/******************************************************************************* * 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 ******************************************************************************/ // // @author raver119@gmail.com // #include namespace nd4j { namespace ops { namespace helpers { template static void flatten_(std::vector &inputs, NDArray *output, const char order) { int numArrays = inputs.size(); std::vector offsets(numArrays); Nd4jLong cOffset = 0; // calculating offsets in output for (int e = 0; e < numArrays; e++) { offsets[e] = cOffset; cOffset += inputs[e]->lengthOf(); } // actually transferring data for (int e = 0; e < numArrays; e++) { auto z = reinterpret_cast(output->bufferWithOffset(offsets[e])); auto xBuffer = inputs[e]->bufferAsT(); auto xShapeInfo = inputs[e]->shapeInfo(); auto xLength = inputs[e]->lengthOf(); for (Nd4jLong i = 0; i < xLength; i++) z[i] = xBuffer[getIndexOffsetOrdered(i, xShapeInfo, order)]; } } void flatten(nd4j::LaunchContext *context, std::vector &inputs, NDArray *output, char order) { BUILD_SINGLE_SELECTOR(output->dataType(), flatten_, (inputs, output, order), LIBND4J_TYPES); } } } }