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Revert "Convert Gelu to use TryParallelFor (#3599)"

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This reverts commit 2579a72a88.
This commit is contained in:
Edward Chen 2020-04-21 18:45:20 +00:00
parent d50c3e7a71
commit 28a0c863b1
1 changed files with 29 additions and 14 deletions
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43
onnxruntime/contrib_ops/cpu/activations.h
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@ -40,20 +40,35 @@ class Gelu : public OpKernel {
const auto* X = context->Input<Tensor>(0);
Tensor* Y = context->Output(0, X->Shape());
concurrency::ThreadPool* tp = context->GetOperatorThreadPool();
const int64_t input_size = X->Shape().Size();
std::ptrdiff_t batch_size = static_cast<std::ptrdiff_t>(input_size);
//The cost comes from microbenchmark(manual tunning).
const double cost = 10.0;
const T* data = X->template Data<T>();
T* output = Y->template MutableData<T>();
concurrency::ThreadPool::TryParallelFor(tp, batch_size, cost, [data, output](ptrdiff_t first, ptrdiff_t last) {
ptrdiff_t len = last - first;
onnxruntime::ConstEigenVectorArrayMap<T> xm(data + first, len);
onnxruntime::EigenVectorArrayMap<T> ym(output + first, len);
ym = xm * static_cast<float>(M_SQRT1_2);
MlasComputeErf(output, output, len);
ym = xm * 0.5f * (ym + 1.0f);
});
if (nullptr != tp) {
const T* input = X->template Data<T>();
T* output = Y->template MutableData<T>();
int task_count = tp->NumThreads();
int64_t elem_count = X->Shape().Size();
if (elem_count > task_count) {
tp->SimpleParallelFor(task_count, [input,
output,
elem_count,
task_count](std::ptrdiff_t i) {
int64_t elem_inx_start = i * elem_count / task_count;
int64_t elem_inx_end = (i + 1) * elem_count / task_count;
for (int64_t elem_inx = elem_inx_start; elem_inx < elem_inx_end; elem_inx++) {
output[elem_inx] = input[elem_inx] * static_cast<float>(M_SQRT1_2);
}
MlasComputeErf(output + elem_inx_start, output + elem_inx_start, elem_inx_end - elem_inx_start);
for (int64_t elem_inx = elem_inx_start; elem_inx < elem_inx_end; elem_inx++) {
output[elem_inx] = 0.5f * input[elem_inx] * (output[elem_inx] + 1.0f);
}
});
return Status::OK();
}
}
EIGEN_X_VAR(xm);
EIGEN_Y_VAR(ym);
ym = xm * static_cast<float>(M_SQRT1_2);
MlasComputeErf(Y->template MutableData<T>(), Y->template MutableData<T>(), X->Shape().Size());
ym = xm * 0.5f * (ym + 1.0f);
return Status::OK();
}
};