// 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/core/kernel.h" #include "lite/core/op_registry.h" namespace paddle { namespace lite { namespace kernels { namespace arm { template class FillConstantCompute : public KernelLite { public: using param_t = operators::FillConstantParam; void Run() override { auto& param = *param_.get_mutable(); auto& context = ctx_->As(); auto data = param.Out->template mutable_data(); for (int i = 0; i < param.Out->numel(); i++) { data[i] = param.value; } } virtual ~FillConstantCompute() = default; }; template class FillConstantBatchLikeCompute : public KernelLite { public: using param_t = operators::FillConstantBatchLikeParam; void Run() override { auto& param = *param_.get_mutable(); auto& context = ctx_->As(); if (param.input->lod().size() && param.input_dim_idx == 0) { auto odims = param.out->dims(); odims[param.output_dim_idx] = param.input->lod().back().size() - 1; param.out->Resize(odims); } auto data = param.out->template mutable_data(); for (int i = 0; i < param.out->numel(); i++) { data[i] = param.value; } } virtual ~FillConstantBatchLikeCompute() = default; }; } // namespace arm } // namespace kernels } // namespace lite } // namespace paddle // float REGISTER_LITE_KERNEL(fill_constant, kARM, kFloat, kNCHW, paddle::lite::kernels::arm::FillConstantCompute, def) .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kARM))}) .Finalize(); REGISTER_LITE_KERNEL( fill_constant_batch_size_like, kARM, kFloat, kNCHW, paddle::lite::kernels::arm::FillConstantBatchLikeCompute, def) .BindInput("Input", {LiteType::GetTensorTy(TARGET(kARM))}) .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kARM))}) .Finalize();