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 +1,125 @@
+/* ******************************************************************************
+ *
+ *
+ * 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 17.10.2017.
+//
+#include <array/DataTypeUtils.h>
+#include <helpers/ConstantTadHelper.h>
+#include <helpers/ShapeUtils.h>
+
+#include <ops/declarable/LegacyStatsOp.h>
+#include <ops/declarable/OpRegistrator.h>
+#include <legacy/NativeOpExecutioner.h>
+
+namespace sd {
+namespace ops {
+Status LegacyStatsOp::validateAndExecute(Context &block) {
+  auto x = INPUT_VARIABLE(0);
+  auto z = OUTPUT_VARIABLE(0);
+
+  NDArray::prepareSpecialUse({z}, {x});
+
+  // we assume that opNuk is either stored in block, or was provided via op constructor
+  int opNum = block.opNum() < 0 ? this->_opNum : block.opNum();
+
+  // bias goes as first argument, unlike all other reductions
+  bool biasCorrected = false;
+  if (block.getIArguments()->size() > 0) biasCorrected = INT_ARG(0) > 0;
+
+  ExtraArguments extras(*block.getTArguments());
+  PointersManager manager(block.launchContext(), "LegacyStatsOp");
+
+  if (block.getIArguments()->size() == 1 ||
+      (block.getIArguments()->size() == 2 && INT_ARG(1) == DataTypeUtils::max<int>())) {
+    // scalar
+    NativeOpExecutioner::execSummaryStatsScalar(block.launchContext(), opNum, x->buffer(), x->shapeInfo(),
+                                                x->specialBuffer(), x->specialShapeInfo(),
+                                                extras.argumentsAsT(z->dataType()), z->buffer(), z->shapeInfo(),
+                                                z->specialBuffer(), z->specialShapeInfo(), biasCorrected);
+  } else {
+    // dimensions for TAD
+    // we should skip first argument here, because it's addressing bias correction
+    std::vector<LongType> dims(*block.getIArguments());
+    for (size_t e = 0; e < dims.size(); e++)
+      if (dims[e] < 0) dims[e] += x->rankOf();
+
+    REQUIRE_TRUE(dims.size() > 0, 0, "Some dimensions requuired for reduction!");
+
+    auto packX = ConstantTadHelper::getInstance().tadForDimensions(x->shapeInfo(), &dims);
+
+    auto pTadShape = Environment::getInstance().isCPU()
+                         ? packX->primaryShapeInfo()
+                         : packX->specialShapeInfo();
+
+    auto pTadOffsets = Environment::getInstance().isCPU()
+                           ? packX->primaryOffsets()
+                           : packX->specialOffsets();
+
+    NativeOpExecutioner::execSummaryStats(block.launchContext(), opNum, x->buffer(), x->shapeInfo(), x->specialBuffer(),
+                                          x->specialShapeInfo(), extras.argumentsAsT(z->dataType()), z->buffer(),
+                                          z->shapeInfo(), z->specialBuffer(), z->specialShapeInfo(), dims.data(),
+                                          (int)dims.size(), pTadShape, pTadOffsets, biasCorrected);
+  }
+
+  manager.synchronize();
+  STORE_RESULT(*z);
+  traceExecIfNeeded(block);
+
+  return Status::OK;
+}
+
+LegacyStatsOp::LegacyStatsOp() : LegacyOp(1) {
+  //
+}
+
+LegacyStatsOp::LegacyStatsOp(int opNum) : LegacyOp(1, opNum) {
+  //
+}
+
+LegacyOp *LegacyStatsOp::clone() { return new LegacyStatsOp(this->_opNum); }
+
+/**
+ *   For all reductions rules are simple: either you return scalar, or you return reduced NDArray.
+ *   It solely depends on input shape, and requested dimensions
+ */
+ShapeList *LegacyStatsOp::calculateOutputShape(ShapeList *inputShape, Context &block) {
+  auto inShape = inputShape->at(0);
+
+  LongType *newShape;
+  if (block.getIArguments()->size() == 0 ||
+      (block.getIArguments()->size() == 1 && INT_ARG(0) == DataTypeUtils::max<int>())) {
+    // 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[5] = 0;
+    newShape[6] = 1;
+    newShape[7] = 99;
+  } else {
+    sd::LongType *xShape2 = ShapeUtils::evalReduceShapeInfo('c', block.getIArguments(), inShape, false, true);
+    return SHAPELIST(xShape2);
+  }
+
+  return SHAPELIST(CONSTANT(newShape));
+}
+}  // namespace ops
+}  // namespace sd