69 lines
2.5 KiB
C++
69 lines
2.5 KiB
C++
/* ******************************************************************************
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*
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* See the NOTICE file distributed with this work for additional
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* information regarding copyright ownership.
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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//
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// Created by GS <sgazeos@gmail.com> on 3/21/2018.
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//
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#include <array/ResultSet.h>
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#include <ops/declarable/helpers/matrix_diag_part.h>
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#include <graph/Status.h>
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#include <execution/Threads.h>
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namespace sd {
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namespace ops {
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namespace helpers {
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//////////////////////////////////////////////////////////////////////////
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// Returns a batched matrix tensor with new batched diagonal values.
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// for detailed explanations please take a look on web page: https://www.tensorflow.org/api_docs/python/tf/matrix_set_diag
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template <typename T>
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int _matrixDiagPart(const NDArray* input, NDArray* output) {
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auto listOut = output->allTensorsAlongDimension({output->rankOf() - 1});
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auto listDiag = input->allTensorsAlongDimension({input->rankOf() - 2, input->rankOf() - 1});
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if (listOut.size() != listDiag. size()) {
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nd4j_printf("matrix_diag_part: Input matrix has wrong shape.", "");
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return ND4J_STATUS_VALIDATION;
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}
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int lastDimension = sd::math::nd4j_min(input->sizeAt(-2), input->sizeAt(-1));
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// TODO: tune this properlys
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int lO = listOut.size();
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auto func = PRAGMA_THREADS_FOR {
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for (auto i = start; i < stop; i++)
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for (int j = 0; j < lastDimension; ++j)
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listOut.at(i)->p(j, listDiag.at(i)->e<T>(j, j));
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};
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samediff::Threads::parallel_tad(func, 0, lO);
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return Status::OK();
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}
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int matrixDiagPart(sd::LaunchContext * context, const NDArray* input, NDArray* output) {
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BUILD_SINGLE_SELECTOR(input->dataType(), return _matrixDiagPart, (input, output), LIBND4J_TYPES);
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}
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BUILD_SINGLE_TEMPLATE(template int _matrixDiagPart, (const NDArray* input, NDArray* output), LIBND4J_TYPES);
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}
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}
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} |