104 lines
4.4 KiB
C++
104 lines
4.4 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 sgazeos@gmail.com
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//
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#include <ops/declarable/helpers/fake_quantization.h>
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#include <NDArrayFactory.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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static void nudge(T min, T max, int quant_min, int quant_max, T* scale, T* nudged_min, T* nudged_max) {
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T quant_max_float = static_cast<T>(quant_max);
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T quant_min_float = static_cast<T>(quant_min);
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*scale = (max - min) / (quant_max_float - quant_min_float);
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auto zero_point_from_min = quant_min_float - min / *scale;
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uint16_t const nudged_zero_point = [zero_point_from_min, quant_min, quant_max, quant_max_float, quant_min_float] {
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if (zero_point_from_min < quant_min_float) {
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return static_cast<uint16_t>(quant_min);
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}
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if (zero_point_from_min > quant_max_float) {
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return static_cast<uint16_t>(quant_max);
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}
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return nd4j::math::nd4j_round<T,uint16_t>(zero_point_from_min);
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}();
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*nudged_min = (quant_min_float - nudged_zero_point) * (*scale);
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*nudged_max = (quant_max_float - nudged_zero_point) * (*scale);
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}
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template <typename T>
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void fakeQuantWithMinMaxVarsPerChannel_(NDArray* input, NDArray* min, NDArray* max, int numBits, bool narrowed, NDArray* output) {
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int lowIntBound = narrowed ? 1 : 0;
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int upperIntBound = (1 << numBits) - 1;
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auto channels = input->sizeAt(-1);
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PRAGMA_OMP_PARALLEL_FOR
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for (auto i = 0; i < channels; i++) {
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T scale, nudged_min, nudged_max;
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nudge<T>(min->t<T>(i), max->t<T>(i), lowIntBound, upperIntBound, &scale, &nudged_min, &nudged_max);
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for (auto e = 0; e < input->lengthOf(); e += channels) {
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T val = input->t<T>(e + i);
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if ( val <= nudged_min)
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val = nudged_min;
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else if (val >= nudged_max)
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val = nudged_max;
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output->t<T>(e + i) = math::nd4j_floor<T,T>((val - nudged_min)/scale + T(0.5)) * scale + nudged_min;
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}
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}
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}
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template <typename T>
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void fakeQuantWithMinMaxVars_(NDArray* input, NDArray* min, NDArray* max, int numBits, bool narrowed, NDArray* output) {
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int lowIntBound = narrowed ? 1 : 0;
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int upperIntBound = (1 << numBits) - 1;
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T nudgedMin, nudgedMax, scale;
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nudge<T>(min->t<T>(0), max->t<T>(0), lowIntBound, upperIntBound, &scale, &nudgedMin, &nudgedMax);
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auto fakeQuantizationWithMinMax = LAMBDA_T(x, nudgedMin, nudgedMax, scale) {
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T val = x;
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if (val < nudgedMin) {
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val = nudgedMin;
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}
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else if (val > nudgedMax)
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val = nudgedMax;
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return (nd4j::math::nd4j_floor<T,T>((val - nudgedMin)/scale + T(0.5)) * scale + nudgedMin);
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};
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input->applyLambda<T>(fakeQuantizationWithMinMax, output);
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}
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void fakeQuantWithMinMaxVars(NDArray* input, NDArray* min, NDArray* max, int numBits, bool narrowed, NDArray* output) {
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BUILD_SINGLE_SELECTOR(input->dataType(), fakeQuantWithMinMaxVars_, (input, min, max, numBits, narrowed, output), FLOAT_TYPES);
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}
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void fakeQuantWithMinMaxVarsPerChannel(LaunchContext* context, NDArray* input, NDArray* min, NDArray* max, int numBits, bool narrowed, NDArray* output) {
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BUILD_SINGLE_SELECTOR(input->dataType(), fakeQuantWithMinMaxVarsPerChannel_, (input, min, max, numBits, narrowed, output), FLOAT_TYPES);
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}
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BUILD_SINGLE_TEMPLATE(template void fakeQuantWithMinMaxVars_, (NDArray* input, NDArray* min, NDArray* max, int numBits, bool narrowed, NDArray* output), FLOAT_TYPES);
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}
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}
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}
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