未验证 提交 2e331c65 编写于 作者: D dzhwinter 提交者: GitHub

accelerate dropout (#9902)

* accelerate dropout

* accelerate dropout

* "fix the dropout test"

* "rerun ci"

* "fix ci"

* "rerun ci"

* "fix ci"

* "fix"

* "stage"

* disable
上级 0b8630b9
......@@ -24,21 +24,11 @@ namespace paddle {
namespace operators {
template <typename T>
__global__ void RandomGenerator(const size_t n, const int seed,
const float dropout_prob, const T* src,
T* mask_data, T* dst) {
thrust::minstd_rand rng;
rng.seed(seed);
thrust::uniform_real_distribution<float> dist(0, 1);
__global__ void RandomGenerator(const size_t n, const T* src,
const T* cpu_mask_data, T* mask_data, T* dst) {
int idx = blockDim.x * blockIdx.x + threadIdx.x;
for (; idx < n; idx += blockDim.x * gridDim.x) {
rng.discard(idx);
if (dist(rng) < dropout_prob) {
mask_data[idx] = static_cast<T>(0);
} else {
mask_data[idx] = static_cast<T>(1);
}
mask_data[idx] = cpu_mask_data[idx];
dst[idx] = mask_data[idx] * src[idx];
}
}
......@@ -66,15 +56,27 @@ class GPUDropoutKernel : public framework::OpKernel<T> {
std::random_device rnd;
int seed =
context.Attr<bool>("fix_seed") ? context.Attr<int>("seed") : rnd();
std::minstd_rand engine;
engine.seed(seed);
std::uniform_real_distribution<float> dist(0, 1);
framework::Vector<T> cpu_mask(size);
for (size_t i = 0; i < size; ++i) {
if (dist(engine) < dropout_prob) {
cpu_mask[i] = static_cast<T>(0);
} else {
cpu_mask[i] = static_cast<T>(1);
}
}
int threads = 512;
int grid = (x->numel() + threads - 1) / threads;
RandomGenerator<
T><<<grid, threads, 0, context.cuda_device_context().stream()>>>(
size, seed, dropout_prob, x_data, mask_data, y_data);
size, x_data, cpu_mask.CUDAData(context.GetPlace()), mask_data,
y_data);
} else {
auto X = EigenMatrix<T>::Reshape(*x, 1);
auto Y = EigenMatrix<T>::Reshape(*y, 1);
auto X = EigenVector<T>::Flatten(*x);
auto Y = EigenVector<T>::Flatten(*y);
Y.device(place) = X * static_cast<T>(1.0f - dropout_prob);
}
}
......@@ -87,6 +89,8 @@ namespace ops = paddle::operators;
namespace plat = paddle::platform;
REGISTER_OP_CUDA_KERNEL(
dropout, ops::GPUDropoutKernel<plat::CUDADeviceContext, float>,
ops::GPUDropoutKernel<plat::CUDADeviceContext, double>,
ops::GPUDropoutKernel<plat::CUDADeviceContext, plat::float16>);
REGISTER_OP_CUDA_KERNEL(dropout_grad,
ops::DropoutGradKernel<plat::CUDADeviceContext, double>,
ops::DropoutGradKernel<plat::CUDADeviceContext, float>);
......@@ -24,7 +24,7 @@ namespace operators {
using Tensor = framework::Tensor;
template <typename T, int MajorType = Eigen::RowMajor,
typename IndexType = Eigen::DenseIndex>
using EigenMatrix = framework::EigenMatrix<T, MajorType, IndexType>;
using EigenVector = framework::EigenVector<T, MajorType, IndexType>;
template <typename DeviceContext, typename T>
class CPUDropoutKernel : public framework::OpKernel<T> {
......@@ -60,8 +60,8 @@ class CPUDropoutKernel : public framework::OpKernel<T> {
}
}
} else {
auto X = EigenMatrix<T>::Reshape(*x, 1);
auto Y = EigenMatrix<T>::Reshape(*y, 1);
auto X = EigenVector<T>::Flatten(*x);
auto Y = EigenVector<T>::Flatten(*y);
auto& place =
*context.template device_context<DeviceContext>().eigen_device();
Y.device(place) = X * (1.0f - dropout_prob);
......@@ -81,9 +81,9 @@ class DropoutGradKernel : public framework::OpKernel<T> {
auto* mask = context.Input<Tensor>("Mask");
grad_x->mutable_data<T>(context.GetPlace());
auto M = EigenMatrix<T>::Reshape(*mask, 1);
auto dX = EigenMatrix<T>::Reshape(*grad_x, 1);
auto dY = EigenMatrix<T>::Reshape(*grad_y, 1);
auto M = EigenVector<T>::Flatten(*mask);
auto dX = EigenVector<T>::Flatten(*grad_x);
auto dY = EigenVector<T>::Flatten(*grad_y);
auto& place =
*context.template device_context<DeviceContext>().eigen_device();
......
......@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include <unistd.h>
#include <iostream>
#include <string>
#include <thread> // NOLINT
......@@ -32,14 +33,16 @@ namespace m = paddle::operators::math;
USE_OP(dropout);
static paddle::framework::DDim dims = {10, 10};
void Compare(f::Scope* scope, const p::DeviceContext& ctx) {
// init
auto var = scope->Var("X");
auto tensor = var->GetMutable<f::LoDTensor>();
tensor->Resize({10, 10});
tensor->Resize(dims);
std::vector<float> init;
for (int64_t i = 0; i < 10 * 10; ++i) {
for (int64_t i = 0; i < f::product(dims); ++i) {
init.push_back(1.0);
}
......@@ -48,18 +51,19 @@ void Compare(f::Scope* scope, const p::DeviceContext& ctx) {
auto place = ctx.GetPlace();
auto out_var = scope->Var("Out");
auto out_tensor = out_var->GetMutable<f::LoDTensor>();
out_tensor->Resize({10, 10});
out_tensor->Resize(dims);
out_tensor->mutable_data<float>(place); // allocate
auto mask_var = scope->Var("Mask");
auto mask_tensor = mask_var->GetMutable<f::LoDTensor>();
mask_tensor->Resize({10, 10});
mask_tensor->Resize(dims);
mask_tensor->mutable_data<float>(place); // allocate
// run
f::AttributeMap attrs;
float dropout_prob = 0.5;
attrs.insert({"fix_seed", 1});
attrs.insert({"is_test", false});
attrs.insert({"fix_seed", true});
attrs.insert({"seed", 3});
attrs.insert({"dropout_prob", dropout_prob});
auto dropout_op = f::OpRegistry::CreateOp(
......@@ -69,6 +73,7 @@ void Compare(f::Scope* scope, const p::DeviceContext& ctx) {
std::vector<float> out_vec;
TensorToVector(*out_tensor, ctx, &out_vec);
ctx.Wait();
std::vector<float> std_out = {
0, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1,
......@@ -83,22 +88,22 @@ void Compare(f::Scope* scope, const p::DeviceContext& ctx) {
}
}
// TODO(wyi): Due to
// https://github.com/PaddlePaddle/Paddle/issues/9507, I temporarily
// disable this test to remove the prevention of the merge of
// unrelated PRs.
/*
TEST(Dropout, CPUDense) {
f::Scope scope;
p::CPUPlace place;
p::CPUDeviceContext ctx(place);
Compare(scope, ctx);
Compare(&scope, ctx);
}
// TODO(wyi, dzhwinter): Due to
// https://github.com/PaddlePaddle/Paddle/issues/9507, I temporarily
// disable this test to remove the prevention of the merge of
// unrelated PRs.
/*
TEST(Dropout, GPUDense) {
f::Scope scope;
p::CUDAPlace place;
p::CUDADeviceContext ctx(place);
Compare(scope, ctx);
Compare(&scope, ctx);
}
*/
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