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 03.01.2018
+//
+#include <array/NDArrayFactory.h>
+#include <helpers/biDiagonalUp.h>
+#include <helpers/jacobiSVD.h>
+#include <helpers/svd.h>
+#if NOT_EXCLUDED(OP_svd)
+namespace sd {
+namespace ops {
+namespace helpers {
+
+//////////////////////////////////////////////////////////////////////////
+// svd operation, this function is not method of SVD class, it is standalone function
+template <typename T>
+static void svd_(NDArray* x, const std::vector<NDArray*>& outArrs, const bool fullUV, const bool calcUV,
+                 const int switchNum) {
+  auto s = outArrs[0];
+  auto u = outArrs[1];
+  auto v = outArrs[2];
+  const int rank = x->rankOf();
+  const int sRank = rank - 1;
+
+  auto listX = x->allTensorsAlongDimension({rank - 2, rank - 1});
+  auto listS = s->allTensorsAlongDimension({sRank - 1});
+  ResultSet *listU(nullptr), *listV(nullptr);
+
+  if (calcUV) {
+    listU = new ResultSet(u->allTensorsAlongDimension({rank - 2, rank - 1}));
+    listV = new ResultSet(v->allTensorsAlongDimension({rank - 2, rank - 1}));
+  }
+
+  for (int i = 0; i < listX.size(); ++i) {
+    helpers::SVD<T> svdObj(*(listX.at(i)), switchNum, calcUV, calcUV, fullUV);
+    listS.at(i)->assign(&svdObj._s);
+
+    if (calcUV) {
+      listU->at(i)->assign(&svdObj._u);
+      listV->at(i)->assign(&svdObj._v);
+    }
+  }
+
+  if (calcUV) {
+    delete listU;
+    delete listV;
+  }
+}
+
+//////////////////////////////////////////////////////////////////////////
+void svd(sd::LaunchContext* context, NDArray* x, const std::vector<NDArray*>& outArrs, const bool fullUV,
+         const bool calcUV, const int switchNum) {
+  BUILD_SINGLE_SELECTOR(x->dataType(), svd_, (x, outArrs, fullUV, calcUV, switchNum), SD_FLOAT_TYPES);
+}
+
+}  // namespace helpers
+}  // namespace ops
+}  // namespace sd
+#endif