/******************************************************************************* * Copyright (c) 2015-2018 Skymind, Inc. * * 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. * * 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 GS // #include #if NOT_EXCLUDED(OP_embedding_lookup) #include #include #include #include namespace sd { namespace ops { ////////////////////////////////////////////////////////////////////////// CUSTOM_OP_IMPL(embedding_lookup, 2, 1, false, 0, 1) { auto input = INPUT_VARIABLE(0); // lookup param auto indices = INPUT_VARIABLE(1); // indices, as is auto output = OUTPUT_VARIABLE(0); // if (block.width() > 2) { // multiple input indices = INPUT_VARIABLE(block.width() - 1); std::vector dims(input->rankOf()); int i = output->rankOf() - input->rankOf(); for (auto& v: dims){ v = i++; } ResultSet outputView = output->allTensorsAlongDimension(dims); REQUIRE_TRUE(block.width() > output->sizeAt(0), 0, "embedding_lookup: input list should be greater then %i, but %i given.", output->sizeAt(0), block.width() ); for (Nd4jLong e = 0; e < indices->lengthOf(); ++e) { Nd4jLong thisIndex = (*indices).e(e); input = INPUT_VARIABLE(thisIndex); // lookup param outputView.at(e)->assign(input); } } else { int indexRank = indices->rankOf(); REQUIRE_TRUE(indexRank > 0, 0, "embeded_lookup: input array of indexes can't be single scalar, the requirement is: rank > 0 !"); int inputRank = input->rankOf(); int lastIndDim = indices->lengthOf(); int partition_mode = INT_ARG(0); // partition_mode == 0 - i.e. 'mod' , 1 - 'div' sd::ops::gather op; auto result(op.evaluate({input, indices}, {0})); REQUIRE_TRUE(result.status() == Status::OK(), 0, "embedding_lookup: cannot retrieve results from gather op."); REQUIRE_TRUE(result.at(0)->isSameShape(output), 0, "embedding_lookup: wrong shape of return from gather op."); output->assign(result.at(0)); } return Status::OK(); } DECLARE_TYPES(embedding_lookup) { getOpDescriptor() ->setAllowedInputTypes(sd::DataType::ANY) ->setAllowedOutputTypes(sd::DataType::ANY); } DECLARE_SHAPE_FN(embedding_lookup) { auto inShapeInfo = inputShape->at(0); auto indicesShapeInfo = inputShape->at(1); int inRank = shape::rank(inShapeInfo); if (inputShape->size() == 2u) { int outRank = inRank; std::vector shapeInfo(outRank); shapeInfo[0] = indicesShapeInfo[1]; // vector - how many elements for (int e = 1; e < outRank; e++) shapeInfo[e] = shape::sizeAt(inShapeInfo, e); auto outShapeInfo = ConstantShapeHelper::getInstance().createShapeInfo(ArrayOptions::dataType(inShapeInfo), shape::order(inShapeInfo), shapeInfo); return SHAPELIST(outShapeInfo); } int outRank = inRank + 1; std::vector shapeInfo(outRank); auto indices = INPUT_VARIABLE(block.width() - 1); shapeInfo[0] = indices->lengthOf(); // vector - how many elements for (int e = 1; e < outRank; e++) shapeInfo[e] = shape::sizeAt(inShapeInfo, e); auto outShapeInfo = ConstantShapeHelper::getInstance().createShapeInfo(ArrayOptions::dataType(inShapeInfo), shape::order(inShapeInfo), shapeInfo); return SHAPELIST(outShapeInfo); } } } #endif