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Kavya Srinet
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doc/design/ops/sequence_decoder.md

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@@ -154,7 +154,7 @@ In this way, users can customize anything on the input or output of beam search,
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2. Remove some specific candidate in `selected_ids`.
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3. Get the final `translation_ids`, remove the translation sequence in it.
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The implementation of sequence decoder can reuse the C++ class [RNNAlgorithm](https://github.com/Superjom/Paddle/blob/68cac3c0f8451fe62a4cdf156747d6dc0ee000b3/paddle/operators/dynamic_recurrent_op.h#L30),
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The implementation of sequence decoder can reuse the C++ class: [RNNAlgorithm](https://github.com/Superjom/Paddle/blob/68cac3c0f8451fe62a4cdf156747d6dc0ee000b3/paddle/operators/dynamic_recurrent_op.h#L30),
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so the python syntax is quite similar to that of an [RNN](https://github.com/Superjom/Paddle/blob/68cac3c0f8451fe62a4cdf156747d6dc0ee000b3/doc/design/block.md#blocks-with-for-and-rnnop).
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Both of them are two-level `LoDTensors`:

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