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c++ code format (#4527)

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zhupengyang
2025-10-22 17:59:50 +08:00
committed by GitHub
parent d7bcedf421
commit 3a6883ac1a
97 changed files with 8760 additions and 7382 deletions
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custom_ops/cpu_ops/simd_sort.cc
+29 -29
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@@ -21,45 +21,45 @@ void probs_sort(const float *probs,
float *ProbsVals,
int vocab_size,
int bsz) {
float cursum = 0;
std::vector<int64_t> elementsIds(vocab_size);
std::vector<float> elementsProbs(vocab_size);
float cursum = 0;
std::vector<int64_t> elementsIds(vocab_size);
std::vector<float> elementsProbs(vocab_size);
#pragma omp parallel for
for (int j = 0; j < vocab_size; j++) {
elementsIds[j] = j;
elementsProbs[j] = probs[j];
}
x86simdsortStatic::keyvalue_qsort(
elementsProbs.data(), elementsIds.data(), vocab_size, false, true);
for (int j = 0; j < vocab_size; j++) {
elementsIds[j] = j;
elementsProbs[j] = probs[j];
}
x86simdsortStatic::keyvalue_qsort(
elementsProbs.data(), elementsIds.data(), vocab_size, false, true);
#pragma omp parallel for
for (int j = 0; j < vocab_size; ++j) {
ProbsVals[j] = elementsProbs[j];
ProbsIds[j] = elementsIds[j];
}
for (int j = 0; j < vocab_size; ++j) {
ProbsVals[j] = elementsProbs[j];
ProbsIds[j] = elementsIds[j];
}
}
std::vector<paddle::Tensor> SimdSort(const paddle::Tensor &probs) {
const int bsz = probs.shape()[0];
const int vocab_size = probs.shape()[1];
auto sorted_indices = paddle::empty(
{bsz, vocab_size}, paddle::DataType::INT64, probs.place());
auto sorted_probs = paddle::empty(
{bsz, vocab_size}, paddle::DataType::FLOAT32, probs.place());
probs_sort(probs.data<float>(),
const_cast<int64_t *>(sorted_indices.data<int64_t>()),
const_cast<float *>(sorted_probs.data<float>()),
vocab_size,
bsz);
return {sorted_indices, sorted_probs};
const int bsz = probs.shape()[0];
const int vocab_size = probs.shape()[1];
auto sorted_indices =
paddle::empty({bsz, vocab_size}, paddle::DataType::INT64, probs.place());
auto sorted_probs = paddle::empty(
{bsz, vocab_size}, paddle::DataType::FLOAT32, probs.place());
probs_sort(probs.data<float>(),
const_cast<int64_t *>(sorted_indices.data<int64_t>()),
const_cast<float *>(sorted_probs.data<float>()),
vocab_size,
bsz);
return {sorted_indices, sorted_probs};
}
std::vector<std::vector<int64_t>> SimdSortInferShape(
const std::vector<int64_t> &probs_shape) {
int64_t bsz = probs_shape[0];
int64_t vocab_size = probs_shape[1];
return {{bsz, vocab_size}, {bsz, vocab_size}};
int64_t bsz = probs_shape[0];
int64_t vocab_size = probs_shape[1];
return {{bsz, vocab_size}, {bsz, vocab_size}};
}
std::vector<paddle::DataType> SimdSortInferDtype(
const paddle::DataType &probs_dtype) {
return {paddle::DataType::INT64, paddle::DataType::FLOAT32};
return {paddle::DataType::INT64, paddle::DataType::FLOAT32};
}
PD_BUILD_STATIC_OP(simd_sort)
.Inputs({"probs"})