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 +1,102 @@
+/*
+ *  ******************************************************************************
+ *  *
+ *  *
+ *  * 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 01.11.2017.
+// Modified by GS <sgazeos@gmail.com> 4/5/2018
+
+#include <system/op_boilerplate.h>
+#if NOT_EXCLUDED(OP_argmax)
+
+#include <helpers/ConstantTadHelper.h>
+#include <ops/declarable/CustomOperations.h>
+#include <ops/declarable/helpers/axis.h>
+#include <ops/declarable/helpers/reductions.h>
+
+namespace sd {
+namespace ops {
+DECLARE_TYPES(argmax) {
+  getOpDescriptor()->setAllowedInputTypes({ALL_FLOATS, ALL_INTS})->setAllowedOutputTypes({ANY});
+}
+
+CUSTOM_OP_IMPL(argmax, 1, 1, false, 0, -2) {
+  auto input = INPUT_VARIABLE(0);
+  auto output = OUTPUT_VARIABLE(0);
+
+  if (output->isEmpty() || output->lengthOf() < 1) return Status::OK;
+
+  auto axis = *block.getIArguments();
+
+  // axis might be dynamic (i.e. tf mode)
+  if (block.width() > 1 && axis.size() == 0) {
+    auto axisVector = INPUT_VARIABLE(1);
+    helpers::adjustAxis(input->rankOf(), axisVector, axis);
+    helpers::argMax(*input, *output, axis);
+  } else {
+    helpers::argMax(*input, *output, axis);
+  }
+
+  STORE_RESULT(output);
+
+  return Status::OK;
+}
+
+DECLARE_SHAPE_FN(argmax) {
+  auto firstInputShape = inputShape->at(0);
+  if(shape::isScalar(firstInputShape)) {
+    return SHAPELIST(ConstantShapeHelper::getInstance().scalarShapeInfo(DataType::INT64));
+  }
+  std::vector<LongType> dims;
+
+  if (block.width() == 1) {
+    dims = *block.getIArguments();
+  } else {
+    auto y = INPUT_VARIABLE(1)->cast(INT64);
+    dims = y->template asVectorT<LongType>();
+  }
+
+  auto keepDims = block.numB() ? B_ARG(0) : false;
+  auto dtype = block.numD() ? D_ARG(0) : INT64;
+
+  // we're resolving negative axis here
+  helpers::adjustAxis(shape::rank(inputShape->at(0)), dims);
+
+
+  for (auto d : dims) {
+    // we have special case here
+    if (d == DataTypeUtils::max<int>()) continue;
+
+    REQUIRE_TRUE(d < shape::rank(firstInputShape), 0, "ArgMax: axis can't be above rank")
+    REQUIRE_TRUE(firstInputShape[d + 1] != 0, 0, "ArgMax: you can't reduce along axis with 0 in shape");
+  }
+
+  // special case - output is scalar
+  if (dims.empty() || (dims.size() == 1 && dims.at(0) == DataTypeUtils::max<int>())) {
+    auto ret = ConstantShapeHelper::getInstance().scalarShapeInfo(dtype);
+    return SHAPELIST(ret);
+  }
+
+  auto ret = ShapeUtils::evalReduceShapeInfo('c', &dims, firstInputShape, dtype, keepDims, false, block.getWorkspace());
+  return SHAPELIST(ret);
+}
+}  // namespace ops
+}  // namespace sd
+
+#endif