensorcircuit.gates.Gate, is_reshapem: bool = True) → Any

tensorcircuit.interfaces.tensortrans.general_args_to_backend(args: Any, dtype: Optional[Any] = None, target_backend: Optional[Any] = None, enable_dlpack: bool = True) → Any

tensorcircuit.interfaces.tensortrans.general_args_to_numpy(args: Any) → Any

Given a pytree, get the corresponding numpy array pytree

参数

args (Any) -- pytree

返回

the same format pytree with all tensor replaced by numpy array

返回类型

Any

tensorcircuit.interfaces.tensortrans.numpy_args_to_backend(args: Any, dtype: Optional[Any] = None, target_backend: Optional[Any] = None) → Any

Given a pytree of numpy arrays, get the corresponding tensor pytree

参数

• args (Any) -- pytree of numpy arrays

• dtype (Any, optional) -- str of str of the same pytree shape as args, defaults to None

• target_backend (Any, optional) -- str or backend object, defaults to None, indicating the current default backend

返回

the same format pytree with all numpy array replaced by the tensors in the target backend

返回类型

Any

tensorcircuit.interfaces.tensortrans.numpy_to_tensor(t: Any, backend: Any) → Any

tensorcircuit.interfaces.tensortrans.qop_to_matrix(t: tensorcircuit.quantum.QuOperator, is_reshapem: bool = True) → Any

tensorcircuit.interfaces.tensortrans.tensor_to_backend_jittable(t: Any) → Any

tensorcircuit.interfaces.tensortrans.tensor_to_dlpack(t: Any) → Any

tensorcircuit.interfaces.tensortrans.tensor_to_dtype(t: Any) → str

tensorcircuit.interfaces.tensortrans.tensor_to_numpy(t: Any) → Any

tensorcircuit.interfaces.tensortrans.which_backend(a: Any, return_backend: bool = True) → Any

Given a tensor a, return the corresponding backend

参数

• a (Tensor) -- the tensor

• return_backend (bool, optional) -- if true, return backend object, if false, return backend str, defaults to True

返回

the backend object or backend str

返回类型

Any