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
@@ -0,0 +1,61 @@
+/* ******************************************************************************
+ *
+ *
+ * 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 GS <sgazeos@gmail.com>
+//
+#include <execution/Threads.h>
+#include <ops/declarable/helpers/confusion.h>
+#if NOT_EXCLUDED(OP_confusion_matrix)
+namespace sd {
+namespace ops {
+namespace helpers {
+
+template <typename T>
+static void _confusionFunctor(NDArray* labels, NDArray* predictions, NDArray* weights, NDArray* output) {
+  ResultSet arrs = output->allTensorsAlongDimension({1});
+  int lLen = labels->lengthOf();
+
+  auto func = PRAGMA_THREADS_FOR {
+    for (sd::LongType j = start; j < stop; j++) {
+      auto label = labels->e<sd::LongType>(j);
+      auto pred = predictions->e<sd::LongType>(j);
+      T value = (weights == nullptr ? (T)1.0f : weights->e<T>(j));
+      T curr = arrs.at(label)->e<T>(pred);
+      arrs.at(label)->p<T>(pred, curr + value);
+    }
+  };
+
+  samediff::Threads::parallel_for(func, 0, lLen);
+}
+
+void confusionFunctor(sd::LaunchContext* context, NDArray* labels, NDArray* predictions, NDArray* weights,
+                      NDArray* output) {
+  auto xType = output->dataType();  // weights can be null
+
+  BUILD_SINGLE_SELECTOR(xType, _confusionFunctor, (labels, predictions, weights, output), SD_NUMERIC_TYPES);
+}
+
+BUILD_SINGLE_TEMPLATE( void _confusionFunctor,
+                      (NDArray * labels, NDArray* predictions, NDArray* weights, NDArray* output);
+                      , SD_NUMERIC_TYPES);
+
+}  // namespace helpers
+}  // namespace ops
+}  // namespace sd
+#endif