Пример #1
0
def get_param_store():
    """
    Returns the ParamStore
    """
    return _PYRO_PARAM_STORE


def clear_param_store():
    """
    Clears the ParamStore. This is especially useful if you're working in a REPL.
    """
    return _PYRO_PARAM_STORE.clear()


_param = effectful(_PYRO_PARAM_STORE.get_param, type="param")


def param(name, *args, **kwargs):
    """
    Saves the variable as a parameter in the param store.
    To interact with the param store or write to disk,
    see `Parameters <parameters.html>`_.

    :param str name: name of parameter
    :param init_tensor: initial tensor or lazy callable that returns a tensor.
        For large tensors, it may be cheaper to write e.g.
        ``lambda: torch.randn(100000)``, which will only be evaluated on the
        initial statement.
    :type init_tensor: torch.Tensor or callable
    :param constraint: torch constraint, defaults to ``constraints.real``.
Пример #2
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 def _make_reparameterizable_functions_effectful(self):
     for name, fn in zip(self.reparameterizable_functions, self.original_fns):
         effectful_fn = update_wrapper(effectful(fn, type="reparameterizable"), fn)
         setattr(F, name, effectful_fn)