tree-based-model #31696
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| // Copyright (c) 2021 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. | ||
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| #include "paddle/fluid/framework/fleet/index_sampler.h" | ||
| #include "paddle/fluid/operators/math/sampler.h" | ||
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| namespace paddle { | ||
| namespace framework { | ||
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| using Sampler = paddle::operators::math::Sampler; | ||
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| std::vector<std::vector<uint64_t>> LayerWiseSampler::sample( | ||
| const std::vector<std::vector<uint64_t>>& user_inputs, | ||
| const std::vector<uint64_t>& target_ids, bool with_hierarchy) { | ||
| auto input_num = target_ids.size(); | ||
| auto user_feature_num = user_inputs[0].size(); | ||
| std::vector<std::vector<uint64_t>> outputs( | ||
| input_num * layer_counts_sum_, | ||
| std::vector<uint64_t>(user_feature_num + 2)); | ||
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| auto max_layer = tree_->height(); | ||
| std::vector<Sampler*> sampler_vec(max_layer - start_sample_layer_); | ||
| std::vector<std::vector<uint64_t>> layer_ids(max_layer - start_sample_layer_); | ||
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| auto layer_index = max_layer - 1; | ||
| size_t idx = 0; | ||
| while (layer_index >= start_sample_layer_) { | ||
| layer_ids[idx] = tree_->get_nodes_given_level(layer_index); | ||
| sampler_vec[idx] = new paddle::operators::math::UniformSampler( | ||
| layer_ids[idx].size() - 1, seed_); | ||
| layer_index--; | ||
| idx++; | ||
| } | ||
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| auto ancestors = tree_->get_parent_path(target_ids, start_sample_layer_); | ||
| idx = 0; | ||
| for (size_t i = 0; i < input_num; i++) { | ||
| for (size_t j = 0; j < ancestors[i].size(); j++) { | ||
| // user | ||
| if (j > 0 && with_hierarchy) { | ||
| auto hierarchical_user = | ||
| tree_->get_ancestor_given_level(user_inputs[i], max_layer - j - 1); | ||
| for (int idx_offset = 0; idx_offset <= layer_counts_[j]; idx_offset++) { | ||
| for (size_t k = 0; k < user_feature_num; k++) { | ||
| outputs[idx + idx_offset][k] = hierarchical_user[k]; | ||
| } | ||
| } | ||
| } else { | ||
| for (int idx_offset = 0; idx_offset <= layer_counts_[j]; idx_offset++) { | ||
| for (size_t k = 0; k < user_feature_num; k++) { | ||
| outputs[idx + idx_offset][k] = user_inputs[i][k]; | ||
| } | ||
| } | ||
| } | ||
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| // sampler ++ | ||
| outputs[idx][user_feature_num] = ancestors[i][j]; | ||
| outputs[idx][user_feature_num + 1] = 1.0; | ||
| idx += 1; | ||
| for (int idx_offset = 0; idx_offset < layer_counts_[j]; idx_offset++) { | ||
| int sample_res = 0; | ||
| do { | ||
| sample_res = sampler_vec[j]->Sample(); | ||
| } while (layer_ids[j][sample_res] == ancestors[i][j]); | ||
| outputs[idx + idx_offset][user_feature_num] = layer_ids[j][sample_res]; | ||
| outputs[idx + idx_offset][user_feature_num + 1] = 0; | ||
| } | ||
| idx += layer_counts_[j]; | ||
| } | ||
| } | ||
| return outputs; | ||
| } | ||
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| } // end namespace framework | ||
| } // end namespace paddle | ||
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,100 @@ | ||
| // Copyright (c) 2021 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. | ||
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| #pragma once | ||
| #include <vector> | ||
| #include "paddle/fluid/framework/fleet/index_wrapper.h" | ||
| #include "paddle/fluid/framework/program_desc.h" | ||
| #include "paddle/fluid/platform/enforce.h" | ||
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| namespace paddle { | ||
| namespace framework { | ||
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| class IndexSampler { | ||
| public: | ||
| virtual ~IndexSampler() {} | ||
| IndexSampler() {} | ||
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| template <typename T> | ||
| static std::shared_ptr<IndexSampler> Init(const std::string& name) { | ||
| std::shared_ptr<IndexSampler> instance = nullptr; | ||
| instance.reset(new T(name)); | ||
| return instance; | ||
| } | ||
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| virtual void init_layerwise_conf(const std::vector<int>& layer_sample_counts, | ||
| int start_sample_layer = 1, int seed = 0) {} | ||
| virtual void init_beamsearch_conf(const int64_t k) {} | ||
| virtual std::vector<std::vector<uint64_t>> sample( | ||
| const std::vector<std::vector<uint64_t>>& user_inputs, | ||
| const std::vector<uint64_t>& input_targets, | ||
| bool with_hierarchy = false) = 0; | ||
| }; | ||
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| class LayerWiseSampler : public IndexSampler { | ||
| public: | ||
| virtual ~LayerWiseSampler() {} | ||
| explicit LayerWiseSampler(const std::string& name) { | ||
| tree_ = IndexWrapper::GetInstance()->GetTreeIndex(name); | ||
|
There was a problem hiding this comment. singleton is necessary? |
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| } | ||
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| void init_layerwise_conf(const std::vector<int>& layer_sample_counts, | ||
| int start_sample_layer, int seed) override { | ||
| seed_ = seed; | ||
| start_sample_layer_ = start_sample_layer; | ||
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| PADDLE_ENFORCE_GT( | ||
| start_sample_layer_, 0, | ||
| paddle::platform::errors::InvalidArgument( | ||
| "start sampler layer = [%d], it should greater than 0.", | ||
| start_sample_layer_)); | ||
| PADDLE_ENFORCE_LT(start_sample_layer_, tree_->height(), | ||
| paddle::platform::errors::InvalidArgument( | ||
| "start sampler layer = [%d], it should less than " | ||
| "max_layer, which is [%d].", | ||
| start_sample_layer_, tree_->height())); | ||
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| size_t i = 0; | ||
| layer_counts_sum_ = 0; | ||
| layer_counts_.clear(); | ||
| int cur_layer = start_sample_layer_; | ||
| while (cur_layer < tree_->height()) { | ||
| int layer_sample_num = 1; | ||
| if (i < layer_sample_counts.size()) { | ||
| layer_sample_num = layer_sample_counts[i]; | ||
| } | ||
| layer_counts_sum_ += layer_sample_num + 1; | ||
| layer_counts_.push_back(layer_sample_num); | ||
| VLOG(1) << "[INFO] level " << cur_layer | ||
| << " sample_layer_counts.push_back: " << layer_sample_num; | ||
| cur_layer += 1; | ||
| i += 1; | ||
| } | ||
| reverse(layer_counts_.begin(), layer_counts_.end()); | ||
| VLOG(1) << "sample counts sum: " << layer_counts_sum_; | ||
| } | ||
| std::vector<std::vector<uint64_t>> sample( | ||
| const std::vector<std::vector<uint64_t>>& user_inputs, | ||
| const std::vector<uint64_t>& target_ids, bool with_hierarchy) override; | ||
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| private: | ||
| std::vector<int> layer_counts_; | ||
| int64_t layer_counts_sum_{0}; | ||
| std::shared_ptr<TreeIndex> tree_{nullptr}; | ||
| int seed_{0}; | ||
| int start_sample_layer_{1}; | ||
| }; | ||
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| } // end namespace framework | ||
| } // end namespace paddle | ||
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namespace upgrade.