dpr/models/biencoder.py [218:234]:
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            question_tensors.append(tensorizer.text_to_tensor(question))

        ctxs_tensor = torch.cat([ctx.view(1, -1) for ctx in ctx_tensors], dim=0)
        questions_tensor = torch.cat([q.view(1, -1) for q in question_tensors], dim=0)

        ctx_segments = torch.zeros_like(ctxs_tensor)
        question_segments = torch.zeros_like(questions_tensor)

        return BiEncoderBatch(
            questions_tensor,
            question_segments,
            ctxs_tensor,
            ctx_segments,
            positive_ctx_indices,
            hard_neg_ctx_indices,
            "question",
        )
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dpr/models/biencoder.py [321:337]:
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                question_tensors.append(tensorizer.text_to_tensor(question))

        ctxs_tensor = torch.cat([ctx.view(1, -1) for ctx in ctx_tensors], dim=0)
        questions_tensor = torch.cat([q.view(1, -1) for q in question_tensors], dim=0)

        ctx_segments = torch.zeros_like(ctxs_tensor)
        question_segments = torch.zeros_like(questions_tensor)

        return BiEncoderBatch(
            questions_tensor,
            question_segments,
            ctxs_tensor,
            ctx_segments,
            positive_ctx_indices,
            hard_neg_ctx_indices,
            "question",
        )
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