cavis/libnd4j/include/helpers/impl/DebugHelper.cpp

110 lines
4.9 KiB
C++

/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://www.apache.org/licenses/LICENSE-2.0.
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
* License for the specific language governing permissions and limitations
* under the License.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
//
// Created by raver119 on 20/04/18.
//
#include <helpers/DebugHelper.h>
#include <NDArray.h>
#include <NDArrayFactory.h>
#include <ops/declarable/headers/parity_ops.h>
#include <helpers/DebugInfo.h>
#include <execution/Threads.h>
namespace nd4j {
DebugInfo DebugHelper::debugStatistics(NDArray const* input) {
DebugInfo info;
DebugHelper::retrieveDebugStatistics(&info, input);
return info;
}
void
DebugHelper::retrieveDebugStatistics(DebugInfo* info, NDArray const* input) {
if (nullptr == info)
return;
info->_minValue = 0.;
info->_maxValue = -1;
info->_meanValue = 0.;
info->_stdDevValue = 1.;
info->_zeroCount = 0;
info->_positiveCount = 0;
info->_negativeCount = 0;
info->_infCount = 0;
info->_nanCount = 0;
if (input->lengthOf() == 1) { // scalar case
info->_minValue = input->e<double>(0);
info->_maxValue = info->_minValue;
info->_meanValue = info->_minValue;
info->_stdDevValue = info->_minValue;
info->_zeroCount = nd4j::math::nd4j_abs(input->e<double>(0)) > 0.00001? 0: 1;
info->_positiveCount = input->e<double>(0) > 0?1:0;
info->_negativeCount = input->e<double>(0) < 0?1:0;
info->_infCount = nd4j::math::nd4j_isinf(input->e<double>(0));
info->_nanCount = nd4j::math::nd4j_isnan(input->e<double>(0));
}
else if (input->lengthOf() > 0) {
// TO DO: here processing for all elements with array
auto _minValue = input->e<double>(0);
auto _maxValue = input->e<double>(0);
auto _meanValue = input->e<double>(0);
auto _stdDevValue = 0.; //info->_minValue;
auto _zeroCount = nd4j::math::nd4j_abs(input->e<double>(0)) > 0.00001? 0L : 1L;
auto _positiveCount = input->e<double>(0) > 0? 1L : 0L;
auto _negativeCount = input->e<double>(0) < 0? 1L : 0L;
auto _infCount = nd4j::math::nd4j_isinf(input->e<double>(0)) ? 1L : 0L;
auto _nanCount = nd4j::math::nd4j_isnan(input->e<double>(0)) ? 1L : 0L;
PRAGMA_OMP_PARALLEL_FOR_ARGS(schedule(guided) reduction(+:_nanCount,_infCount,_meanValue,_zeroCount,_positiveCount,_negativeCount) reduction(min:_minValue) reduction(max:_maxValue))
for (Nd4jLong e = 1; e < input->lengthOf(); e++) {
auto current = input->e<double>(e);
auto n = e + 1.;
// auto delta = current - _meanValue;
// auto delta2 = delta * delta;
_minValue = nd4j::math::nd4j_min(current, _minValue);
_maxValue = nd4j::math::nd4j_max(current, _maxValue);
_meanValue += current;
//_meanValue += delta / n; // this is a perfect formula but not working with omp in this notation
//_stdDevValue += delta2 * e / n;
_zeroCount += nd4j::math::nd4j_abs(current) > 0.00001 ? 0 : 1;
_positiveCount += current > 0 ? 1 : 0;
_negativeCount += current < 0 ? 1 : 0;
_infCount += nd4j::math::nd4j_isinf(current);
_nanCount += nd4j::math::nd4j_isnan(current);
}
*info = {_minValue, _maxValue, _meanValue / input->lengthOf(), _stdDevValue, _zeroCount, _positiveCount, _negativeCount, _infCount, _nanCount};
_stdDevValue = 0; //math::nd4j_sqrt<double, double>(info->_stdDevValue / (input->lengthOf() - 1));
auto func = PRAGMA_REDUCE_DOUBLE {
auto _stdDevValue = 0.0;
for (auto e = start; e < stop; e++) {
double current = input->e<double>(e);
_stdDevValue += (info->_meanValue - current) * (info->_meanValue - current); //info->_minValue;
}
return _stdDevValue;
};
_stdDevValue = samediff::Threads::parallel_double(func, LAMBDA_AD { return _old + _new; }, 0, input->lengthOf());
info->_stdDevValue = math::nd4j_sqrt<double, double>(_stdDevValue / input->lengthOf());
}
// else - no statistics for empty
}
}