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81 lines
2.7 KiB
81 lines
2.7 KiB
7 years ago
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#pragma once
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#include "paddle/framework/op_registry.h"
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#include "paddle/operators/math/softmax.h"
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namespace paddle {
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namespace operators {
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using Tensor = framework::Tensor;
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using LoDTensor = framework::LoDTensor;
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template <typename DeviceContext, typename T>
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class SequenceEraseKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& ctx) const override {
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auto* in = ctx.Input<LoDTensor>("X");
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auto* out = ctx.Output<LoDTensor>("Out");
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auto lod = in->lod();
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PADDLE_ENFORCE_EQ(lod.size(), 1UL, "Only support one level sequence now.");
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// auto dims = x->dims();
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/*
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const size_t level = lod.size() - 1;
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PADDLE_ENFORCE_EQ(dims[0], static_cast<int64_t>(lod[level].back()),
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"The first dimension of Input(X) should be equal to the "
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"sum of all sequences' lengths.");
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PADDLE_ENFORCE_EQ(dims[0], x->numel(),
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"The width of each timestep in Input(X) of "
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"SequenceEraseOp should be 1.");
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out->mutable_data<T>(ctx.GetPlace());
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*/
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auto tokens = ctx.Attr<std::vector<int>>("tokens");
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auto in_len = in->numel();
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auto in_dat = in->data<T>();
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auto lod0 = lod[0];
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std::vector<size_t> num_erased(in_len + 1, 0);
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for (int64_t i = 1; i < in_len + 1; ++i) {
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num_erased[i] = num_erased[i - 1];
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if (std::find(tokens.begin(), tokens.end(), in_dat[i - 1]) !=
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tokens.end()) {
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num_erased[i] += 1;
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}
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}
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std::vector<size_t> out_lod0(lod0.size(), 0);
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for (size_t i = 1; i < lod0.size(); ++i) {
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out_lod0[i] = lod0[i] - num_erased[lod0[i]];
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}
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auto out_len = in_len - num_erased[in_len];
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out->Resize({static_cast<int64_t>(out_len), 1});
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auto out_dat = out->mutable_data<T>(ctx.GetPlace());
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for (size_t i = 0; i < in_len; ++i) {
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if (num_erased[i] == num_erased[i + 1]) {
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out_dat[i - num_erased[i]] = in_dat[i];
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}
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}
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framework::LoD out_lod;
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out_lod.push_back(out_lod0);
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out->set_lod(out_lod);
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}
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};
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} // namespace operators
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} // namespace paddle
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