Enhance inplace prediction. (#6653)

* Accept array interface for csr and array.
* Accept an optional proxy dmatrix for metainfo.

This constructs an explicit `_ProxyDMatrix` type in Python.

* Remove unused doc.
* Add strict output.

include/xgboost/gbm.h

@@ -1,5 +1,5 @@
 /*!
- * Copyright 2014-2020 by Contributors
+ * Copyright 2014-2021 by Contributors
  * \file gbm.h
  * \brief Interface of gradient booster,
  *  that learns through gradient statistics.
@@ -118,7 +118,7 @@ class GradientBooster : public Model, public Configurable {
    * \param           layer_begin (Optional) Begining of boosted tree layer used for prediction.
    * \param           layer_end   (Optional) End of booster layer. 0 means do not limit trees.
    */
-  virtual void InplacePredict(dmlc::any const &, float,
+  virtual void InplacePredict(dmlc::any const &, std::shared_ptr<DMatrix>, float,
                               PredictionCacheEntry*,
                               uint32_t,
                               uint32_t) const {

include/xgboost/json.h

@@ -308,6 +308,7 @@ struct StringView {
  public:
   StringView() = default;
   StringView(CharT const* str, size_t size) : str_{str}, size_{size} {}
+  explicit StringView(std::string const& str): str_{str.c_str()}, size_{str.size()} {}
   explicit StringView(CharT const* str) : str_{str}, size_{Traits::length(str)} {}
 
   CharT const& operator[](size_t p) const { return str_[p]; }

include/xgboost/learner.h

@@ -1,5 +1,5 @@
 /*!
- * Copyright 2015-2020 by Contributors
+ * Copyright 2015-2021 by Contributors
  * \file learner.h
  * \brief Learner interface that integrates objective, gbm and evaluation together.
  *  This is the user facing XGBoost training module.
@@ -30,6 +30,15 @@ class ObjFunction;
 class DMatrix;
 class Json;
 
+enum class PredictionType : std::uint8_t {  // NOLINT
+  kValue = 0,
+  kMargin = 1,
+  kContribution = 2,
+  kApproxContribution = 3,
+  kInteraction = 4,
+  kLeaf = 5
+};
+
 /*! \brief entry to to easily hold returning information */
 struct XGBAPIThreadLocalEntry {
   /*! \brief result holder for returning string */
@@ -42,7 +51,10 @@ struct XGBAPIThreadLocalEntry {
   std::vector<bst_float> ret_vec_float;
   /*! \brief temp variable of gradient pairs. */
   std::vector<GradientPair> tmp_gpair;
+  /*! \brief Temp variable for returing prediction result. */
   PredictionCacheEntry prediction_entry;
+  /*! \brief Temp variable for returing prediction shape. */
+  std::vector<bst_ulong> prediction_shape;
 };
 
 /*!
@@ -123,13 +135,17 @@ class Learner : public Model, public Configurable, public dmlc::Serializable {
    * \brief Inplace prediction.
    *
    * \param          x           A type erased data adapter.
+   * \param          p_m         An optional Proxy DMatrix object storing meta info like
+   *                             base margin.  Can be nullptr.
    * \param          type        Prediction type.
    * \param          missing     Missing value in the data.
    * \param [in,out] out_preds   Pointer to output prediction vector.
-   * \param          layer_begin (Optional) Begining of boosted tree layer used for prediction.
-   * \param          layer_end   (Optional) End of booster layer. 0 means do not limit trees.
+   * \param          layer_begin Begining of boosted tree layer used for prediction.
+   * \param          layer_end   End of booster layer. 0 means do not limit trees.
    */
-  virtual void InplacePredict(dmlc::any const& x, std::string const& type,
+  virtual void InplacePredict(dmlc::any const &x,
+                              std::shared_ptr<DMatrix> p_m,
+                              PredictionType type,
                               float missing,
                               HostDeviceVector<bst_float> **out_preds,
                               uint32_t layer_begin, uint32_t layer_end) = 0;
@@ -138,6 +154,7 @@ class Learner : public Model, public Configurable, public dmlc::Serializable {
    * \brief Get number of boosted rounds from gradient booster.
    */
   virtual int32_t BoostedRounds() const = 0;
+  virtual uint32_t Groups() const = 0;
 
   void LoadModel(Json const& in) override = 0;
   void SaveModel(Json* out) const override = 0;

include/xgboost/predictor.h

@@ -1,5 +1,5 @@
 /*!
- * Copyright 2017-2020 by Contributors
+ * Copyright 2017-2021 by Contributors
  * \file predictor.h
  * \brief Interface of predictor,
  *  performs predictions for a gradient booster.
@@ -142,10 +142,14 @@ class Predictor {
    * \param [in,out]  out_preds              The output preds.
    * \param           tree_begin (Optional) Begining of boosted trees used for prediction.
    * \param           tree_end   (Optional) End of booster trees. 0 means do not limit trees.
+   *
+   * \return True if the data can be handled by current predictor, false otherwise.
    */
-  virtual void InplacePredict(dmlc::any const &x, const gbm::GBTreeModel &model,
-                              float missing, PredictionCacheEntry *out_preds,
-                              uint32_t tree_begin = 0, uint32_t tree_end = 0) const = 0;
+  virtual bool InplacePredict(dmlc::any const &x, std::shared_ptr<DMatrix> p_m,
+                              const gbm::GBTreeModel &model, float missing,
+                              PredictionCacheEntry *out_preds,
+                              uint32_t tree_begin = 0,
+                              uint32_t tree_end = 0) const = 0;
   /**
    * \brief online prediction function, predict score for one instance at a time
    * NOTE: use the batch prediction interface if possible, batch prediction is