def get_preds()

in evaluations/th_evaluator.py [0:0]

• 19 lines of code
• 3 McCabe index (conditional complexity)

    def get_preds(self, batch, captions=None):
        with torch.no_grad():
            batch = 127.5 * (batch + 1)
            np_batch = batch.to(torch.uint8).cpu().numpy().transpose((0, 2, 3, 1))

            pred, spatial_pred = self.inception(batch)
            pred, spatial_pred = pred.reshape(
                [pred.shape[0], -1]
            ), spatial_pred.reshape([spatial_pred.shape[0], -1])

            clip_in = torch.stack(
                [clip_preproc(self.clip_preproc_fn, img) for img in np_batch]
            )
            clip_pred = self.clip_visual(clip_in.half().to(dist_util.dev()))
            if captions is not None:
                text_in = self.clip_tokenizer(captions)
                text_pred = self.clip_text(text_in.to(dist_util.dev()))
            else:
                # Hack to easily deal with no captions
                text_pred = self.clip_proj(clip_pred.half())
            text_pred = text_pred / text_pred.norm(dim=-1, keepdim=True)

        return pred, spatial_pred, clip_pred, text_pred, np_batch