flambe.sampler.episodic
¶
Module Contents¶
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class
flambe.sampler.episodic.
EpisodicSampler
(n_support: int, n_query: int, n_episodes: int, n_classes: int = None, pad_index: int = 0, balance_query: bool = False)[source]¶ Bases:
flambe.sampler.Sampler
Implement an EpisodicSample object.
Currently only supports sequence inputs.
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sample
(self, data: Sequence[Sequence[torch.Tensor]], n_epochs: int = 1)[source]¶ Sample from the list of features and yields batches.
Parameters: - data (Sequence[Sequence[torch.Tensor, torch.Tensor]]) – The input data as a list of (source, target) pairs
- n_epochs (int, optional) – The number of epochs to run in the output iterator. For this object, the total number of batches will be (n_episodes * n_epochs)
Yields: Iterator[Tuple[Tensor, Tensor, Tensor, Tensor]] – In order: the query_source, the query_target the support_source, and the support_target tensors. For sequences, the batch is used as first dimension.
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