enchanter.utils

enchanter.utils.comet

enchanter.utils.backend

enchanter.utils.backend.is_scalar(data: Union[numbers.Number, numpy.ndarray, torch.Tensor]) → bool

Returns True if the type of data is a scalar type.

Parameters

data (Union[Number, Union[np.ndarray, torch.Tensor]]) – Numerical value

Returns

True if data is a scalar type, False if it is not.

Examples

>>> a = torch.tensor([1.0])
>>> is_scalar(a)    # True
>>> a = torch.tensor(1.0)
>>> is_scalar(a)    # True
>>> a = torch.tensor([1, 2, 3])
>>> is_scalar(a)    # False
>>> a = 1.0
>>> is_scalar(a)    # True

enchanter.utils.datasets

class enchanter.utils.datasets.TimeSeriesLabeledDataset(data: Union[torch.Tensor, numpy.ndarray], targets: Union[torch.Tensor, numpy.ndarray], transform: Optional[Callable[[torch.Tensor], torch.Tensor]] = None)

Bases: Generic[torch.utils.data.dataset.T_co]

Examples

>>> from torch.utils.data import DataLoader
>>> ds = TimeSeriesLabeledDataset(data=..., targets=...)
>>> loader = DataLoader(ds)
>>> data, targets = next(iter(loader))

class enchanter.utils.datasets.TimeSeriesUnlabeledDataset(data: Union[torch.Tensor, numpy.ndarray], transform: Optional[Callable[[torch.Tensor], torch.Tensor]] = None)

Bases: Generic[torch.utils.data.dataset.T_co]

Examples

>>> from torch.utils.data import DataLoader
>>> ds = TimeSeriesUnlabeledDataset(data=...)
>>> loader = DataLoader(ds)
>>> data = next(iter(loader))

enchanter.utils.visualize