chore: import upstream snapshot with attribution

2026-07-13 12:47:05 +08:00
commit 4f3b7da785
7394 changed files with 2005594 additions and 0 deletions
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+/* ******************************************************************************
+ *
+ *
+ * This program and the accompanying materials are made available under the
+ * terms of the Apache License, Version 2.0 which is available at
+ * https://www.apache.org/licenses/LICENSE-2.0.
+ *
+ *  See the NOTICE file distributed with this work for additional
+ *  information regarding copyright ownership.
+ * 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.
+ *
+ * SPDX-License-Identifier: Apache-2.0
+ ******************************************************************************/
+
+//
+// @author Yurii Shyrma (iuriish@yahoo.com), created on 17.05.2018
+//
+#include <array/NDArrayFactory.h>
+#include <array/ResultSet.h>
+#include <ops/declarable/helpers/percentile.h>
+#if NOT_EXCLUDED(OP_percentile)
+namespace sd {
+namespace ops {
+namespace helpers {
+
+//////////////////////////////////////////////////////////////////////////
+template <typename T>
+static void _percentile(NDArray& input, NDArray& output, std::vector<LongType>& axises, const float q,
+                        const int interpolation) {
+  const int inputRank = input.rankOf();
+
+  if (axises.empty())
+    for (int i = 0; i < inputRank; ++i) axises.push_back(i);
+  else
+    shape::checkDimensions(inputRank, &axises);  // check, sort dimensions and remove duplicates if they are present
+
+  auto listOfSubArrs = input.allTensorsAlongDimension(axises);
+
+  std::vector<sd::LongType> shapeOfSubArr(listOfSubArrs.at(0)->rankOf());
+  for (size_t i = 0; i < shapeOfSubArr.size(); ++i) shapeOfSubArr[i] = listOfSubArrs.at(0)->shapeOf()[i];
+
+  auto flattenedArr = NDArrayFactory::create('c', shapeOfSubArr, input.dataType(), input.getContext());
+  const int len = flattenedArr->lengthOf();
+
+  const float fraction = 1.f - q / 100.;
+  sd::LongType position = 0;
+
+  switch (interpolation) {
+    case 0:  // lower
+      position = static_cast<sd::LongType>(math::sd_ceil<float, T>((len - 1) * fraction));
+      break;
+    case 1:  // higher
+      position = static_cast<sd::LongType>(math::sd_floor<float, T>((len - 1) * fraction));
+      break;
+    case 2:  // nearest
+      position = static_cast<sd::LongType>(math::sd_round<float, T>((len - 1) * fraction));
+      break;
+  }
+  position = len - position - 1;
+
+  // FIXME: our sort impl should be used instead, so this operation might be implemented as generic
+  // FIXME: parallelism !
+  for (int i = 0; i < listOfSubArrs.size(); ++i) {
+    auto buff = reinterpret_cast<T*>(flattenedArr->buffer());
+    flattenedArr->assign(listOfSubArrs.at(i));
+    std::sort(buff, buff + len);
+    output.p(i, flattenedArr->e<T>(position));
+  }
+
+  delete flattenedArr;
+}
+
+void percentile(sd::LaunchContext* context, NDArray& input, NDArray& output, std::vector<LongType>& axises,
+                const float q, const int interpolation) {
+  BUILD_SINGLE_SELECTOR(input.dataType(), _percentile, (input, output, axises, q, interpolation), SD_COMMON_TYPES);
+}
+
+BUILD_SINGLE_TEMPLATE( void _percentile,
+                      (NDArray& input, NDArray& output, std::vector<LongType>& axises, const float q,
+                       const int interpolation),
+                      SD_COMMON_TYPES);
+
+}  // namespace helpers
+}  // namespace ops
+}  // namespace sd
+#endif