Python get_local_kernel示例

编程语言: Python

命名空间/包名称: netket.vqs.mc

方法/功能: get_local_kernel

hotexamples.com的示例: 6

Python get_local_kernel - 已找到6个示例。这些是从开源项目中提取的最受好评的netket.vqs.mc.get_local_kernel现实Python示例。您可以评价示例，以帮助我们提高示例质量。

示例#1

显示文件

def expect_and_grad(  # noqa: F811
    vstate: MCState,
    Ô: AbstractOperator,
    use_covariance: TrueT,
    *,
    mutable: Any,
) -> Tuple[Stats, PyTree]:
    σ, args = get_local_kernel_arguments(vstate, Ô)

    local_estimator_fun = get_local_kernel(vstate, Ô)

    Ō, Ō_grad, new_model_state = grad_expect_hermitian(
        local_estimator_fun,
        vstate._apply_fun,
        mutable,
        vstate.parameters,
        vstate.model_state,
        σ,
        args,
    )

    if mutable is not False:
        vstate.model_state = new_model_state

    return Ō, Ō_grad

示例#2

显示文件

def expect_and_grad(  # noqa: F811
    vstate,
    Ô,
    use_covariance,
    *,
    mutable: Any,
) -> Tuple[Stats, PyTree]:
    σ, args = get_local_kernel_arguments(vstate, Ô)

    local_estimator_fun = get_local_kernel(vstate, Ô)

    Ō, Ō_grad, new_model_state = grad_expect_operator_kernel(
        local_estimator_fun,
        vstate._apply_fun,
        vstate.sampler.machine_pow,
        mutable,
        vstate.parameters,
        vstate.model_state,
        σ,
        args,
    )

    if mutable is not False:
        vstate.model_state = new_model_state

    return Ō, Ō_grad

示例#3

显示文件

def local_estimators(
    state: MCState, op: AbstractOperator, *, chunk_size: Optional[int]
):
    s, extra_args = get_local_kernel_arguments(state, op)

    shape = s.shape
    if jnp.ndim(s) != 2:
        s = s.reshape((-1, shape[-1]))

    if chunk_size is None:
        chunk_size = state.chunk_size  # state.chunk_size can still be None

    if chunk_size is None:
        kernel = get_local_kernel(state, op)
    else:
        kernel = get_local_kernel(state, op, chunk_size)

    return _local_estimators_kernel(
        kernel, state._apply_fun, shape[:-1], state.variables, s, extra_args
    )

示例#4

显示文件

def expect(vstate: MCState, Ô: AbstractOperator) -> Stats:  # noqa: F811
    σ, args = get_local_kernel_arguments(vstate, Ô)

    local_estimator_fun = get_local_kernel(vstate, Ô)

    return _expect(
        local_estimator_fun,
        vstate._apply_fun,
        vstate.sampler.machine_pow,
        vstate.parameters,
        vstate.model_state,
        σ,
        args,
    )

示例#5

显示文件

文件： expect_chunked.py 项目： yannra/netket

def expect_mcstate_operator_chunked(
    vstate: MCState, Ô: AbstractOperator, chunk_size: int
) -> Stats:  # noqa: F811
    σ, args = get_local_kernel_arguments(vstate, Ô)

    local_estimator_fun = get_local_kernel(vstate, Ô, chunk_size)

    return _expect_chunking(
        chunk_size,
        local_estimator_fun,
        vstate._apply_fun,
        vstate.sampler.machine_pow,
        vstate.parameters,
        vstate.model_state,
        σ,
        args,
    )

示例#6

显示文件

def expect_and_grad(  # noqa: F811
    vstate,
    Ô,
    use_covariance,
    *,
    mutable: Any,
) -> Tuple[Stats, PyTree]:

    if not isinstance(Ô, Squared) and not config.FLAGS["NETKET_EXPERIMENTAL"]:
        raise RuntimeError(
            """
            Computing the gradient of non hermitian operator is an
            experimental feature under development and is known not to
            return wrong values sometimes.

            If you want to debug it, set the environment variable
            NETKET_EXPERIMENTAL=1
            """
        )

    σ, args = get_local_kernel_arguments(vstate, Ô)

    local_estimator_fun = get_local_kernel(vstate, Ô)

    Ō, Ō_grad, new_model_state = grad_expect_operator_kernel(
        local_estimator_fun,
        vstate._apply_fun,
        vstate.sampler.machine_pow,
        mutable,
        vstate.parameters,
        vstate.model_state,
        σ,
        args,
    )

    if mutable is not False:
        vstate.model_state = new_model_state

    return Ō, Ō_grad