未验证 提交 65c859db 编写于 作者: Q Qiao Longfei 提交者: GitHub

beam_search_decode support multi data type (#5847)

* beam_search_decode support multi data type

* add VisitDataType for beam search decode

* use Specialization to handle bool

* move Specialization of BeamSearchDecodeFunctor out of class
上级 3a76062c
......@@ -17,6 +17,36 @@ limitations under the License. */
namespace paddle {
namespace operators {
struct BeamSearchDecodeFunctor {
BeamSearchDecodeFunctor(const LoDTensorArray& step_ids,
const LoDTensorArray& step_scores,
LoDTensor* id_tensor, LoDTensor* score_tensor)
: step_ids_(step_ids),
step_scores_(step_scores),
id_tensor_(id_tensor),
score_tensor_(score_tensor) {}
template <typename T>
void operator()() const;
const LoDTensorArray& step_ids_;
const LoDTensorArray& step_scores_;
LoDTensor* id_tensor_;
LoDTensor* score_tensor_;
};
template <typename T>
void BeamSearchDecodeFunctor::operator()() const {
BeamSearchDecoder<T> beam_search_decoder;
beam_search_decoder.PackAllSteps(step_ids_, step_scores_, id_tensor_,
score_tensor_);
}
template <>
void BeamSearchDecodeFunctor::operator()<bool>() const {
PADDLE_THROW("beam search decode op does not support bool!");
}
class BeamSearchDecodeOp : public framework::OperatorBase {
public:
BeamSearchDecodeOp(const std::string& type,
......@@ -45,9 +75,9 @@ class BeamSearchDecodeOp : public framework::OperatorBase {
LoDTensor* sentenceIds = ctx.Output<LoDTensor>("SentenceIds");
LoDTensor* sentenceScores = ctx.Output<LoDTensor>("SentenceScores");
BeamSearchDecoder<float> beam_search_decoder;
beam_search_decoder.PackAllSteps(*ids, *scores, sentenceIds,
sentenceScores);
framework::VisitDataType(
framework::ToDataType(scores->at(0).type()),
BeamSearchDecodeFunctor(*ids, *scores, sentenceIds, sentenceScores));
}
};
......
......@@ -35,15 +35,15 @@ class TestBeamSearchDecodeOp(unittest.TestCase):
self.append_lod_tensor(
scores, [[0, 3, 6], [0, 1, 2, 3, 4, 5, 6]],
np.array(
[1, 2, 3, 4, 5, 6], dtype="float32"))
[1, 2, 3, 4, 5, 6], dtype="float64"))
self.append_lod_tensor(
scores, [[0, 3, 6], [0, 1, 1, 3, 5, 5, 6]],
np.array(
[0, 1, 2, 3, 4, 5], dtype="float32"))
[0, 1, 2, 3, 4, 5], dtype="float64"))
self.append_lod_tensor(
scores, [[0, 3, 6], [0, 0, 1, 2, 3, 4, 5]],
np.array(
[0, 1, 2, 3, 4], dtype="float32"))
[0, 1, 2, 3, 4], dtype="float64"))
sentence_ids = self.scope.var("sentence_ids").get_tensor()
sentence_scores = self.scope.var("sentence_scores").get_tensor()
......
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