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 +1,188 @@
+/* ******************************************************************************
+ *
+ *
+ * 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 raver119 on 16.10.2017.
+//
+#include <helpers/ConstantTadHelper.h>
+#include <helpers/ShapeUtils.h>
+
+#include <ops/declarable/LegacyIndexReduceOp.h>
+#include <ops/declarable/OpRegistrator.h>
+#include <legacy/NativeOpExecutioner.h>
+
+namespace sd {
+namespace ops {
+LegacyIndexReduceOp::LegacyIndexReduceOp() : LegacyOp(1) {
+  //
+}
+
+LegacyIndexReduceOp::LegacyIndexReduceOp(int opNum) : LegacyOp(1, opNum) {
+  //
+}
+
+LegacyOp *LegacyIndexReduceOp::clone() { return new LegacyIndexReduceOp(this->_opNum); }
+
+ShapeList *LegacyIndexReduceOp::calculateOutputShape(ShapeList *inputShape, Context &block) {
+  auto inShape = inputShape->at(0);
+
+  if (block.getAxis()->size() == 0 && block.width() == 1) {
+    LongType *newShape;
+    // in this case we just return scalar
+    ALLOCATE(newShape, block.getWorkspace(), shape::shapeInfoLength(2), sd::LongType);
+    newShape[0] = 2;
+    newShape[1] = 1;
+    newShape[2] = 1;
+    newShape[3] = 1;
+    newShape[4] = 1;
+    newShape[6] = 1;
+    newShape[7] = 99;
+
+    auto result = ConstantShapeHelper::getInstance().bufferForShapeInfo(newShape);
+    RELEASE(newShape, block.getWorkspace());
+    return SHAPELIST(result->primary());
+  } else if (block.getAxis()->size()) {
+    // in this case we're building proper shape for reduction
+    auto array = INPUT_VARIABLE(0);
+
+    auto newShape =
+        ShapeUtils::evalReduceShapeInfo('c', block.getAxis(), *array, INT64, false, true, block.workspace());
+    return SHAPELIST(newShape);
+  } else {
+    bool allAxes = false;
+    auto indices = INPUT_VARIABLE(1);
+    LongType rank = shape::rank(inShape);
+    if (indices->lengthOf() == rank) allAxes = true;
+
+    std::vector<LongType> axis(indices->lengthOf());
+    for (int e = 0; e < indices->lengthOf(); e++) {
+      // lol otherwise we segfault on macOS
+      int f = indices->e<int>(e);
+      axis[e] = f >= 0 ? f : f += rank;
+    }
+    if (allAxes) {
+      LongType *newShape;
+      // in this case we just return scalar
+      ALLOCATE(newShape, block.getWorkspace(), shape::shapeInfoLength(2), sd::LongType);
+      newShape[0] = 2;
+      newShape[1] = 1;
+      newShape[2] = 1;
+      newShape[3] = 1;
+      newShape[4] = 1;
+      newShape[6] = 1;
+      newShape[7] = 99;
+
+      auto result = ConstantShapeHelper::getInstance().bufferForShapeInfo(newShape);
+
+      RELEASE(newShape, block.getWorkspace());
+      return SHAPELIST(result->primary());
+    } else {
+      // in this case we're building proper shape for reduction
+      auto array = INPUT_VARIABLE(0);
+      return SHAPELIST(
+          ShapeUtils::evalReduceShapeInfo('c', &axis, *array, DataType::INT64, false, true, block.workspace()));
+    }
+  }
+}
+
+/**
+ *   For all reductions rules are simple: either you return scalar, or you return reduced NDArray.
+ *   It solely depends on input shape, and requested dimensions
+ */
+Status LegacyIndexReduceOp::validateAndExecute(Context &block) {
+  auto x = INPUT_VARIABLE(0);
+  auto z = OUTPUT_VARIABLE(0);
+
+  NDArray::prepareSpecialUse({z}, {x});
+
+  if (z->dataType() != INT64) {
+    THROW_EXCEPTION("IndexReduce operations require output to be INT64");
+  }
+
+  int opNum = block.opNum() < 0 ? this->_opNum : block.opNum();
+
+  bool allAxes = false;
+
+  ExtraArguments extras(*block.getTArguments());
+  PointersManager manager(block.launchContext(), "LegacyIndexReduceOp");
+
+  if (block.width() == 1) {
+    if (block.getAxis()->size() == 0) {
+      // scalar
+      NativeOpExecutioner::execIndexReduceScalar(
+          block.launchContext(), opNum, x->buffer(), x->shapeInfo(), x->specialBuffer(), x->specialShapeInfo(),
+          extras.argumentsAsT(x->dataType()), z->buffer(), z->shapeInfo(), z->specialBuffer(), z->specialShapeInfo());
+    } else {
+      // TAD
+      std::vector<LongType> dims(block.getAxis()->size());
+      for (size_t e = 0; e < dims.size(); e++) {
+        auto axe = block.getAxis()->at(e);
+        dims[e] = axe < 0 ? axe + x->rankOf() : axe;
+      }
+      if (dims.size() > 1) std::sort(dims.begin(), dims.end());
+
+      auto tadPack = ConstantTadHelper::getInstance().tadForDimensions(x->shapeInfo(), &dims);
+
+      NativeOpExecutioner::execIndexReduce(
+          block.launchContext(), opNum, x->buffer(), x->shapeInfo(), x->specialBuffer(), x->specialShapeInfo(),
+          extras.argumentsAsT(x->dataType()), reinterpret_cast<LongType *>(z->buffer()), z->shapeInfo(),
+          z->specialBuffer(), z->specialShapeInfo(), nullptr, (int)dims.size(),
+          Environment::getInstance().isCPU() ? tadPack->primaryShapeInfo() : tadPack->specialShapeInfo(),
+          Environment::getInstance().isCPU() ? tadPack->primaryOffsets() : tadPack->specialOffsets());
+    }
+  } else {
+    // TF mode
+    auto indices = INPUT_VARIABLE(1);
+    if (indices->lengthOf() == x->rankOf()) allAxes = true;
+
+    std::vector<LongType> axis(indices->lengthOf());
+    for (LongType e = 0; e < indices->lengthOf(); e++) {
+      LongType f = indices->e<LongType>(e);
+      axis[e] = f >= 0 ? f : f += x->rankOf();
+    }
+
+    if (allAxes) {
+      NativeOpExecutioner::execIndexReduceScalar(
+          block.launchContext(), opNum, x->buffer(), x->shapeInfo(), x->specialBuffer(), x->specialShapeInfo(),
+          extras.argumentsAsT(x->dataType()), z->buffer(), z->shapeInfo(), z->specialBuffer(), z->specialShapeInfo());
+
+    } else {
+      if (indices->lengthOf() > 1) std::sort(axis.begin(), axis.end());
+
+      REQUIRE_TRUE(axis.size() > 0, 0, "Some dimensions required for reduction!");
+
+      auto tadPack = ConstantTadHelper::getInstance().tadForDimensions(x->shapeInfo(), &axis);
+
+      NativeOpExecutioner::execIndexReduce(
+          block.launchContext(), opNum, x->buffer(), x->shapeInfo(), x->specialBuffer(), x->specialShapeInfo(),
+          extras.argumentsAsT(x->dataType()), reinterpret_cast<LongType *>(z->buffer()), z->shapeInfo(),
+          z->specialBuffer(), z->specialShapeInfo(), nullptr, (int)axis.size(),
+          Environment::getInstance().isCPU() ? tadPack->primaryShapeInfo() : tadPack->specialShapeInfo(),
+          Environment::getInstance().isCPU() ? tadPack->primaryOffsets() : tadPack->specialOffsets());
+    }
+  }
+
+  manager.synchronize();
+  STORE_RESULT(*z);
+  traceExecIfNeeded(block);
+
+
+  return Status::OK;
+}
+}  // namespace ops
+}  // namespace sd