mindquantum.parameterresolver

Parameter resolver.

class mindquantum.parameterresolver.ParameterResolver(data=None)[source]

A ParameterRsolver can set the parameter of parameterized quantum gate or parameterized quantum circuit.

By specific which part of parameters needs to calculate gradient, the PQC operator can only calculate gradient of these parameters.

Parameters

data (dict) – initial parameter names and its values. Default: None.

Examples

>>> from mindquantum import ParameterResolver
>>> pr = ParameterResolver({'a': 0.3})
>>> pr['b'] = 0.5
>>> pr.no_grad_part('a')
>>> pr *= 2
>>> pr
{'a': 0.6, 'b': 1.0}
>>> pr.no_grad_parameters
{'a'}
combination(pr)[source]

Apply linear combination between this parameter resolver with input pr.

Parameters

pr (Union[dict, ParameterResolver]) – The parameter resolver you want to do linear combination.

Returns

numbers.Number, the combination result.

Examples: >>> from mindquantum import ParameterResolver >>> pr1 = ParameterResolver({‘a’: 1, ‘b’: 2}) >>> pr2 = ParameterResolver({‘a’: 2, ‘b’: 3}) >>> pr1.combination(pr2)

conjugate()[source]

Get the conjugate of the parameter resolver.

Returns

ParameterResolver, the conjugate version of this parameter resolver.

Examples

>>> from mindquantum.parameterresolver import ParameterResolver as PR
>>> pr = PR({'a' : 1, 'b': 1j})
>>> pr.conjugate().expression()
a - 1.0*I*b
expression()[source]

Get the expression of this parameter resolver.

Returns

sympy.Expr, the symbol expression of this parameter resolver.

Examples

>>> from mindquantum.parameterresolver import ParameterResolver as PR
>>> pr = PR({'a' : 2, 'b' : 0.3})
>>> pr.expression()
2*a + 0.3*b
property imag

Get the real part of this parameter resolver

Returns

ParameterResolver, the image part of this parameter resolver.

Examples

>>> from mindquantum.parameterresolver import ParameterResolver as PR
>>> pr = PR({'a': 1.2 + 1.3j})
>>> pr.imag()
{'a': 1.3}
mindspore_data()[source]

Generate data for PQC operator.

Returns

Dict.

no_grad()[source]

Set all parameters to not require gradient calculation. Inplace operation.

Returns

ParameterResolver, the parameter resolver itself.

Examples

>>> from mindquantum import ParameterResolver
>>> pr = ParameterResolver({'a': 1, 'b': 2})
>>> pr.no_grad()
>>> pr.requires_grad_parameters
set()
no_grad_part(*names)[source]

Set part of parameters that not requires grad.

Parameters

names (tuple[str]) – Parameters that not requires grad.

Returns

ParameterResolver, the parameter resolver itself.

Examples

>>> from mindquantum import ParameterResolver
>>> pr = ParameterResolver({'a': 1, 'b': 2})
>>> pr.no_grad_part('a')
>>> pr.requires_grad_parameters
{'b'}
property para_name

Get the parameters name.

Returns

list, a list of parameters name.

Examples

>>> from mindquantum import ParameterResolver
>>> pr = ParameterResolver({'a': 1, 'b': 2})
>>> pr.para_name
['a', 'b']
property para_value

Get the parameters value.

Returns

list, a list of parameters value.

Examples

>>> from mindquantum import ParameterResolver
>>> pr = ParameterResolver({'a': 1, 'b': 2})
>>> pr.para_value
[1, 2]
property real

Get the real part of this parameter resolver

Returns

ParameterResolver, the real part of this parameter resolver.

Examples

>>> from mindquantum.parameterresolver import ParameterResolver as PR
>>> pr = PR({'a': 1.2 + 1.3j})
>>> pr.real()
{'a': 1.2}
requires_grad()[source]

Set all parameters of this parameter resolver to require gradient calculation. Inplace operation.

Returns

ParameterResolver, the parameter resolver itself.

Examples

>>> from mindquantum import ParameterResolver
>>> pr = ParameterResolver({'a': 1, 'b': 2})
>>> pr.no_grad_part('a')
>>> pr.requires_grad()
>>> pr.requires_grad_parameters
{'a', 'b'}
requires_grad_part(*names)[source]

Set part of parameters that requires grad. Inplace operation.

Parameters

names (tuple[str]) – Parameters that requires grad.

Returns

ParameterResolver, the parameter resolver itself.

Examples

>>> from mindquantum import ParameterResolver
>>> pr = ParameterResolver({'a': 1, 'b': 2})
>>> pr.no_grad()
>>> pr.requires_grad_part('a')
>>> pr.requires_grad_parameters
{'a'}
update(others)[source]

Update this parameter resolver with other parameter resolver.

Parameters

others (ParameterResolver) – other parameter resolver.

Raises

ValueError – If some parameters require grad and not require grad in other parameter resolver and vise versa.

Examples

>>> from mindquantum import ParameterResolver
>>> pr1 = ParameterResolver({'a': 1})
>>> pr2 = ParameterResolver({'b': 2})
>>> pr2.no_grad()
>>> pr1.update(pr2)
>>> pr1
{'a': 1, 'b': 2}
>>> pr1.no_grad_parameters
{'b'}