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 +1,163 @@
+/* ******************************************************************************
+ *
+ *
+ * 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
+ ******************************************************************************/
+
+//
+//  @author raver119@gmail.com
+//
+
+#include <system/op_boilerplate.h>
+#if NOT_EXCLUDED(OP_bincount)
+
+#include <ops/declarable/CustomOperations.h>
+#include <ops/declarable/helpers/weights.h>
+
+namespace sd {
+namespace ops {
+DECLARE_TYPES(bincount) {
+  getOpDescriptor()
+      ->setAllowedInputTypes({ALL_INTS})
+      ->setAllowedInputTypes(1, ANY)
+      ->setAllowedOutputTypes({ALL_INTS, ALL_FLOATS});
+}
+
+CUSTOM_OP_IMPL(bincount, 1, 1, false, 0, 0) {
+  auto values = INPUT_VARIABLE(0)->cast(INT64);
+
+  NDArray *weights = nullptr;
+
+  LongType maxLength = -1;
+  LongType minLength = 0;
+  LongType maxIndex = values->argMax();
+  maxLength = values->e<LongType>(maxIndex) + 1;
+
+  if (block.numI() > 0) {
+    minLength = math::sd_max(INT_ARG(0), (LongType) 0L);
+    if (block.numI() == 2) maxLength = math::sd_min(maxLength, INT_ARG(1));
+  }
+
+  if (block.width() == 2) {  // the second argument is weights
+    weights = INPUT_VARIABLE(1);
+    if (weights->lengthOf() < 1) {
+      auto* valuesShape = values->getShapeAsVector();
+      weights = NDArrayFactory::create_('c', *valuesShape, values->dataType());
+      delete valuesShape;
+      int one = 1;
+      weights->assign(one);
+    } else if (weights->isScalar()) {
+      auto value = weights->cast(INT64)->asVectorT<LongType>();
+      auto* valuesShape = values->getShapeAsVector();
+      weights = NDArrayFactory::create_('c', *valuesShape, values->dataType());
+      delete valuesShape;
+      weights->assign(value[0]);
+    }
+
+
+    REQUIRE_TRUE(values->isSameShape(weights), 0, "bincount: the input and weights shapes should be equals");
+  } else if (block.width() == 3) {  // the second argument is min and the third is max
+    auto min = INPUT_VARIABLE(1);
+    auto max = min;
+    if (INPUT_VARIABLE(2)->lengthOf() > 0) {
+      max = INPUT_VARIABLE(2);
+    }
+    minLength = min->e<LongType>(0);
+    maxLength = max->e<LongType>(0);
+  } else if (block.width() > 3) {
+    auto min = INPUT_VARIABLE(2);
+    auto max = INPUT_VARIABLE(3);
+    minLength = min->e<LongType>(0);
+    if (INPUT_VARIABLE(2)->lengthOf() > 0) {
+      maxLength = max->e<LongType>(0);
+    } else
+      maxLength = minLength;
+    weights = INPUT_VARIABLE(1);
+    if (weights->lengthOf() < 1) {
+      auto* valuesShape = values->getShapeAsVector();
+      weights = NDArrayFactory::create_('c', *valuesShape, values->dataType());
+      delete valuesShape;
+      int one = 1;
+      weights->assign(one);
+    } else if (weights->isScalar()) {
+      auto value = weights->asVectorT<LongType>();
+      auto* valuesShape = values->getShapeAsVector();
+      weights = NDArrayFactory::create_('c', *valuesShape, values->dataType());
+      delete valuesShape;
+      weights->assign(value[0]);
+    }
+    REQUIRE_TRUE(values->isSameShape(weights), 0, "bincount: the input and weights shapes should be equals");
+  }
+
+  minLength = math::sd_max(minLength, (LongType) 0);
+  maxLength = math::sd_min(maxLength, values->e<LongType>(maxIndex) + 1);
+
+  auto result = OUTPUT_VARIABLE(0);
+  float zero = 0.0f;
+  result->assign(zero);
+
+  helpers::adjustWeights(block.launchContext(), values, weights, result, minLength, maxLength);
+  if(weights->isScalar()) {
+    delete weights;
+  }
+  return Status::OK;
+}
+
+DECLARE_SHAPE_FN(bincount) {
+  auto shapeList = SHAPELIST();
+  auto in = INPUT_VARIABLE(0);
+  DataType dtype = INT64;
+  if (block.width() > 1)
+    dtype = ArrayOptions::dataType(inputShape->at(1));
+  else if (block.numI() > 2)
+    dtype = (DataType)INT_ARG(2);
+
+  LongType maxIndex = in->argMax();
+  LongType maxLength = in->e<LongType>(maxIndex) + 1;
+  LongType outLength = maxLength;
+
+  if (block.numI() > 0) outLength = math::sd_max(maxLength, INT_ARG(0));
+
+  if (block.numI() > 1) outLength = math::sd_min(outLength, INT_ARG(1));
+
+  if (block.width() == 3) {  // the second argument is min and the third is max
+    auto min = INPUT_VARIABLE(1)->e<LongType>(0);
+    auto max = min;
+    if (INPUT_VARIABLE(2)->lengthOf() > 0) {
+      max = INPUT_VARIABLE(2)->e<LongType>(0);
+    }
+
+    outLength = math::sd_max(maxLength, min);
+    outLength = math::sd_min(outLength, max);
+  } else if (block.width() > 3) {
+    auto min = INPUT_VARIABLE(2);
+    auto max = min;
+    if (INPUT_VARIABLE(3)->lengthOf() > 0) {
+      max = INPUT_VARIABLE(3);
+    }
+    outLength = math::sd_max(maxLength, min->e<LongType>(0));
+    outLength = math::sd_min(outLength, max->e<LongType>(0));
+  }
+
+  auto newshape = ConstantShapeHelper::getInstance().vectorShapeInfo(outLength, dtype);
+
+  shapeList->push_back(newshape);
+  return shapeList;
+}
+
+}  // namespace ops
+}  // namespace sd
+
+#endif