// 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. #pragma once #include "paddle/fluid/framework/op_registry.h" namespace paddle { namespace operators { using LoDTensor = framework::LoDTensor; template class SequenceEnumerateKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& context) const override { auto* in = context.Input("X"); auto* out = context.Output("Out"); int win_size = context.Attr("win_size"); auto pad_value = static_cast(context.Attr("pad_value")); PADDLE_ENFORCE_EQ( in->lod().empty(), false, platform::errors::InvalidArgument( "Input(X) Tensor of SequenceEnumerateOp does not contain " "LoD information.")); auto in_dims = in->dims(); auto lod0 = in->lod()[0]; PADDLE_ENFORCE_EQ( static_cast(in_dims[0]), lod0.back(), platform::errors::InvalidArgument( "The actual input data's size mismatched with LoD information.")); PADDLE_ENFORCE_EQ( in_dims.size(), 2UL, platform::errors::InvalidArgument( "Input(X) of SequenceEnumerate operator's rank should be 2.")); PADDLE_ENFORCE_EQ(in_dims[1], 1, platform::errors::InvalidArgument( "Input(X) of SequenceEnumerate operator's 2nd " "dimension should be 1.")); // Generate enumerate sequence set auto in_data = in->data(); out->Resize({in_dims[0], win_size}); out->set_lod(in->lod()); auto out_data = out->mutable_data(context.GetPlace()); for (size_t i = 0; i < lod0.size() - 1; ++i) { if (lod0[i] == lod0[i + 1]) continue; int start = lod0[i]; int end = lod0[i + 1]; int copy_size = win_size < end - start + 1 ? win_size : end - start + 1; int mid = end + 1 - copy_size; int pad_num = win_size - copy_size; copy_size *= sizeof(T); for (int idx = start; idx < mid; ++idx) { std::memcpy(out_data, in_data + idx, copy_size); out_data += win_size; } for (int idx = mid; idx < end; ++idx) { copy_size -= sizeof(T); pad_num++; std::memcpy(out_data, in_data + idx, copy_size); T* pdata = out_data + copy_size / sizeof(T); for (int i = 0; i < pad_num; ++i) { pdata[i] = pad_value; } out_data += win_size; } } } }; } // namespace operators } // namespace paddle