/******************************************************************************* * 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 George A. Shulinok 4/18/2019 // #ifndef LIBND4J_HEADERS_BARNES_HUT_TSNE_H #define LIBND4J_HEADERS_BARNES_HUT_TSNE_H #include namespace nd4j { namespace ops { /** * This operation used as helper with BarnesHutTsne class * to compute edge forces using barnes hut * * Expected input: * 0: 1D row-vector (or with shape (1, m)) * 1: 1D integer vector with slice nums * 2: 1D float-point values vector with same shape as above * 3: 2D float-point matrix with data to search * * Int args: * 0: N - number of slices * * Output: * 0: 2D matrix with the same shape and type as the 3th argument */ #if NOT_EXCLUDED(OP_barnes_edge_forces) DECLARE_CUSTOM_OP(barnes_edge_forces, 4, 1, false, 0, 1); #endif /** * This operation used as helper with BarnesHutTsne class * to Symmetrize the value matrix * * Expected input: * 0: 1D int row-vector * 1: 1D int col-vector * 2: 1D float vector with values * * Output: * 0: 1D int result row-vector * 1: 1D int result col-vector * 2: a float-point tensor with shape 1xN, with values from the last input vector */ #if NOT_EXCLUDED(OP_barnes_symmetrized) DECLARE_CUSTOM_OP(barnes_symmetrized, 3, 3, false, 0, -1); #endif /** * This operation used as helper with BranesHutTsne class * to compute x = x + 2 * yGrads / abs(yGrads) != yIncs / abs(yIncs) * * Expected input: * 0: input tensor * 1: input gradient * 2: gradient step tensor * * Output: * 0: result of expression above */ #if NOT_EXCLUDED(OP_barnes_gains) DECLARE_OP(barnes_gains, 3, 1, true); #endif /** * This operation used as helper with Cell class * to check vals in given set * * Expected input: * 0: 1D float row-vector (corners) * 1: 1D float col-vector (widths) * 2: 1D float vector (point) * * Output: * 0: bool val */ #if NOT_EXCLUDED(OP_cell_contains) DECLARE_CUSTOM_OP(cell_contains, 3, 1, false, 0, 1); #endif } } #endif // LIBND4J_HEADERS_BARNES_HUT_TSNE_H