/* Copyright (c) 2022 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. */ #ifdef PADDLE_WITH_MLU #include #include "paddle/fluid/framework/op_registry.h" namespace paddle { namespace operators { using Tensor = phi::DenseTensor; using LoDTensor = framework::LoDTensor; using SelectedRows = phi::SelectedRows; template class ShapeMLUKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& ctx) const override { auto* in_var = ctx.InputVar("Input"); framework::DDim in_dims; if (in_var->IsType()) { in_dims = in_var->Get().value().dims(); } else { in_dims = in_var->Get().dims(); } auto* out_t = ctx.Output("Out"); out_t->Resize({in_dims.size()}); out_t->mutable_data(ctx.GetPlace()); // shape op cpu Tensor shape_on_cpu( framework::TransToPhiDataType(framework::proto::VarType::INT32)); shape_on_cpu.Resize({in_dims.size()}); auto cpu_data = shape_on_cpu.mutable_data(platform::CPUPlace()); for (int i = 0; i < in_dims.size(); ++i) { cpu_data[i] = in_dims[i]; } // cpu to mlu auto& dev_ctx = ctx.template device_context(); framework::TensorCopy(shape_on_cpu, ctx.GetPlace(), dev_ctx, out_t); dev_ctx.Wait(); } }; } // namespace operators } // namespace paddle namespace ops = paddle::operators; REGISTER_OP_MLU_KERNEL(shape, ops::ShapeMLUKernel, ops::ShapeMLUKernel, ops::ShapeMLUKernel, ops::ShapeMLUKernel, ops::ShapeMLUKernel, ops::ShapeMLUKernel, ops::ShapeMLUKernel, ops::ShapeMLUKernel); #endif