122 lines
5.1 KiB
C++
122 lines
5.1 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
|
|
******************************************************************************/
|
|
|
|
//
|
|
// @author sgazeos@gmail.com
|
|
//
|
|
|
|
#include <ops/declarable/helpers/fake_quantization.h>
|
|
#include <NDArrayFactory.h>
|
|
|
|
namespace nd4j {
|
|
namespace ops {
|
|
namespace helpers {
|
|
|
|
template <typename T>
|
|
static void Nudge(T min, T max, T quant_min, T quant_max, T* scale, T* nudged_min, T* nudged_max) {
|
|
*scale = (max - min) / (quant_max - quant_min);
|
|
auto zero_point_from_min = quant_min - min / *scale;
|
|
uint16_t const nudged_zero_point = [zero_point_from_min, quant_min, quant_max] {
|
|
if (zero_point_from_min < quant_min) {
|
|
return static_cast<uint16_t>(quant_min);
|
|
}
|
|
if (zero_point_from_min > quant_max) {
|
|
return static_cast<uint16_t>(quant_max);
|
|
}
|
|
return nd4j::math::nd4j_round<T,uint16_t>(zero_point_from_min);
|
|
}();
|
|
*nudged_min = (quant_min - nudged_zero_point) * (*scale);
|
|
*nudged_max = (quant_max - nudged_zero_point) * (*scale);
|
|
}
|
|
|
|
template <typename T>
|
|
void fakeQuantWithMinMaxVarsPerChannel_(NDArray* input, NDArray* min, NDArray* max, int numBits, bool narrowed, NDArray* output) {
|
|
int lowIntBound = narrowed ? 1 : 0;
|
|
int upperIntBound = 1 << numBits - 1;
|
|
|
|
const float quant_min_float = static_cast<float>(lowIntBound);
|
|
const float quant_max_float = static_cast<float>(upperIntBound);
|
|
// auto scaleTensor(*input); // = NDArrayFactory::create(input->ordering(), input->getShapeAsVector(), input->getWorkspace());
|
|
auto clamped(*input); // = NDArrayFactory::create(input->ordering(), input->getShapeAsVector(), input->getWorkspace());
|
|
for (auto i = 0; i < min->lengthOf(); i++) {
|
|
T scale, nudged_min, nudged_max;
|
|
Nudge<T>(min->t<T>(i), max->t<T>(i), quant_min_float, quant_max_float, &scale, &nudged_min, &nudged_max);
|
|
auto wiseMinMax = LAMBDA_T(x, nudged_min, nudged_max) {
|
|
if (x < nudged_min) {
|
|
return nudged_min;
|
|
}
|
|
else if (x > nudged_max)
|
|
return nudged_max;
|
|
return x;
|
|
};
|
|
// scaleTensor.assign(scale);
|
|
input->applyLambda<T>(wiseMinMax, &clamped);
|
|
clamped -= nudged_min;
|
|
// auto nudgedScale = scale;
|
|
clamped /= scale;
|
|
clamped += T(0.5f);
|
|
clamped.applyTransform(transform::Floor, output, nullptr);
|
|
(*output) *= scale;
|
|
(*output) += nudged_min;
|
|
}
|
|
}
|
|
|
|
template <typename T>
|
|
static void WiseMinMax(NDArray* input, T min, T max, NDArray* output) {
|
|
auto wiseMinMax = LAMBDA_T(x, min, max) {
|
|
if (x < min) {
|
|
return min;
|
|
}
|
|
else if (x > max)
|
|
return max;
|
|
return x;
|
|
};
|
|
|
|
input->applyLambda<T>(wiseMinMax, output);
|
|
}
|
|
|
|
template <typename T>
|
|
void fakeQuantWithMinMaxVars_(NDArray* input, NDArray* min, NDArray* max, int numBits, bool narrowed, NDArray* output) {
|
|
int lowIntBound = narrowed ? 1 : 0;
|
|
int upperIntBound = 1 << numBits - 1;
|
|
|
|
const float quant_min_float = static_cast<float>(lowIntBound);
|
|
const float quant_max_float = static_cast<float>(upperIntBound);
|
|
T nudged_min, nudged_max, scale;
|
|
|
|
Nudge<T>(min->t<T>(0), max->t<T>(0), quant_min_float, quant_max_float, &scale, &nudged_min, &nudged_max);
|
|
WiseMinMax<T>(input, nudged_min, nudged_max, output);
|
|
*output -= nudged_min;
|
|
(*output) /= scale;
|
|
(*output) += T(0.5f);
|
|
output->applyTransform(transform::Floor, nullptr, nullptr);
|
|
(*output) *= scale;
|
|
(*output) += nudged_min;
|
|
}
|
|
|
|
void fakeQuantWithMinMaxVars(NDArray* input, NDArray* min, NDArray* max, int numBits, bool narrowed, NDArray* output) {
|
|
BUILD_SINGLE_SELECTOR(input->dataType(), fakeQuantWithMinMaxVars_, (input, min, max, numBits, narrowed, output), FLOAT_TYPES);
|
|
}
|
|
void fakeQuantWithMinMaxVarsPerChannel(NDArray* input, NDArray* min, NDArray* max, int numBits, bool narrowed, NDArray* output) {
|
|
BUILD_SINGLE_SELECTOR(input->dataType(), fakeQuantWithMinMaxVarsPerChannel_, (input, min, max, numBits, narrowed, output), FLOAT_TYPES);
|
|
}
|
|
|
|
BUILD_SINGLE_TEMPLATE(template void fakeQuantWithMinMaxVars_, (NDArray* input, NDArray* min, NDArray* max, int numBits, bool narrowed, NDArray* output), FLOAT_TYPES);
|
|
|
|
}
|
|
}
|
|
}
|