/* ****************************************************************************** * * * 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 #include #include #include #include #include namespace sd { namespace ops { LegacyReduceLongOp::LegacyReduceLongOp() : LegacyOp(1) { // } LegacyReduceLongOp::LegacyReduceLongOp(int opNum) : LegacyOp(1, opNum) { } LegacyOp* LegacyReduceLongOp::clone() { return new LegacyReduceLongOp(this->_opNum); } Status LegacyReduceLongOp::validateAndExecute(Context& block) { auto x = INPUT_VARIABLE(0); auto z = OUTPUT_VARIABLE(0); NDArray::prepareSpecialUse({z}, {x}); int opNum = block.opNum() < 0 ? this->_opNum : block.opNum(); sd_debug("Executing LegacyReduceFloatOp: [%i]\n", opNum); auto axis = *block.getAxis(); bool allAxes = false; ExtraArguments extras(*block.getTArguments()); PointersManager manager(block.launchContext(), "LegacyReduceLongOp"); if (block.width() == 1) { if (axis.size() == static_cast(x->rankOf())) allAxes = true; if ((axis.empty()) || (axis.size() == 1 && axis[0] == DataTypeUtils::max()) || allAxes) { // scalar NativeOpExecutioner::execReduceLongScalar( 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 dims(axis); for (size_t e = 0; e < dims.size(); e++) if (dims[e] < 0) dims[e] += x->rankOf(); if (dims.size() > 1) std::sort(dims.begin(), dims.end()); REQUIRE_TRUE(dims.size() > 0, 0, "Some dimensions required for reduction!"); const LongType* zShapeInfoH = z->shapeInfo(); const LongType* zShapeInfoD = z->specialShapeInfo(); if (x->rankOf() - dims.size() != static_cast(z->rankOf())) { auto zPack = ConstantShapeHelper::getInstance().createShapeInfoWithNoUnitiesForReduce( z->shapeInfo(), &dims, z->getContext()->getWorkspace()); zShapeInfoH = reinterpret_cast(zPack->primary()); zShapeInfoD = reinterpret_cast(zPack->special()); } std::vector *dims2 = ShapeUtils::evalDimsForReduceOp(x->rankOf(), &dims); NativeOpExecutioner::execReduceLong(block.launchContext(), opNum, x->buffer(), x->shapeInfo(), x->specialBuffer(), x->specialShapeInfo(), nullptr, z->buffer(), zShapeInfoH, z->specialBuffer(), zShapeInfoD, dims2->data(), dims2->size()); delete dims2; } STORE_RESULT(*z); } else { auto indices = INPUT_VARIABLE(1); if (indices->lengthOf() == x->rankOf()) allAxes = true; std::vector dims(indices->lengthOf()); for (int e = 0; e < indices->lengthOf(); e++) { // segfault on macOS if not like this int f = indices->e(e); dims[e] = f >= 0 ? f : f += x->rankOf(); } if ((block.getIArguments()->size() == 1 && INT_ARG(0) == DataTypeUtils::max()) || allAxes) { // scalar NativeOpExecutioner::execReduceLongScalar( 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 REQUIRE_TRUE(dims.size() > 0, 0, "Some dimensions required for reduction!"); const LongType* zShapeInfoH = z->shapeInfo(); const LongType* zShapeInfoD = z->specialShapeInfo(); if (x->rankOf() - dims.size() != static_cast(z->rankOf())) { auto zPack = ConstantShapeHelper::getInstance().createShapeInfoWithNoUnitiesForReduce( z->shapeInfo(), &dims, z->getContext()->getWorkspace()); zShapeInfoH = reinterpret_cast(zPack->primary()); zShapeInfoD = reinterpret_cast(zPack->special()); } std::vector *dims2 = ShapeUtils::evalDimsForReduceOp(x->rankOf(), &dims); NativeOpExecutioner::execReduceLong(block.launchContext(), opNum, x->buffer(), x->shapeInfo(), x->specialBuffer(), x->specialShapeInfo(), nullptr, z->buffer(), zShapeInfoH, z->specialBuffer(), zShapeInfoD, dims2->data(), dims2->size()); delete dims2; } } manager.synchronize(); traceExecIfNeeded(block); return Status::OK; } /** * 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* LegacyReduceLongOp::calculateOutputShape(ShapeList* inputShape, Context& block) { auto inShape = inputShape->at(0); LongType* newShape; auto keepDims = block.numB() > 0 ? B_ARG(0) : false; auto newFormat = block.numB() > 1 ? B_ARG(1) : true; auto axis = block.width() > 1 ? INPUT_VARIABLE(1)->asVectorT() : *block.getAxis(); // in this case we're building proper shape for reduction return SHAPELIST(ShapeUtils::evalReduceShapeInfo(shape::order(inShape), &axis, inShape, DataType::INT64, keepDims, !newFormat, block.workspace())); } } // namespace ops } // namespace sd