// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // 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 "lite/kernels/xpu/layer_norm_compute.h" #include "lite/backends/xpu/xpu_header_sitter.h" #include "lite/core/op_registry.h" namespace paddle { namespace lite { namespace kernels { namespace xpu { void LayerNormCompute::Run() { auto& param = this->Param(); auto& ctx = this->ctx_->As(); auto x_dims = param.X->dims(); auto axis = param.begin_norm_axis; auto matrix_dim = x_dims.Flatten2D(axis); float epsilon = param.epsilon; int r = xdnn::layer_norm(ctx.GetRawContext(), /* context */ matrix_dim[0], /* m */ matrix_dim[1], /* n */ param.X->data(), /* in */ param.Y->mutable_data(TARGET(kXPU)), /* out */ param.Scale->data(), /* scale */ param.Bias->data(), /* bias */ epsilon /* epsilon */); CHECK_EQ(r, 0); } } // namespace xpu } // namespace kernels } // namespace lite } // namespace paddle REGISTER_LITE_KERNEL(layer_norm, kXPU, kFloat, kNCHW, paddle::lite::kernels::xpu::LayerNormCompute, def) .BindInput("X", {LiteType::GetTensorTy(TARGET(kXPU))}) .BindInput("Scale", {LiteType::GetTensorTy(TARGET(kXPU))}) .BindInput("Bias", {LiteType::GetTensorTy(TARGET(kXPU))}) .BindOutput("Y", {LiteType::GetTensorTy(TARGET(kXPU))}) .BindOutput("Mean", {LiteType::GetTensorTy(TARGET(kXPU))}) .BindOutput("Variance", {LiteType::GetTensorTy(TARGET(kXPU))}) .Finalize();