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 +1,123 @@
+/* ******************************************************************************
+ *
+ *
+ * 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 24.11.17.
+//
+
+#include <system/op_boilerplate.h>
+#include <helpers/StringUtils.h>
+#if NOT_EXCLUDED(OP_assign)
+
+#include <ops/declarable/CustomOperations.h>
+#include <ops/declarable/generic/helpers/BroadcastHelper.h>
+
+namespace sd {
+namespace ops {
+BROADCASTABLE_OP_IMPL(assign, 0, 0) {
+  auto x = INPUT_VARIABLE(0);
+  auto y = block.width() < 2 ? x: INPUT_VARIABLE(1);
+  auto z = OUTPUT_VARIABLE(0);
+
+  // Check if any array is of string type
+  if (x->isS() || y->isS() || z->isS()) {
+    // Handle string broadcast at high level
+    StringUtils::broadcastStringAssign(x,z);
+    return Status::OK;
+  }
+
+  NDArray *castedX = x->dataType() == z->dataType() ? x : x->cast(z->dataType());
+  NDArray *castedY = y->dataType() == z->dataType() ? y : y->cast(z->dataType());
+
+  ArrayOptions::validateSingleDataType(ArrayOptions::dataType(castedX->shapeInfo()));
+  ArrayOptions::validateSingleDataType(ArrayOptions::extra(castedY->shapeInfo()));
+  ArrayOptions::validateSingleDataType(ArrayOptions::extra(z->shapeInfo()));
+
+  auto tZ = BroadcastHelper::broadcastApply(BroadcastOpsTuple::Assign(), castedX, castedY, z);
+
+  if (tZ != z) {
+    OVERWRITE_RESULT(tZ);
+  }
+
+  // Cleanup casted arrays if they were allocated
+  if (castedX != x) delete castedX;
+  if (castedY != y) delete castedY;
+
+  return Status::OK;
+}
+DECLARE_SYN(set, assign);
+DECLARE_SYN(copy, assign);
+
+DECLARE_TYPES(assign) {
+  getOpDescriptor()
+      ->setAllowedInputTypes(0, {ALL_INTS,ALL_FLOATS,ALL_STRINGS,BOOL})
+      ->setAllowedInputTypes(1, {ALL_INTS,ALL_FLOATS,ALL_STRINGS,BOOL})
+      ->setAllowedOutputTypes(0, {ALL_INTS,ALL_FLOATS,ALL_STRINGS,BOOL});
+}
+
+DECLARE_TYPES(assign_bp) {
+  getOpDescriptor()->setAllowedInputTypes(ANY)->setAllowedOutputTypes({ALL_INTS,ALL_FLOATS,ALL_STRINGS});
+}
+
+CUSTOM_OP_IMPL(assign_bp, 3, 2, false, 0, 0) {
+  auto x = INPUT_VARIABLE(0);
+  auto y = block.width() < 2 ? x->dup(x->ordering(), false) : INPUT_VARIABLE(1);  // dup() already returns NDArray*
+  auto epsNext = INPUT_VARIABLE(2);
+
+  auto gradX = OUTPUT_VARIABLE(0);
+  auto gradY = OUTPUT_VARIABLE(1);
+
+  float zero = 0.0f;
+  gradX->assign(zero);
+
+  if (x->isSameShape(y)) {
+    gradY->assign(epsNext);
+  } else if (y->isScalar()) {
+    auto sum = epsNext->reduceNumber(reduce::Sum);
+    gradY->assign(sum);
+    delete sum;
+  } else {
+    // broadcastable
+    auto axisY = ShapeUtils::evalBroadcastBackwardAxis(y->shapeInfo(), epsNext->shapeInfo());
+
+    if (axisY.size() > 0) {
+      auto sum = epsNext->reduceAlongDimension(reduce::Sum, &axisY);
+      gradY->assign(sum);
+      delete sum;
+    } else
+      gradY->assign(epsNext);
+  }
+
+  return Status::OK;
+}
+
+DECLARE_SHAPE_FN(assign_bp) {
+  auto x = inputShape->at(0);
+  auto y = inputShape->at(1);
+  auto e = inputShape->at(2);
+
+  // eps always has shape of x
+  // grad always has shape of y
+  auto shapeList = SHAPELIST(CONSTANT(x), CONSTANT(y));
+
+  return shapeList;
+}
+}  // namespace ops
+}  // namespace sd
+
+#endif