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81 lines
2.8 KiB
81 lines
2.8 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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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 <vector>
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#include "paddle/fluid/framework/op_registry.h"
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namespace paddle {
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namespace operators {
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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<framework::LoDTensor>("X");
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auto* out = ctx.Output<framework::LoDTensor>("Out");
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auto lod = in->lod();
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PADDLE_ENFORCE_EQ(
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lod.empty(), false,
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platform::errors::InvalidArgument("Input(X) Tensor of SequenceEraseOp "
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"does not contain LoD information."));
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PADDLE_ENFORCE_EQ(lod[lod.size() - 1].back(), (size_t)in->numel(),
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platform::errors::InvalidArgument(
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"The actual input size %d mismatches with the LoD "
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"information size %d.",
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lod[lod.size() - 1].back(), (size_t)in->numel()));
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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 last_lod = lod[lod.size() - 1];
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std::vector<size_t> num_erased(in_len + 1, 0);
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std::vector<size_t> out_last_lod(1, 0);
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for (size_t i = 0; i < last_lod.size() - 1; ++i) {
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size_t num_out = 0;
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for (auto j = last_lod[i] + 1; j <= last_lod[i + 1]; ++j) {
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num_erased[j] = num_erased[j - 1];
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if (std::find(tokens.begin(), tokens.end(), in_dat[j - 1]) !=
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tokens.end()) {
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num_erased[j] += 1;
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} else {
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num_out += 1;
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}
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}
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out_last_lod.push_back(out_last_lod.back() + num_out);
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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 (int64_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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for (size_t i = 0; i < lod.size() - 1; ++i) {
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out_lod.push_back(lod[i]);
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}
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out_lod.push_back(out_last_lod);
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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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