xgboost

predictor.h
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1
7 #pragma once
8 #include <xgboost/base.h>
9 #include <xgboost/data.h>
10 #include <xgboost/generic_parameters.h>
11 #include <xgboost/host_device_vector.h>
12
13 #include <functional>
14 #include <memory>
15 #include <string>
16 #include <unordered_map>
17 #include <utility>
18 #include <vector>
19 #include <mutex>
20
21 // Forward declarations
22 namespace xgboost {
23 class TreeUpdater;
24 namespace gbm {
25 struct GBTreeModel;
26 } // namespace gbm
27 }
28
29 namespace xgboost {
35 struct PredictionCacheEntry {
36 // A storage for caching prediction values
37 HostDeviceVector<bst_float> predictions;
38 // The version of current cache, corresponding number of layers of trees
39 uint32_t version { 0 };
40 // A weak pointer for checking whether the DMatrix object has expired.
41 std::weak_ptr< DMatrix > ref;
42
43 PredictionCacheEntry() = default;
44 /* \brief Update the cache entry by number of versions.
45 *
46 * \param v Added versions.
47 */
48 void Update(uint32_t v) {
49 version += v;
50 }
51 };
52
53 /* \brief A container for managed prediction caches.
54 */
55 class PredictionContainer {
56 std::unordered_map<DMatrix *, PredictionCacheEntry> container_;
57 void ClearExpiredEntries();
58 std::mutex cache_lock_;
59
60 public:
61 PredictionContainer() = default;
62 /* \brief Add a new DMatrix to the cache, at the same time this function will clear out
63 * all expired caches by checking the `std::weak_ptr`. Caching an existing
64 * DMatrix won't renew it.
65 *
66 * Passing in a `shared_ptr` is critical here. First to create a `weak_ptr` inside the
67 * entry this shared pointer is necessary. More importantly, the life time of this
68 * cache is tied to the shared pointer.
69 *
70 * Another way to make a safe cache is create a proxy to this entry, with anther shared
71 * pointer defined inside, and pass this proxy around instead of the real entry. But
72 * seems to be too messy. In XGBoost, functions like `UpdateOneIter` will have
73 * (memory) safe access to the DMatrix as long as it's passed in as a `shared_ptr`.
74 *
75 * \param m shared pointer to the DMatrix that needs to be cached.
76 * \param device Which device should the cache be allocated on. Pass
77 * GenericParameter::kCpuId for CPU or positive integer for GPU id.
78 *
79 * \return the cache entry for passed in DMatrix, either an existing cache or newly
80 * created.
81 */
82 PredictionCacheEntry& Cache(std::shared_ptr<DMatrix> m, int32_t device);
83 /* \brief Get a prediction cache entry. This entry must be already allocated by `Cache`
84 * method. Otherwise a dmlc::Error is thrown.
85 *
86 * \param m pointer to the DMatrix.
87 * \return The prediction cache for passed in DMatrix.
88 */
89 PredictionCacheEntry& Entry(DMatrix* m);
90 /* \brief Get a const reference to the underlying hash map. Clear expired caches before
91 * returning.
92 */
93 decltype(container_) const& Container();
94 };
95
104 class Predictor {
105 protected:
106 /*
107 * \brief Runtime parameters.
108 */
109 GenericParameter const* generic_param_;
110
111 public:
112 explicit Predictor(GenericParameter const* generic_param) :
113 generic_param_{generic_param} {}
114 virtual ~Predictor() = default;
115
121 virtual void Configure(const std::vector<std::pair<std::string, std::string>>& cfg);
122
134 virtual void PredictBatch(DMatrix* dmat, PredictionCacheEntry* out_preds,
135 const gbm::GBTreeModel& model, int tree_begin,
136 uint32_t const ntree_limit = 0) = 0;
137
147 virtual void InplacePredict(dmlc::any const &x, const gbm::GBTreeModel &model,
148 float missing, PredictionCacheEntry *out_preds,
149 uint32_t tree_begin = 0, uint32_t tree_end = 0) const = 0;
162 virtual void PredictInstance(const SparsePage::Inst& inst,
163 std::vector<bst_float>* out_preds,
164 const gbm::GBTreeModel& model,
165 unsigned ntree_limit = 0) = 0;
166
181 virtual void PredictLeaf(DMatrix* dmat, std::vector<bst_float>* out_preds,
182 const gbm::GBTreeModel& model,
183 unsigned ntree_limit = 0) = 0;
184
204 virtual void PredictContribution(DMatrix* dmat,
205 std::vector<bst_float>* out_contribs,
206 const gbm::GBTreeModel& model,
207 unsigned ntree_limit = 0,
208 std::vector<bst_float>* tree_weights = nullptr,
209 bool approximate = false,
210 int condition = 0,
211 unsigned condition_feature = 0) = 0;
212
213 virtual void PredictInteractionContributions(DMatrix* dmat,
214 std::vector<bst_float>* out_contribs,
215 const gbm::GBTreeModel& model,
216 unsigned ntree_limit = 0,
217 std::vector<bst_float>* tree_weights = nullptr,
218 bool approximate = false) = 0;
219
220
227 static Predictor* Create(
228 std::string const& name, GenericParameter const* generic_param);
229 };
230
234 struct PredictorReg
235 : public dmlc::FunctionRegEntryBase<
236 PredictorReg, std::function<Predictor*(GenericParameter const*)>> {};
237
238 #define XGBOOST_REGISTER_PREDICTOR(UniqueId, Name) \
239 static DMLC_ATTRIBUTE_UNUSED ::xgboost::PredictorReg& \
240 __make_##PredictorReg##_##UniqueId##__ = \
241 ::dmlc::Registry<::xgboost::PredictorReg>::Get()->__REGISTER__(Name)
242 } // namespace xgboost
xgboost::HostDeviceVector< bst_float >
xgboost::Predictor
Performs prediction on individual training instances or batches of instances for GBTree. Prediction functions all take a GBTreeModel and a DMatrix as input and output a vector of predictions. The predictor does not modify any state of the model itself.
Definition: predictor.h:104
data.h
The input data structure of xgboost.
xgboost::GenericParameter
Definition: generic_parameters.h:14
xgboost::DMatrix
Internal data structured used by XGBoost during training. There are two ways to create a customized D...
Definition: data.h:451
xgboost::PredictorReg
Registry entry for predictor.
Definition: predictor.h:234
host_device_vector.h
A device-and-host vector abstraction layer.
xgboost::Predictor::generic_param_
GenericParameter const * generic_param_
Definition: predictor.h:109
xgboost::common::Span
span class implementation, based on ISO++20 span<T>. The interface should be the same.
Definition: span.h:126
xgboost::Predictor::Predictor
Predictor(GenericParameter const *generic_param)
Definition: predictor.h:112
xgboost::PredictionCacheEntry::ref
std::weak_ptr< DMatrix > ref
Definition: predictor.h:41
xgboost::PredictionCacheEntry::predictions
HostDeviceVector< bst_float > predictions
Definition: predictor.h:37
xgboost::PredictionContainer
Definition: predictor.h:55
xgboost
namespace of xgboost
Definition: base.h:102
base.h
defines configuration macros of xgboost.
xgboost::PredictionCacheEntry::Update
void Update(uint32_t v)
Definition: predictor.h:48
xgboost::Entry
Element from a sparse vector.
Definition: data.h:167
generic_parameters.h
xgboost::PredictionCacheEntry
Contains pointer to input matrix and associated cached predictions.
Definition: predictor.h:35