cavis/libnd4j/include/ops/declarable/generic/parity_ops/cholesky.cpp

46 lines
1.9 KiB
C++

/*******************************************************************************
* 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 <sgazeos@gmail.com> at 11/12/2018
//
#include <op_boilerplate.h>
#if NOT_EXCLUDED(OP_cholesky)
#include <ops/declarable/CustomOperations.h>
#include <ops/declarable/helpers/lup.h>
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