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279 lines
11 KiB
279 lines
11 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 <set>
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#include <string>
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#include <vector>
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#include "paddle/fluid/framework/eigen.h"
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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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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 ChunkEvalKernel : public framework::OpKernel<T> {
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public:
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struct Segment {
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int begin;
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int end;
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int type;
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bool operator==(const Segment& y) const {
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return begin == y.begin && end == y.end && type == y.type;
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}
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};
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void GetSegments(const int64_t* label, int length,
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std::vector<Segment>* segments, int num_chunk_types,
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int num_tag_types, int other_chunk_type, int tag_begin,
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int tag_inside, int tag_end, int tag_single) const {
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segments->clear();
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segments->reserve(length);
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int chunk_start = 0;
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bool in_chunk = false;
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int tag = -1;
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int type = other_chunk_type;
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for (int i = 0; i < length; ++i) {
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int prev_tag = tag;
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int prev_type = type;
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PADDLE_ENFORCE_LE(
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label[i], num_chunk_types * num_tag_types,
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platform::errors::InvalidArgument(
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"The value of Input(Label) should be less than the number of "
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"chunk types times the number of tag types, but received %d "
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"(Label) vs %d (chunk types) * %d (tag types).",
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label[i], num_chunk_types, num_tag_types));
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tag = label[i] % num_tag_types;
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type = label[i] / num_tag_types;
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if (in_chunk && ChunkEnd(prev_tag, prev_type, tag, type, other_chunk_type,
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tag_begin, tag_inside, tag_end, tag_single)) {
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Segment segment{
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chunk_start, // begin
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i - 1, // end
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prev_type,
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};
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segments->push_back(segment);
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in_chunk = false;
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}
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if (ChunkBegin(prev_tag, prev_type, tag, type, other_chunk_type,
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tag_begin, tag_inside, tag_end, tag_single)) {
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chunk_start = i;
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in_chunk = true;
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}
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}
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if (in_chunk) {
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Segment segment{
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chunk_start, // begin
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length - 1, // end
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type,
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};
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segments->push_back(segment);
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}
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}
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bool ChunkEnd(int prev_tag, int prev_type, int tag, int type,
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int other_chunk_type, int tag_begin, int tag_inside,
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int tag_end, int tag_single) const {
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if (prev_type == other_chunk_type) return false;
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if (type == other_chunk_type) return true;
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if (type != prev_type) return true;
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if (prev_tag == tag_begin) return tag == tag_begin || tag == tag_single;
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if (prev_tag == tag_inside) return tag == tag_begin || tag == tag_single;
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if (prev_tag == tag_end) return true;
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if (prev_tag == tag_single) return true;
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return false;
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}
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bool ChunkBegin(int prev_tag, int prev_type, int tag, int type,
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int other_chunk_type, int tag_begin, int tag_inside,
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int tag_end, int tag_single) const {
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if (prev_type == other_chunk_type) return type != other_chunk_type;
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if (type == other_chunk_type) return false;
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if (type != prev_type) return true;
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if (tag == tag_begin) return true;
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if (tag == tag_inside) return prev_tag == tag_end || prev_tag == tag_single;
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if (tag == tag_end) return prev_tag == tag_end || prev_tag == tag_single;
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if (tag == tag_single) return true;
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return false;
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}
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void Compute(const framework::ExecutionContext& context) const override {
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// initialize to parse configurations
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int num_chunk_types, num_tag_types;
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int other_chunk_type;
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int tag_begin, tag_inside, tag_end, tag_single;
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std::vector<Segment> label_segments;
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std::vector<Segment> output_segments;
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std::set<int> excluded_chunk_types;
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if (context.Attr<std::string>("chunk_scheme") == "IOB") {
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num_tag_types = 2;
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tag_begin = 0;
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tag_inside = 1;
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tag_end = -1;
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tag_single = -1;
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} else if (context.Attr<std::string>("chunk_scheme") == "IOE") {
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num_tag_types = 2;
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tag_begin = -1;
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tag_inside = 0;
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tag_end = 1;
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tag_single = -1;
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} else if (context.Attr<std::string>("chunk_scheme") == "IOBES") {
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num_tag_types = 4;
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tag_begin = 0;
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tag_inside = 1;
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tag_end = 2;
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tag_single = 3;
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} else if (context.Attr<std::string>("chunk_scheme") == "plain") {
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num_tag_types = 1;
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tag_begin = -1;
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tag_inside = -1;
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tag_end = -1;
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tag_single = -1;
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} else {
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PADDLE_THROW(platform::errors::InvalidArgument("Unknown chunk scheme."));
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}
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other_chunk_type = num_chunk_types = context.Attr<int>("num_chunk_types");
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excluded_chunk_types.insert(
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context.Attr<std::vector<int>>("excluded_chunk_types").begin(),
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context.Attr<std::vector<int>>("excluded_chunk_types").end());
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auto* inference = context.Input<LoDTensor>("Inference");
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auto place = inference->place();
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auto* label = context.Input<LoDTensor>("Label");
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auto* precision = context.Output<Tensor>("Precision");
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auto* recall = context.Output<Tensor>("Recall");
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auto* f1 = context.Output<Tensor>("F1-Score");
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auto* num_infer_chunks = context.Output<Tensor>("NumInferChunks");
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auto* num_label_chunks = context.Output<Tensor>("NumLabelChunks");
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auto* num_correct_chunks = context.Output<Tensor>("NumCorrectChunks");
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const int64_t* inference_data = inference->data<int64_t>();
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const int64_t* label_data = label->data<int64_t>();
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T* precision_data = precision->mutable_data<T>(place);
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T* racall_data = recall->mutable_data<T>(place);
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T* f1_data = f1->mutable_data<T>(place);
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int64_t* num_infer_chunks_data =
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num_infer_chunks->mutable_data<int64_t>(place);
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int64_t* num_label_chunks_data =
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num_label_chunks->mutable_data<int64_t>(place);
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int64_t* num_correct_chunks_data =
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num_correct_chunks->mutable_data<int64_t>(place);
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*num_infer_chunks_data = 0;
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*num_label_chunks_data = 0;
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*num_correct_chunks_data = 0;
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auto lod = label->lod();
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bool use_padding = lod.empty();
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int num_sequences = 0;
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if (use_padding) {
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auto dim1 = inference->dims()[1];
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auto* seq_length_t = context.Input<Tensor>("SeqLength");
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auto* seq_length_data = seq_length_t->data<int64_t>();
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num_sequences = seq_length_t->dims()[0];
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for (int i = 0; i < num_sequences; ++i) {
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int seq_length = seq_length_data[i];
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EvalOneSeq(inference_data + i * dim1, label_data + i * dim1, seq_length,
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&output_segments, &label_segments, num_infer_chunks_data,
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num_label_chunks_data, num_correct_chunks_data,
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num_chunk_types, num_tag_types, other_chunk_type, tag_begin,
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tag_inside, tag_end, tag_single, excluded_chunk_types);
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}
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} else {
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PADDLE_ENFORCE_EQ(
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lod.size(), 1UL,
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platform::errors::InvalidArgument(
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"Only support one level LoD sequence now, but received %d.",
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lod.size()));
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PADDLE_ENFORCE_EQ(
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lod, inference->lod(),
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platform::errors::InvalidArgument(
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"Input(Inference) and Input(Label) of Op(chunk_eval) should have "
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"same LoD information."));
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num_sequences = lod[0].size() - 1;
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for (int i = 0; i < num_sequences; ++i) {
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int seq_length = lod[0][i + 1] - lod[0][i];
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EvalOneSeq(inference_data + lod[0][i], label_data + lod[0][i],
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seq_length, &output_segments, &label_segments,
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num_infer_chunks_data, num_label_chunks_data,
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num_correct_chunks_data, num_chunk_types, num_tag_types,
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other_chunk_type, tag_begin, tag_inside, tag_end, tag_single,
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excluded_chunk_types);
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}
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}
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*precision_data = !(*num_infer_chunks_data)
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? 0
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: static_cast<T>(*num_correct_chunks_data) /
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(*num_infer_chunks_data);
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*racall_data = !(*num_label_chunks_data)
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? 0
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: static_cast<T>(*num_correct_chunks_data) /
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(*num_label_chunks_data);
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*f1_data = !(*num_correct_chunks_data)
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? 0
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: 2 * (*precision_data) * (*racall_data) /
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((*precision_data) + (*racall_data));
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}
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void EvalOneSeq(const int64_t* output, const int64_t* label, int length,
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std::vector<Segment>* output_segments,
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std::vector<Segment>* label_segments,
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int64_t* num_output_segments, int64_t* num_label_segments,
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int64_t* num_correct, int num_chunk_types, int num_tag_types,
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int other_chunk_type, int tag_begin, int tag_inside,
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int tag_end, int tag_single,
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const std::set<int>& excluded_chunk_types) const {
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GetSegments(output, length, output_segments, num_chunk_types, num_tag_types,
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other_chunk_type, tag_begin, tag_inside, tag_end, tag_single);
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GetSegments(label, length, label_segments, num_chunk_types, num_tag_types,
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other_chunk_type, tag_begin, tag_inside, tag_end, tag_single);
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size_t i = 0, j = 0;
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while (i < output_segments->size() && j < label_segments->size()) {
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if (output_segments->at(i) == label_segments->at(j) &&
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excluded_chunk_types.count(output_segments->at(i).type) != 1) {
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++(*num_correct);
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}
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if (output_segments->at(i).end < label_segments->at(j).end) {
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++i;
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} else if (output_segments->at(i).end > label_segments->at(j).end) {
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++j;
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} else {
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++i;
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++j;
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}
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}
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for (auto& segment : (*label_segments)) {
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if (excluded_chunk_types.count(segment.type) != 1) {
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++(*num_label_segments);
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}
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}
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for (auto& segment : (*output_segments)) {
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if (excluded_chunk_types.count(segment.type) != 1) {
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++(*num_output_segments);
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}
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}
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}
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};
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} // namespace operators
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} // namespace paddle
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