64 lines
2.2 KiB
C++
64 lines
2.2 KiB
C++
/*******************************************************************************
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* Copyright (c) 2015-2018 Skymind, Inc.
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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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* 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 to use with batched tensor by GS <sgazeos@gmail.com> 3/21/2018
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//
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#include <ops/declarable/CustomOperations.h>
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#include <ops/declarable/helpers/matrix_diag.h>
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namespace nd4j {
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namespace ops {
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CUSTOM_OP_IMPL(matrix_diag, 1, 1, false, 0, 0) {
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auto input = INPUT_VARIABLE(0);
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auto output = OUTPUT_VARIABLE(0);
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REQUIRE_TRUE(!input->isScalar(), 0, "CUSTOM_OP matrix_diag: input array must be at list a vector, but scalar was given!");
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output->nullify();
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return helpers::matrixDiag(block.launchContext(), input, output);
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}
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DECLARE_SHAPE_FN(matrix_diag) {
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Nd4jLong* outShapeInfo = nullptr;
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auto in = inputShape->at(0);
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int inRank = shape::rank(in);
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int outRank = inRank + 1;
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auto lastDimension = shape::sizeAt(in, -1);
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ALLOCATE(outShapeInfo, block.getWorkspace(), shape::shapeInfoLength(outRank), Nd4jLong);
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outShapeInfo[0] = outRank;
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for(int i = 0; i < inRank; ++i)
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outShapeInfo[i + 1] = shape::sizeAt(in, i);
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outShapeInfo[outRank] = lastDimension;
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ShapeUtils::updateStridesAndType(outShapeInfo, in, shape::order(in));
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return SHAPELIST(CONSTANT(outShapeInfo));
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}
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DECLARE_TYPES(matrix_diag) {
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getOpDescriptor()
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->setAllowedInputTypes(nd4j::DataType::ANY)
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->setSameMode(true);
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}
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}
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}
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