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Refactored fake_quant_with_min_max_vars op.

master
shugeo 2019-10-09 22:09:33 +03:00
parent 352f1eee80
commit 3c0c59ab88
1 changed files with 21 additions and 53 deletions
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74
libnd4j/include/ops/declarable/helpers/cpu/fake_quantization.cpp
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@ -74,6 +74,20 @@ namespace helpers {
} }
} }
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> template <typename T>
void fakeQuantWithMinMaxVars_(NDArray* input, NDArray* min, NDArray* max, int numBits, bool narrowed, NDArray* output) { void fakeQuantWithMinMaxVars_(NDArray* input, NDArray* min, NDArray* max, int numBits, bool narrowed, NDArray* output) {
int lowIntBound = narrowed ? 1 : 0; int lowIntBound = narrowed ? 1 : 0;
@ -81,62 +95,16 @@ namespace helpers {
const float quant_min_float = static_cast<float>(lowIntBound); const float quant_min_float = static_cast<float>(lowIntBound);
const float quant_max_float = static_cast<float>(upperIntBound); const float quant_max_float = static_cast<float>(upperIntBound);
T scale = (max->t<T>(0) - min->t<T>(0)) / (quant_max_float - quant_min_float); T nudged_min, nudged_max, scale;
const T zero_point_from_min = quant_min_float - min->e<T>(0) / scale;
const uint16_t nudged_zero_point = [zero_point_from_min, lowIntBound,
quant_min_float, upperIntBound,
quant_max_float] {
if (zero_point_from_min < quant_min_float) {
return static_cast<uint16_t>(lowIntBound);
}
if (zero_point_from_min > quant_max_float) {
return static_cast<uint16_t>(upperIntBound);
}
return static_cast<uint16_t>(roundf(zero_point_from_min));
}();
auto nudged_min = (quant_min_float - nudged_zero_point) * (scale); Nudge<T>(min->t<T>(0), max->t<T>(0), quant_min_float, quant_max_float, &scale, &nudged_min, &nudged_max);
auto nudged_max = (quant_max_float - nudged_zero_point) * (scale); WiseMinMax<T>(input, nudged_min, nudged_max, output);
//input->applyScalar(scalar::CompareAndSet, nudged_max, clamped, nullptr); //.cwiseMin(nudged_max).cwiseMax(nudged_min);
//input->applyScalar(scalar::CompareAndSet, nudged_min, clamped, nullptr); //.cwiseMin(nudged_max).cwiseMax(nudged_min);
auto wiseMax = LAMBDA_T(x, nudged_min) {
if (x < nudged_min) {
return nudged_min;
}
return x;
};
auto wiseMin = LAMBDA_T(x, nudged_max) {
if (x > nudged_max) {
return nudged_max;
}
return x;
};
auto scaleTensor(*input); // = NDArrayFactory::create(input->ordering(), input->getShapeAsVector(), input->getWorkspace());
auto clamped(*input); // = NDArrayFactory::create(input->ordering(), input->getShapeAsVector(), input->getWorkspace());
scaleTensor.assign(scale);
input->applyLambda<T>(wiseMin, &clamped);
// const auto clamped = inputs.cwiseMin(nudged_max).cwiseMax(nudged_min);
clamped.applyLambda<T>(wiseMax, output);
// const auto clamped_shifted = clamped - nudged_min;
*output -= nudged_min; *output -= nudged_min;
// auto nudgedScale = scale; (*output) /= scale;
(*output) /= scaleTensor; (*output) += T(0.5f);
// (*output) += T(0.5f); output->applyTransform(transform::Floor, nullptr, nullptr);
output->applyTransform(transform::Round, nullptr, nullptr); (*output) *= scale;
(*output) *= scaleTensor;
(*output) += nudged_min; (*output) += nudged_min;
//output->printIndexedBuffer("FAKE QUANTED");
/*
const auto nudged_scale_repl = inputs.constant(nudged_scale);
const auto clamped = inputs.cwiseMin(nudged_max).cwiseMax(nudged_min);
const auto clamped_shifted = clamped - nudged_min;
*output = (clamped_shifted / nudged_scale_repl + 0.5f).floor() *
nudged_scale_repl +
nudged_min;
*/
} }
void fakeQuantWithMinMaxVars(NDArray* input, NDArray* min, NDArray* max, int numBits, bool narrowed, NDArray* output) { void fakeQuantWithMinMaxVars(NDArray* input, NDArray* min, NDArray* max, int numBits, bool narrowed, NDArray* output) {