Clean up some comments (+5 squashed commits)

Squashed commits:
[99b8f1f] Remove pom change
[7b80fef] Remove changes from cpu_predictor, fix rebase miss
[a531053] Cleaning up XGBoosterInplacePredict

Further de-newification

More clean-up
[de6e109] pom change git didn't pick up (+5 squashed commits)
Squashed commits:
[6182244] One missed pom
[ab5bc5e] Update all the poms, even the unused ones
[a96c3b9] More clean-up
[aea9cd3] Further de-newification
[1539100] Cleaning up XGBoosterInplacePredict
[a81361d] increment our version (+15 squashed commits)
Squashed commits:
[c4d6d52] missed param
[b343f89] Remove redundant line
[5609102] Remove need to pass DMatrix
[e31c53d] another missed logging message
[f6a2508] comment out some logging
[148e29e] undo static cast
[6372805] More logging
[a173763] change how proxy is cast in cpu predictor
[5a08ff8] proxy to stuff
[823c92f] Dense adapter changes
[9a3214b] change some variables and things
[d9dd5c4] uncomment stuff, more logging
[7968bca] Set dense data
[9e79c2e] Try some stuff with DMatrix
[2b8cca6] Print result of p_m.get()

Author: yoquinjo

include/xgboost/c_api.h

@@ -1017,6 +1017,7 @@ XGB_DLL int XGBoosterInplacePredict(BoosterHandle handle,
                                     const float *data,
                                     size_t num_rows,
                                     size_t num_features,
+                                    DMatrixHandle d_matrix_handle,
                                     float missing,
                                     int option_mask,
                                     int ntree_limit,

jvm-packages/xgboost4j/pom.xml

@@ -69,7 +69,7 @@
                           <goal>exec</goal>
                       </goals>
                       <configuration>
-                          <executable>python3</executable>
+                          <executable>python</executable>
                           <arguments>
                             <argument>create_jni.py</argument>
                             <argument>--log-capi-invocation</argument>

jvm-packages/xgboost4j/src/main/java/ml/dmlc/xgboost4j/java/Booster.java

@@ -315,6 +315,7 @@ private synchronized float[][] predict(DMatrix data,
     }
     return predicts;
   }
+
   /**
    * Perform thread-safe prediction. Calls
    * <code>inplace_predict(data, num_rows, num_features, Float.NaN, false, 0, false, false)</code>.
@@ -332,7 +333,8 @@ private synchronized float[][] predict(DMatrix data,
   public float[][] inplace_predict(float[] data,
                                    int num_rows,
                                    int num_features) throws XGBoostError {
-    return this.inplace_predict(data, num_rows, num_features, Float.NaN, false, 0, false, false);
+    return this.inplace_predict(data, num_rows, num_features,
+                Float.NaN, false, 0, false, false);
   }
 
   /**
@@ -354,7 +356,8 @@ public float[][] inplace_predict(float[] data,
                                    int num_rows,
                                    int num_features,
                                    float missing) throws XGBoostError {
-    return this.inplace_predict(data, num_rows, num_features, missing, false, 0, false, false);
+    return this.inplace_predict(data, num_rows, num_features,
+                missing, false, 0, false, false);
   }
 
   /**
@@ -380,8 +383,8 @@ public float[][] inplace_predict(float[] data,
                                    int num_features,
                                    float missing,
                                    boolean outputMargin) throws XGBoostError {
-    return this.inplace_predict(data, num_rows, num_features, missing, outputMargin,
-                       0, false, false);
+    return this.inplace_predict(data, num_rows, num_features, missing,
+                       outputMargin, 0, false, false);
   }
 
   /**
@@ -408,8 +411,8 @@ public float[][] inplace_predict(float[] data,
                                    float missing,
                                    boolean outputMargin,
                                    int treeLimit) throws XGBoostError {
-    return this.inplace_predict(data, num_rows, num_features, missing, outputMargin,
-                                treeLimit, false, false);
+    return this.inplace_predict(data, num_rows, num_features, missing,
+                                outputMargin, treeLimit, false, false);
   }
 
   /**
@@ -418,6 +421,7 @@ public float[][] inplace_predict(float[] data,
    * @param data           Flattened input matrix of features for prediction
    * @param num_rows       The number of preditions to make (count of input matrix rows)
    * @param num_features   The number of features in the model (count of input matrix columns)
+   * @param d_matrix_h     The handle for a dmatrix
    * @param missing        Value indicating missing element in the <code>data</code> input matrix
    * @param outputMargin   Whether to only predict margin value instead of transformed prediction
    * @param treeLimit      limit number of trees, 0 means all trees.
@@ -444,10 +448,11 @@ public float[][] inplace_predict(float[] data,
     if (predContribs) {
       optionMask = 4;
     }
-
+    DMatrix d_mat = new DMatrix(data, num_rows, num_features, missing);
     float[][] rawPredicts = new float[1][];
     XGBoostJNI.checkCall(XGBoostJNI.XGBoosterInplacePredict(handle, data, num_rows, num_features,
-        missing, optionMask, treeLimit, rawPredicts));  // pass missing and treelimit here?
+        d_mat.getHandle(), missing,
+        optionMask, treeLimit, rawPredicts));  // pass missing and treelimit here?
 
     // System.out.println("Booster.inplace_predict rawPredicts[0].length = " +
     //    rawPredicts[0].length);

jvm-packages/xgboost4j/src/main/java/ml/dmlc/xgboost4j/java/XGBoostJNI.java

@@ -119,7 +119,7 @@ public final static native int XGBoosterEvalOneIter(long handle, int iter, long[
   public final static native int XGBoosterPredict(long handle, long dmat, int option_mask,
                                                   int ntree_limit, float[][] predicts);
 
-  public final static native int XGBoosterInplacePredict(long handle, float[] data, int num_rows, int num_features,
+  public final static native int XGBoosterInplacePredict(long handle, float[] data, int num_rows, int num_features, long d_matrix_handle,
                                                          float missing, int option_mask, int ntree_limit,
                                                          float[][] predicts);
 

jvm-packages/xgboost4j/src/native/xgboost4j.cpp

@@ -667,18 +667,18 @@ JNIEXPORT jint JNICALL Java_ml_dmlc_xgboost4j_java_XGBoostJNI_XGBoosterPredict
  * Signature: (J[FIII[[F)I
  */
 JNIEXPORT jint JNICALL Java_ml_dmlc_xgboost4j_java_XGBoostJNI_XGBoosterInplacePredict
-  (JNIEnv *jenv, jclass jcls, jlong jhandle, jfloatArray jdata, jint num_rows, jint num_features,
+  (JNIEnv *jenv, jclass jcls, jlong jhandle, jfloatArray jdata, jint num_rows, jint num_features, jlong d_matrix_handle,
                                              jfloat missing, jint option_mask, jint treeLimit, jobjectArray jout) {
   BoosterHandle handle = (BoosterHandle) jhandle;
+  DMatrixHandle dmat = (DMatrixHandle) d_matrix_handle;
   jfloat* data = jenv->GetFloatArrayElements(jdata, 0);
   const bst_ulong *len;
   float *result;
-  int ret = XGBoosterInplacePredict(handle, data, num_rows, num_features, missing, option_mask, treeLimit,
+  int ret = XGBoosterInplacePredict(handle, data, num_rows, num_features, dmat, missing, option_mask, treeLimit,
             &len, (const float **) &result);
   JVM_CHECK_CALL(ret);
   jenv->ReleaseFloatArrayElements(jdata, data, 0);
   if (*len) {
-//    printf("JNI XGBoosterInplacePredict len = %u\n", *len);
     jsize jlen = (jsize) *len;
     jfloatArray jarray = jenv->NewFloatArray(jlen);
     jenv->SetFloatArrayRegion(jarray, 0, jlen, (jfloat *) result);

jvm-packages/xgboost4j/src/native/xgboost4j.h

@@ -157,13 +157,6 @@
 pred = Pred("prediction", "rawPrediction", "probability", "predContrib")
 
 
-# TODO: supply hint message for all other unsupported params.
-_unsupported_params_hint_message = {
-    "enable_categorical": "`xgboost.spark` estimators do not have 'enable_categorical' param, "
-    "but you can set `feature_types` param and mark categorical features with 'c' string."
-}
-
-
 class _SparkXGBParams(
     HasFeaturesCol,
     HasLabelCol,

python-package/xgboost/spark/core.py

@@ -1068,6 +1068,7 @@ XGB_DLL int XGBoosterInplacePredict(BoosterHandle handle,
                                     const float *data,
                                     size_t num_rows,
                                     size_t num_features,
+                                    DMatrixHandle dMatrixHandle,
                                     float missing,
                                     int option_mask,
                                     int ntree_limit,
@@ -1076,16 +1077,13 @@ XGB_DLL int XGBoosterInplacePredict(BoosterHandle handle,
   API_BEGIN();
   CHECK_HANDLE();
   xgboost::bst_ulong out_dim;
-  std::shared_ptr<xgboost::data::DenseAdapter> x{new xgboost::data::DenseAdapter(data, num_rows, num_features)};
-  std::shared_ptr<DMatrix> p_m{nullptr};
-  p_m.reset(new data::DMatrixProxy);
-  auto proxy = dynamic_cast<data::DMatrixProxy *>(p_m.get());
-  CHECK(proxy) << "Invalid input type for inplace predict.";
+
   auto *learner = static_cast<xgboost::Learner *>(handle);
   auto iteration_end = GetIterationFromTreeLimit(ntree_limit, learner);
-  InplacePredictImplCore(p_m, learner, (xgboost::PredictionType)0, missing, num_rows, num_features,
+  auto proxy = std::make_shared<data::DMatrixProxy>();
+  proxy->SetDenseData(data, num_rows, num_features);
+  InplacePredictImplCore(proxy, learner, (xgboost::PredictionType)0, missing, num_rows, num_features,
                          0, iteration_end, true, len, &out_dim, out_result);
-//  printf("XGBoosterInplacePredict len = %u, dim = %u\n", **len, out_dim);
   API_END();
 }
 

src/c_api/c_api.cc

@@ -15,6 +15,15 @@ void DMatrixProxy::SetArrayData(char const *c_interface) {
   this->ctx_.gpu_id = Context::kCpuId;
 }
 
+void DMatrixProxy::SetDenseData(const float *data, size_t num_rows,
+                                size_t num_features) {
+  std::shared_ptr<xgboost::data::DenseAdapter> adapter{new xgboost::data::DenseAdapter(data, num_rows, num_features)};
+  this->batch_ = adapter;
+  this->Info().num_col_ = adapter->NumColumns();
+  this->Info().num_row_ = adapter->NumRows();
+  this->ctx_.gpu_id = Context::kCpuId;
+}
+
 void DMatrixProxy::SetCSRData(char const *c_indptr, char const *c_indices,
                               char const *c_values, bst_feature_t n_features, bool on_host) {
   CHECK(on_host) << "Not implemented on device.";

src/data/proxy_dmatrix.cc

@@ -63,8 +63,11 @@ class DMatrixProxy : public DMatrix {
   }
 
   void SetArrayData(char const* c_interface);
-  void SetCSRData(char const* c_indptr, char const* c_indices, char const* c_values,
-                  bst_feature_t n_features, bool on_host);
+  void SetDenseData(const float *data,size_t num_rows,
+                    size_t num_features);
+  void SetCSRData(char const *c_indptr, char const *c_indices,
+                  char const *c_values, bst_feature_t n_features,
+                  bool on_host);
 
   MetaInfo& Info() override { return info_; }
   MetaInfo const& Info() const override { return info_; }