56 lines
1.7 KiB
C++
56 lines
1.7 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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// @author GS (sgazeos@gmail.com), created on 10/1/2018
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//
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#include<ops/declarable/helpers/cross.h>
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#include <helpers/ShapeUtils.h>
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#include <ops/declarable/CustomOperations.h>
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namespace nd4j {
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namespace ops {
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namespace helpers {
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void crossBatched(nd4j::LaunchContext * context, NDArray *a, NDArray *b, NDArray *o) {
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auto _a = a->reshape(a->ordering(), {-1, 3});
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auto _b = b->reshape(b->ordering(), {-1, 3});
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auto _o = o->reshape(o->ordering(), {-1, 3}, false);
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auto tadsA = _a.allTensorsAlongDimension({1});
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auto tadsB = _b.allTensorsAlongDimension({1});
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auto tadsO = _o.allTensorsAlongDimension({1});
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int tads = tadsA.size();
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auto func = PRAGMA_THREADS_FOR {
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for (auto e = start; e < stop; e++) {
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auto a_ = tadsA.at(e);
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auto b_ = tadsB.at(e);
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auto o_ = tadsO.at(e);
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helpers::cross(context, a_, b_, o_);
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}
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};
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samediff::Threads::parallel_tad(func, 0, tads);
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}
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}
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}
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} |