Base Sampler interface.
Objects implementing this interface should implement two methods:
- sample: takes a set of data and returns an iterator
- lenght: takes a set of data and return the length of the
- iterator that would be given by the sample method
Sampler objects are used inside the Trainer to provide the data to the models. Note that pushing the data to the appropriate device is usually done inside the Trainer.
sample(self, data: Sequence[Sequence[torch.Tensor]], n_epochs: int = 1)¶
Sample from the list of features and yields batches.
- data (Sequence[Sequence[torch.Tensor, ..]]) – The input data to sample from
- n_epochs (int, optional) – The number of epochs to run in the output iterator.
Iterator[Tuple[Tensor]] – A batch of data, as a tuple of Tensors
length(self, data: Sequence[Sequence[torch.Tensor]])¶
Return the number of batches in the sampler.
Parameters: data (Sequence[Sequence[torch.Tensor, ..]]) – The input data to sample from Returns: The number of batches that would be created per epoch Return type: int