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 +1,152 @@
+/* ******************************************************************************
+ *
+ *
+ * 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
+ ******************************************************************************/
+
+//
+// Created by GS <sgazeos@gmail.com> at 2/26/2018
+//
+
+#include <ops/declarable/CustomOperations.h>
+#include <ops/declarable/helpers/lup.h>
+#include <system/op_boilerplate.h>
+
+#if NOT_EXCLUDED(OP_matrix_determinant)
+namespace sd {
+namespace ops {
+CUSTOM_OP_IMPL(matrix_determinant, 1, 1, false, 0, 0) {
+  auto input = INPUT_VARIABLE(0);
+  auto output = OUTPUT_VARIABLE(0);
+
+  REQUIRE_TRUE(input->rankOf() >= 2, 0,
+               "matrix_determinant: The rank of input array should not less than 2, but %i is given", input->rankOf());
+  REQUIRE_TRUE(input->sizeAt(-1) == input->sizeAt(-2), 0,
+               "matrix_determinant: The last two dimensions should be equal, but %i and %i are given",
+               input->sizeAt(-1), input->sizeAt(-2));
+
+  return helpers::determinant(block.launchContext(), input, output);
+}
+
+DECLARE_SHAPE_FN(matrix_determinant) {
+  auto inShape = inputShape->at(0);
+
+  LongType * determinantShape;
+  int targetRank = shape::rank(inShape) - 2;  // last two dimensions will be reduced to scalar
+
+  if (targetRank == 0) {  // scalar only
+    determinantShape = ConstantShapeHelper::getInstance().scalarShapeInfo(ArrayOptions::dataType(inShape));
+  } else if (targetRank == 1) {  // vector
+    determinantShape =
+        ConstantShapeHelper::getInstance().vectorShapeInfo(shape::sizeAt(inShape, static_cast<LongType>(0)), ArrayOptions::dataType(inShape));
+  } else {  // only two last dimensions are excluded
+    determinantShape = ConstantShapeHelper::getInstance().createShapeInfo(
+        ArrayOptions::dataType(inShape), shape::order(inShape), targetRank, shape::shapeOf(inShape), -1);
+  }
+  return SHAPELIST(determinantShape);
+}
+
+DECLARE_TYPES(matrix_determinant) {
+  getOpDescriptor()->setAllowedInputTypes(ANY)->setAllowedOutputTypes({ALL_FLOATS});
+}
+}  // namespace ops
+}  // namespace sd
+
+#endif
+
+#if NOT_EXCLUDED(OP_log_matrix_determinant)
+namespace sd {
+namespace ops {
+DECLARE_TYPES(log_matrix_determinant) {
+  getOpDescriptor()->setAllowedInputTypes(ANY)->setAllowedOutputTypes({ALL_FLOATS});
+}
+
+CUSTOM_OP_IMPL(log_matrix_determinant, 1, 1, false, 0, 0) {
+  auto input = INPUT_VARIABLE(0);
+  auto output = OUTPUT_VARIABLE(0);
+
+  REQUIRE_TRUE(input->rankOf() >= 2, 0,
+               "log_matrix_determinant: The rank of input array should not less than 2, but %i is given",
+               input->rankOf());
+  REQUIRE_TRUE(input->sizeAt(-1) == input->sizeAt(-2), 0,
+               "log_matrix_determinant: The last two dimensions should be equal, but %i and %i are given",
+               input->sizeAt(-1), input->sizeAt(-2));
+
+  return helpers::logAbsDeterminant(block.launchContext(), input, output);
+}
+
+DECLARE_SHAPE_FN(log_matrix_determinant) {
+  auto inShape = inputShape->at(0);
+
+  LongType * determinantShape;
+  int targetRank = shape::rank(inShape) - 2;  // last two dimensions will be reduced to scalar
+
+  if (targetRank == 0) {  // scalar only
+    determinantShape = ConstantShapeHelper::getInstance().scalarShapeInfo(ArrayOptions::dataType(inShape));
+  } else if (targetRank == 1) {  // vector
+    determinantShape =
+        ConstantShapeHelper::getInstance().vectorShapeInfo(shape::sizeAt(inShape, static_cast<LongType>(0)), ArrayOptions::dataType(inShape));
+  } else {  // only two last dimensions are excluded
+    determinantShape = ConstantShapeHelper::getInstance().createShapeInfo(
+        ArrayOptions::dataType(inShape), shape::order(inShape), targetRank, shape::shapeOf(inShape), -1);
+  }
+  return SHAPELIST(determinantShape);
+}
+}  // namespace ops
+}  // namespace sd
+#endif
+
+#if NOT_EXCLUDED(OP_logdet)
+namespace sd {
+namespace ops {
+DECLARE_TYPES(logdet) {
+  getOpDescriptor()->setAllowedInputTypes(ANY)->setAllowedOutputTypes({ALL_FLOATS});
+}
+
+CUSTOM_OP_IMPL(logdet, 1, 1, false, 0, 0) {
+  auto input = INPUT_VARIABLE(0);
+  auto output = OUTPUT_NULLIFIED(0);
+
+  REQUIRE_TRUE(input->rankOf() >= 2, 0, "logdet: The rank of input array should not less than 2, but %i is given",
+               input->rankOf());
+  REQUIRE_TRUE(input->sizeAt(-1) == input->sizeAt(-2), 0,
+               "logdet: The last two dimensions should be equal, but %i and %i are given", input->sizeAt(-1),
+               input->sizeAt(-2));
+  REQUIRE_TRUE(helpers::checkCholeskyInput(block.launchContext(), input), 0,
+               "logdet: The input tensor should be positive-defined hermitian.");
+
+  return helpers::logdetFunctor(block.launchContext(), input, output);
+}
+
+DECLARE_SHAPE_FN(logdet) {
+  auto inShape = inputShape->at(0);
+
+  LongType* determinantShape;
+  int targetRank = shape::rank(inShape) - 2;  // last two dimensions will be reduced to scalar
+
+  if (targetRank == 0) {  // scalar only
+    determinantShape = ConstantShapeHelper::getInstance().scalarShapeInfo(ArrayOptions::dataType(inShape));
+  } else if (targetRank == 1) {  // vector
+    determinantShape =
+        ConstantShapeHelper::getInstance().vectorShapeInfo(shape::sizeAt(inShape, static_cast<LongType>(0)), ArrayOptions::dataType(inShape));
+  } else {  // only two last dimensions are excluded
+    determinantShape = ConstantShapeHelper::getInstance().createShapeInfo(
+        ArrayOptions::dataType(inShape), shape::order(inShape), targetRank, shape::shapeOf(inShape), -1);
+  }
+  return SHAPELIST(determinantShape);
+}
+}  // namespace ops
+}  // namespace sd
+#endif