Method get_eval_dataloader

textattack/trainer.py:452–487

Returns the :obj:`torch.utils.data.DataLoader` for evaluation. Args: dataset (:class:`~textattack.datasets.Dataset`): Dataset to use for evaluation. batch_size (:obj:`int`): Batch size for evaluation. Returns: :obj:

(self, dataset, batch_size)

        return train_dataloader

    def get_eval_dataloader(self, dataset, batch_size):
        """Returns the :obj:`torch.utils.data.DataLoader` for evaluation.

        Args:
            dataset (:class:`~textattack.datasets.Dataset`):
                Dataset to use for evaluation.
            batch_size (:obj:`int`):
                Batch size for evaluation.
        Returns:
            :obj:`torch.utils.data.DataLoader`
        """

        # Helper functions for collating data
        def collate_fn(data):
            input_texts = []
            targets = []
            for _input, label in data:
                if isinstance(_input, collections.OrderedDict):
                    _input = tuple(_input.values())
                else:
                    _input = tuple(_input)

                if len(_input) == 1:
                    _input = _input[0]
                input_texts.append(_input)
                targets.append(label)
            return input_texts, torch.tensor(targets)

        eval_dataloader = torch.utils.data.DataLoader(
            dataset,
            batch_size=batch_size,
            shuffle=True,
            collate_fn=collate_fn,
            pin_memory=True,
        )
        return eval_dataloader

    def training_step(self, model, tokenizer, batch):
        """Perform a single training step on a batch of inputs.