def __init__(self, model: Model, sampler: Optional[MCSampler]=None, objective: Optional[MCAcquisitionObjective]=None, X_pending: Optional[Tensor]=None) -> None:
    'Constructor for the MCAcquisitionFunction base class.\n\n        Args:\n            model: A fitted model.\n            sampler: The sampler used to draw base samples. Defaults to\n                `SobolQMCNormalSampler(num_samples=512, collapse_batch_dims=True)`.\n            objective: The MCAcquisitionObjective under which the samples are\n                evaluated. Defaults to `IdentityMCObjective()`.\n            X_pending:  A `m x d`-dim Tensor of `m` design points that have\n                points that have been submitted for function evaluation\n                but have not yet been evaluated.\n        '
    super().__init__(model=model)
    if (sampler is None):
        sampler = SobolQMCNormalSampler(num_samples=512, collapse_batch_dims=True)
    self.add_module('sampler', sampler)
    if (objective is None):
        objective = IdentityMCObjective()
    elif (not isinstance(objective, MCAcquisitionObjective)):
        raise UnsupportedError('Only objectives of type MCAcquisitionObjective are supported for MC acquisition functions.')
    self.add_module('objective', objective)
    self.set_X_pending(X_pending)
Constructor for the MCAcquisitionFunction base class.

Args:
    model: A fitted model.
    sampler: The sampler used to draw base samples. Defaults to
        `SobolQMCNormalSampler(num_samples=512, collapse_batch_dims=True)`.
    objective: The MCAcquisitionObjective under which the samples are
        evaluated. Defaults to `IdentityMCObjective()`.
    X_pending:  A `m x d`-dim Tensor of `m` design points that have
        points that have been submitted for function evaluation
        but have not yet been evaluated.
def __init__(self, model: Model, sampler: Optional[MCSampler]=None, objective: Optional[MCAcquisitionObjective]=None, X_pending: Optional[Tensor]=None) -> None:
    'Constructor for the MCAcquisitionFunction base class.\n\n        Args:\n            model: A fitted model.\n            sampler: The sampler used to draw base samples. Defaults to\n                `SobolQMCNormalSampler(num_samples=512, collapse_batch_dims=True)`.\n            objective: The MCAcquisitionObjective under which the samples are\n                evaluated. Defaults to `IdentityMCObjective()`.\n            X_pending:  A `m x d`-dim Tensor of `m` design points that have\n                points that have been submitted for function evaluation\n                but have not yet been evaluated.\n        '
    super().__init__(model=model)
    if (sampler is None):
        sampler = SobolQMCNormalSampler(num_samples=512, collapse_batch_dims=True)
    self.add_module('sampler', sampler)
    if (objective is None):
        objective = IdentityMCObjective()
    elif (not isinstance(objective, MCAcquisitionObjective)):
        raise UnsupportedError('Only objectives of type MCAcquisitionObjective are supported for MC acquisition functions.')
    self.add_module('objective', objective)
    self.set_X_pending(X_pending)