/******************************************************************************* * 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 at 11/12/2018 // #include #if NOT_EXCLUDED(OP_cholesky) #include #include namespace nd4j { namespace ops { OP_IMPL(cholesky, 1, 1, true) { NDArray* input = INPUT_VARIABLE(0); NDArray* output = OUTPUT_VARIABLE(0); REQUIRE_TRUE(input->rankOf() >=2, 0, "cholesky: The rank of input array should not less than 2, but %i is given", input->rankOf()); REQUIRE_TRUE(input->sizeAt(-1) == input->sizeAt(-2), 0, "cholesky: The last two dimmensions should be equal, but %i and %i are given", input->sizeAt(-1), input->sizeAt(-2)); REQUIRE_TRUE(helpers::checkCholeskyInput(block.launchContext(), input), 0, "cholesky: The input tensor should be positive-defined and symmetric."); return helpers::cholesky(block.launchContext(), input, output); } DECLARE_TYPES(cholesky) { getOpDescriptor() ->setAllowedInputTypes(nd4j::DataType::ANY) ->setAllowedOutputTypes({ALL_FLOATS}); } } } #endif