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
+ ******************************************************************************/
+
+//
+// Created by george@skymind.io on 2/21/2018.
+// Modified by sgazeos@gmail.com on 4/4/2018
+
+#include <system/op_boilerplate.h>
+#if NOT_EXCLUDED(OP_sufficient_statistics)
+
+#include <ops/declarable/CustomOperations.h>
+#include <ops/declarable/helpers/axis.h>
+namespace sd {
+namespace ops {
+CUSTOM_OP_IMPL(sufficient_statistics, 2, 3, false, 0, 0) {
+  auto input = INPUT_VARIABLE(0);
+  auto axisVector = INPUT_VARIABLE(1);
+  auto dataCount = OUTPUT_VARIABLE(0);
+
+  auto sum = OUTPUT_VARIABLE(1);
+  auto squares = OUTPUT_VARIABLE(2);
+
+  std::vector<LongType> axis(axisVector->lengthOf());
+
+  // axis might be dynamic (i.e. tf mode)
+  helpers::adjustAxis(input->rankOf(), axisVector, axis);
+
+  input->reduceAlongDimension(reduce::SquaredNorm, squares, &axis);
+  input->reduceAlongDimension(reduce::Sum, sum, &axis);
+  auto count = NDArrayFactory::create(input->dataType(), input->lengthOf() / sum->lengthOf());
+  dataCount->assign(count);
+  if (block.numT() > 0) {
+    auto shift = OUTPUT_VARIABLE(3);
+#ifdef HAS_DOUBLE
+    double shiftValue = static_cast<double>(T_ARG(0));
+    shift->assign(shiftValue);
+#elif defined(HAS_FLOAT32)
+    float shiftValue = static_cast<float>(T_ARG(0));
+    shift->assign(shiftValue);
+#else
+#error "No floating-point type available for sufficient_statistics operation"
+#endif
+  }
+
+  delete count;
+  return Status::OK;
+}
+
+DECLARE_TYPES(sufficient_statistics) {
+  getOpDescriptor()->setAllowedInputTypes(0, {ALL_INTS, ALL_FLOATS});
+  getOpDescriptor()->setAllowedInputTypes(1, {INT32, INT64});
+  getOpDescriptor()->setAllowedOutputTypes(0, INHERIT);
+  getOpDescriptor()->setAllowedOutputTypes(1, INHERIT);
+  getOpDescriptor()->setAllowedOutputTypes(2, INHERIT);
+}
+
+DECLARE_SHAPE_FN(sufficient_statistics) {
+  auto axisVector = INPUT_VARIABLE(1);
+  std::vector<LongType> axis(axisVector->lengthOf());
+
+  auto input = INPUT_VARIABLE(0);
+  helpers::adjustAxis(input->rankOf(), axisVector, axis);
+
+  auto scalarShape = ConstantShapeHelper::getInstance().scalarShapeInfo(ArrayOptions::dataType(inputShape->at(0)));
+  auto sumShape = ShapeUtils::evalReduceShapeInfo('c', &axis, *input, false, false, block.workspace());
+
+  auto squareShape = ShapeUtils::evalReduceShapeInfo('c', &axis, *input, false, false, block.workspace());
+
+  auto shapeList = SHAPELIST(scalarShape, sumShape, squareShape);
+  if (block.numT() > 0)
+    shapeList->push_back(ConstantShapeHelper::getInstance().scalarShapeInfo(ArrayOptions::dataType(inputShape->at(0))));
+
+  return shapeList;
+}
+}  // namespace ops
+
+}  // namespace sd
+
+#endif