// Copyright (c) 2018 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 "paddle/fluid/operators/stack_op.h" #include #ifdef PADDLE_WITH_XPU namespace paddle { namespace operators { using framework::Tensor; template class StackXPUKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& ctx) const override { auto x = ctx.MultiInput("X"); auto* y = ctx.Output("Y"); int axis = ctx.Attr("axis"); if (axis < 0) { axis += x[0]->dims().size() + 1; } auto* y_data = y->mutable_data(ctx.GetPlace()); auto& dim = x[0]->dims(); std::vector xdims; for (auto i = 0; i < dim.size(); ++i) { xdims.push_back(dim[i]); } xdims.push_back(1); std::vector> xdims_list; int n = static_cast(x.size()); for (int i = 0; i < n; i++) { xdims_list.push_back(xdims); } std::vector x_list; for (int i = 0; i < n; i++) { x_list.push_back(x[i]->data()); } auto& dev_ctx = ctx.template device_context(); int r = xpu::concat(dev_ctx.x_context(), x_list, y_data, xdims_list, axis); PADDLE_ENFORCE_EQ(r, xpu::Error_t::SUCCESS, platform::errors::External( "The stack XPU API return wrong value[%d %s]", r, XPUAPIErrorMsg[r])); } }; } // namespace operators } // namespace paddle namespace plat = paddle::platform; namespace ops = paddle::operators; REGISTER_OP_XPU_KERNEL(stack, ops::StackXPUKernel); #endif