/******************************************************************************* * 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 raver119 on 29/10/17. // #include #if NOT_EXCLUDED(OP_transpose) #include #include namespace nd4j { namespace ops { ////////////////////////////////////////////////////////////////////////// CUSTOM_OP_IMPL(transpose, 1, 1, true, 0, 0) { auto x = INPUT_VARIABLE(0); if (block.width() == 1) { if (block.isInplace()) { x->transposei(); STORE_RESULT(*x); } else { auto output = OUTPUT_VARIABLE(0); auto t = x->transpose(); output->assign(t); STORE_RESULT(*output); } } else { // this is tf-mode transpose, that's nd4j permute bool replace = false; std::vector arguments(*block.getIArguments()); auto w = block.width(); auto a = arguments.size(); if (w == 2 && a == 0) { auto axis = INPUT_VARIABLE(1); for (int e = 0; e < axis->lengthOf(); e++) { auto ax = axis->e(e); if (ax < 0) ax += x->rankOf(); arguments.emplace_back(ax); } replace = true; } else if (a == 0) { for (int e = x->rankOf() - 1; e >= 0; e--) arguments.emplace_back(e); } // 0D edge case if (x->rankOf() == 0) { REQUIRE_TRUE(arguments.size() == 1, 0, "Permute: only one axis is allowed for scalar"); auto output = OUTPUT_VARIABLE(0); if (!block.isInplace()) output->assign(x); return Status::OK(); } if(block.isInplace()) { // in-place x->permutei(arguments); STORE_RESULT(x); } else { auto input = x->permute(arguments); auto output = OUTPUT_VARIABLE(0); output->assign(input); } } return Status::OK(); } DECLARE_TYPES(transpose) { getOpDescriptor() ->setAllowedInputTypes(nd4j::DataType::ANY) ->setSameMode(true); } DECLARE_SHAPE_FN(transpose) { if (block.width() == 1) { auto outputShapeInfo = ShapeUtils::evalTranspShapeInfo(*INPUT_VARIABLE(0), block.workspace()); return SHAPELIST(outputShapeInfo); } else { // this is basically permute mode auto shapeList = SHAPELIST(); auto arguments = block.getIArguments(); if (shape::rank(inputShape->at(0)) == 0) { Nd4jLong *newshape; ALLOCATE(newshape, block.getWorkspace(), shape::shapeInfoLength(inputShape->at(0)), Nd4jLong); newshape[0] = 0; newshape[1] = 0; newshape[2] = 1; newshape[3] = 99; ArrayOptions::copyDataType(newshape, inputShape->at(0)); shapeList->push_back(newshape); } else if (arguments->size() > 0 || inputShape->size() > 1) { auto axis = arguments->size() > 0 ? *arguments : (INPUT_VARIABLE(1))->template asVectorT(); auto outputShapeInfo = ShapeUtils::evalPermShapeInfo(axis.data(), axis.size(), *INPUT_VARIABLE(0), block.workspace()); shapeList->push_back(outputShapeInfo); } else if (inputShape->size() == 2) { // dead end auto axis = INPUT_VARIABLE(1); auto axisV = axis->template asVectorT(); auto newshape = ShapeUtils::evalPermShapeInfo(axisV.data(), axisV.size(), *INPUT_VARIABLE(0), block.workspace()); shapeList->push_back(newshape); } else { int rank = shape::rank(inputShape->at(0)); for (int e = rank - 1; e >= 0; e--) arguments->emplace_back(e); auto outputShapeInfo = ShapeUtils::evalPermShapeInfo(arguments->data(), arguments->size(), *INPUT_VARIABLE(0), block.workspace()); shapeList->push_back(outputShapeInfo); } return shapeList; } } } } #endif