/******************************************************************************* * 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 Yurii Shyrma on 07.12.2017. // #include "ResultSet.h" #include namespace nd4j { namespace ops { namespace helpers { ////////////////////////////////////////////////////////////////////////// // Returns a batched matrix tensor with new batched diagonal values. // for detailed explanations please take a look on web page: https://www.tensorflow.org/api_docs/python/tf/matrix_set_diag template static void _matrixSetDiag(const NDArray* input, const NDArray* diagonal, NDArray* output) { *output = *input; const int lastDimSize = input->sizeAt(-1); const int last2DimSize = input->sizeAt(-1) * input->sizeAt(-2); const int lastSmallDim = diagonal->sizeAt(-1); const int batchSize = input->lengthOf()/last2DimSize; for(int i = 0; i < batchSize; ++i ) for(int j = 0; j < lastSmallDim; ++j) { output->p(i*last2DimSize + j*(lastDimSize + 1), diagonal->e(i*lastSmallDim + j)); } } void matrixSetDiag(nd4j::LaunchContext * context, const NDArray* input, const NDArray* diagonal, NDArray* output) { BUILD_SINGLE_SELECTOR(input->dataType(), _matrixSetDiag, (input, diagonal, output), LIBND4J_TYPES); } BUILD_SINGLE_TEMPLATE(template void _matrixSetDiag, (const NDArray* input, const NDArray* diagonal, NDArray* output), LIBND4J_TYPES); } } }