Validate weights are positive values. (#6115)

R-package/tests/testthat/test_dmatrix.R

@@ -64,8 +64,8 @@ test_that("xgb.DMatrix: getinfo & setinfo", {
   expect_true(setinfo(dtest, 'group', c(50, 50)))
   expect_error(setinfo(dtest, 'group', test_label))
 
-  # providing character values will give a warning
+  # providing character values will give an error
-  expect_warning(setinfo(dtest, 'weight', rep('a', nrow(test_data))))
+  expect_error(setinfo(dtest, 'weight', rep('a', nrow(test_data))))
 
   # any other label should error
   expect_error(setinfo(dtest, 'asdf', test_label))

demo/guide-python/data_iterator.py

@@ -39,7 +39,7 @@ class IterForDMatrixDemo(xgboost.core.DataIter):
         rng = cupy.random.RandomState(1994)
         self._data = [rng.randn(self.rows, self.cols)] * BATCHES
         self._labels = [rng.randn(self.rows)] * BATCHES
-        self._weights = [rng.randn(self.rows)] * BATCHES
+        self._weights = [rng.uniform(size=self.rows)] * BATCHES
 
         self.it = 0             # set iterator to 0
         super().__init__()

src/data/data.cc

@@ -359,6 +359,9 @@ void MetaInfo::SetInfo(const char* key, const void* dptr, DataType dtype, size_t
     weights.resize(num);
     DISPATCH_CONST_PTR(dtype, dptr, cast_dptr,
                        std::copy(cast_dptr, cast_dptr + num, weights.begin()));
+    auto valid = std::all_of(weights.cbegin(), weights.cend(),
+                             [](float w) { return w >= 0; });
+    CHECK(valid) << "Weights must be positive values.";
   } else if (!std::strcmp(key, "base_margin")) {
     auto& base_margin = base_margin_.HostVector();
     base_margin.resize(num);

src/data/data.cu

@@ -86,6 +86,10 @@ void MetaInfo::SetInfo(const char * c_key, std::string const& interface_str) {
     CopyInfoImpl(array_interface, &labels_);
   } else if (key == "weight") {
     CopyInfoImpl(array_interface, &weights_);
+    auto ptr = weights_.ConstDevicePointer();
+    auto valid =
+        thrust::all_of(thrust::device, ptr, ptr + weights_.Size(), AllOfOp{});
+    CHECK(valid) << "Weights must be positive values.";
   } else if (key == "base_margin") {
     CopyInfoImpl(array_interface, &base_margin_);
   } else if (key == "group") {
@@ -100,10 +104,9 @@ void MetaInfo::SetInfo(const char * c_key, std::string const& interface_str) {
   } else if (key == "feature_weights") {
     CopyInfoImpl(array_interface, &feature_weigths);
     auto d_feature_weights = feature_weigths.ConstDeviceSpan();
-    auto valid =
+    auto valid = thrust::all_of(
-        thrust::all_of(thrust::device, d_feature_weights.data(),
+        thrust::device, d_feature_weights.data(),
-                       d_feature_weights.data() + d_feature_weights.size(),
+        d_feature_weights.data() + d_feature_weights.size(), AllOfOp{});
-                       AllOfOp{});
     CHECK(valid) << "Feature weight must be greater than 0.";
     return;
   } else {

tests/python/test_with_modin.py

@@ -135,7 +135,7 @@ class TestModin(unittest.TestCase):
 
         X = np.random.randn(kRows, kCols)
         y = np.random.randn(kRows)
-        w = np.random.randn(kRows).astype(np.float32)
+        w = np.random.uniform(size=kRows).astype(np.float32)
         w_pd = md.DataFrame(w)
         data = xgb.DMatrix(X, y, w_pd)
 

tests/python/test_with_pandas.py

@@ -151,7 +151,7 @@ class TestPandas(unittest.TestCase):
 
         X = np.random.randn(kRows, kCols)
         y = np.random.randn(kRows)
-        w = np.random.randn(kRows).astype(np.float32)
+        w = np.random.uniform(size=kRows).astype(np.float32)
         w_pd = pd.DataFrame(w)
         data = xgb.DMatrix(X, y, w_pd)