62 lines
2.4 KiB
C++
62 lines
2.4 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 raver119@gmail.com
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//
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#include <ops/declarable/helpers/knn.h>
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namespace nd4j {
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namespace ops {
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namespace helpers {
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template <typename T>
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void mindistance_(const void* vinput, const void *vlow, const void *vhigh, int32_t length, void *vout) {
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auto input = reinterpret_cast<const T*>(vinput);
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auto low = reinterpret_cast<const T*>(vlow);
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auto high = reinterpret_cast<const T*>(vhigh);
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auto output = reinterpret_cast<T*>(vout);
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T res = 0.0f;
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T po = 2.f;
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T o = 1.f;
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#pragma omp simd reduction(sumT:res)
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for (auto e = 0; e < length; e++) {
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T p = input[e];
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T l = low[e];
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T h = high[e];
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if (!(l <= p || h <= p)) {
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if (p < l)
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res += nd4j::math::nd4j_pow<T, T, T>((p - o), po);
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else
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res += nd4j::math::nd4j_pow<T, T, T>((p - h), po);
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}
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}
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output[0] = nd4j::math::nd4j_pow<T, T, T>(res, (T) 0.5f);
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}
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void knn_mindistance(const NDArray &input, const NDArray &lowest, const NDArray &highest, NDArray &output) {
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NDArray::preparePrimaryUse({&output}, {&input, &lowest, &highest});
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BUILD_SINGLE_SELECTOR(input.dataType(), mindistance_, (input.getBuffer(), lowest.getBuffer(), highest.getBuffer(), input.lengthOf(), output.buffer()), FLOAT_TYPES);
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NDArray::registerPrimaryUse({&output}, {&input, &lowest, &highest});
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}
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}
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}
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} |