87 lines
2.8 KiB
C
87 lines
2.8 KiB
C
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/*******************************************************************************
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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 raver119@gmail.com
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//
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#include <ops/declarable/helpers/helpers.h>
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namespace nd4j {
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namespace ops {
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namespace helpers {
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void FORCEINLINE _cross(nd4j::LaunchContext * context, NDArray *a, NDArray *b, NDArray *o) {
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if (a->isR()) {
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auto a0 = a->e<double>(0);
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auto a1 = a->e<double>(1);
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auto a2 = a->e<double>(2);
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auto b0 = b->e<double>(0);
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auto b1 = b->e<double>(1);
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auto b2 = b->e<double>(2);
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Nd4jLong idx = 0L;
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o->p(Nd4jLong(0L), a1 * b2 - a2 * b1);
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o->p(1L, a2 * b0 - a0 * b2);
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o->p(2L, a0 * b1 - a1 * b0);
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} else {
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auto a0 = a->e<Nd4jLong>(0);
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auto a1 = a->e<Nd4jLong>(1);
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auto a2 = a->e<Nd4jLong>(2);
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auto b0 = b->e<Nd4jLong>(0);
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auto b1 = b->e<Nd4jLong>(1);
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auto b2 = b->e<Nd4jLong>(2);
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Nd4jLong idx = 0L;
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o->p(Nd4jLong(0L), a1 * b2 - a2 * b1);
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o->p(1L, a2 * b0 - a0 * b2);
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o->p(2L, a0 * b1 - a1 * b0);
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}
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}
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void FORCEINLINE _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});
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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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PRAGMA_OMP_PARALLEL_FOR_SIMD
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for (int e = 0; e < tads; 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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delete tadsA;
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delete tadsB;
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delete tadsO;
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delete _a;
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delete _b;
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delete _o;
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}
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void weightedCrossEntropyWithLogitsFunctor(nd4j::LaunchContext * context, NDArray const* targets, NDArray const* input, NDArray const* weights, NDArray* output);
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}
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}
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}
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