未验证 提交 4440d7ce 编写于 作者: W wangchaochaohu 提交者: GitHub

test=develop cuda realization of label smooth op (#19175)

上级 31c5a5ee
......@@ -12,15 +12,101 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/framework/tensor.h"
#include "paddle/fluid/operators/label_smooth_op.h"
namespace paddle {
namespace operators {
template <typename T>
__global__ void LabelSmoothRunOriginKernel(const int N, const float epsilon,
const int label_dim, const T* src,
T* dst) {
int idx = blockDim.x * blockIdx.x + threadIdx.x;
for (; idx < N; idx += blockDim.x * gridDim.x) {
dst[idx] = static_cast<T>(1 - epsilon) * src[idx] +
static_cast<T>(epsilon / label_dim);
}
}
template <typename T>
__global__ void LabelSmoothRunDistKernel(const int N, const float epsilon,
const int dist_numel, const T* src,
const T* dist_data, T* dst) {
int idx = blockDim.x * blockIdx.x + threadIdx.x;
for (; idx < N; idx += blockDim.x * gridDim.x) {
int dist_idx = idx - (idx / dist_numel) * dist_numel;
dst[idx] = static_cast<T>(1 - epsilon) * src[idx] +
static_cast<T>(epsilon) * dist_data[dist_idx];
}
}
template <typename T>
__global__ void LabelSmoothGradRunKernel(const int N, const float epsilon,
const T* src, T* dst) {
int idx = blockDim.x * blockIdx.x + threadIdx.x;
for (; idx < N; idx += blockDim.x * gridDim.x) {
dst[idx] = static_cast<T>(1 - epsilon) * src[idx];
}
}
template <typename DeviceContext, typename T>
class LabelSmoothGPUKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const {
auto* out_t = ctx.Output<framework::LoDTensor>("Out");
auto* in_t = ctx.Input<framework::LoDTensor>("X");
auto* dist_t = ctx.Input<framework::Tensor>("PriorDist");
auto label_dim = in_t->dims()[1];
auto epsilon = ctx.Attr<float>("epsilon");
auto& dev = *ctx.template device_context<DeviceContext>().eigen_device();
auto size_prob = in_t->numel();
const T* in_data = in_t->data<T>();
T* out_data = out_t->mutable_data<T>(ctx.GetPlace());
int threads = 512;
int grid = (size_prob + threads - 1) / threads;
auto stream = ctx.cuda_device_context().stream();
if (dist_t) {
auto dist_numel = dist_t->numel();
const T* dist_data = dist_t->data<T>();
LabelSmoothRunDistKernel<T><<<grid, threads, 0, stream>>>(
size_prob, epsilon, dist_numel, in_data, dist_data, out_data);
} else {
LabelSmoothRunOriginKernel<T><<<grid, threads, 0, stream>>>(
size_prob, epsilon, label_dim, in_data, out_data);
}
}
};
template <typename DeviceContext, typename T>
class LabelSmoothGradGPUKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const {
auto* d_out_t = ctx.Input<framework::Tensor>(framework::GradVarName("Out"));
auto* d_in_t = ctx.Output<framework::Tensor>(framework::GradVarName("X"));
d_in_t->mutable_data<T>(ctx.GetPlace());
auto epsilon = ctx.Attr<float>("epsilon");
auto& dev = *ctx.template device_context<DeviceContext>().eigen_device();
const T* in_data = d_out_t->data<T>();
auto size_prob = d_out_t->numel();
T* out_data = d_in_t->mutable_data<T>(ctx.GetPlace());
int threads = 512;
int grid = (size_prob + threads - 1) / threads;
auto stream = ctx.cuda_device_context().stream();
LabelSmoothGradRunKernel<T><<<grid, threads, 0, stream>>>(
size_prob, epsilon, in_data, out_data);
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OP_CUDA_KERNEL(
label_smooth,
ops::LabelSmoothKernel<paddle::platform::CUDADeviceContext, float>,
ops::LabelSmoothKernel<paddle::platform::CUDADeviceContext, double>);
ops::LabelSmoothGPUKernel<paddle::platform::CUDADeviceContext, float>,
ops::LabelSmoothGPUKernel<paddle::platform::CUDADeviceContext, double>);
REGISTER_OP_CUDA_KERNEL(
label_smooth_grad,
ops::LabelSmoothGradKernel<paddle::platform::CUDADeviceContext, float>,
ops::LabelSmoothGradKernel<paddle::platform::CUDADeviceContext, double>);
ops::LabelSmoothGradGPUKernel<paddle::platform::CUDADeviceContext, float>,
ops::LabelSmoothGradGPUKernel<paddle::platform::CUDADeviceContext, double>);
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