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Implemented fake_quant_with_min_max_per_channel helper for cpu platform. The first approach.

master
shugeo 2019-10-09 21:39:59 +03:00
parent d0cbd33b0e
commit 352f1eee80
2 changed files with 73 additions and 21 deletions
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55
libnd4j/include/ops/declarable/helpers/cpu/fake_quantization.cpp
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@ -25,6 +25,55 @@ 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>
void fakeQuantWithMinMaxVars_(NDArray* input, NDArray* min, NDArray* max, int numBits, bool narrowed, NDArray* output) {
int lowIntBound = narrowed ? 1 : 0;
@ -73,8 +122,8 @@ namespace helpers {
*output -= nudged_min;
// auto nudgedScale = scale;
(*output) /= scaleTensor;
(*output) += T(0.5f);
output->applyTransform(transform::Floor, nullptr, nullptr);
// (*output) += T(0.5f);
output->applyTransform(transform::Round, nullptr, nullptr);
(*output) *= scaleTensor;
(*output) += nudged_min;
//output->printIndexedBuffer("FAKE QUANTED");
@ -94,7 +143,7 @@ namespace helpers {
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(), fakeQuantWithMinMaxVars_, (input, min, max, numBits, narrowed, output), FLOAT_TYPES);
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);

19
libnd4j/tests_cpu/layers_tests/DeclarableOpsTests10.cpp
View File

@ -2159,8 +2159,8 @@ TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_3) {
NDArray x = NDArrayFactory::create<double>('c', {1,2,3,1}, {-63.80, -63.75, -63.4, -63.5, 0.0, 0.1});
NDArray exp = NDArrayFactory::create<double>('c', {1,2,3,1}, {-63.75, -63.75, -63.251953, -63.251953, 0.0, 0.0});
NDArray min = NDArrayFactory::create<double>(-63.65);
NDArray max = NDArrayFactory::create<double>(0.1);
NDArray min = NDArrayFactory::create<double>('c', {1},{-63.65});
NDArray max = NDArrayFactory::create<double>('c', {1}, {0.1});
nd4j::ops::fake_quant_with_min_max_vars_per_channel op;
auto results = op.execute({&x, &min, &max}, {}, {});
@ -2178,8 +2178,8 @@ TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_3) {
////////////////////////////////////////////////////////////////////
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_4) {
NDArray x = NDArrayFactory::create<double>('c', {2,4,5,3});
NDArray exp = NDArrayFactory::create<double>('c', {2,4,5,3},
NDArray x = NDArrayFactory::create<float>('c', {2,4,5,3});
NDArray exp = NDArrayFactory::create<float>('c', {2,4,5,3},
{1.0588236, 1.9607843, 3.019608, 4.0588236, 5.098039, 6.039216, 7.0588236, 8.039216, 9.058824,
10.058824, 10.980392, 12.078432, 13.058824, 13.921569, 15.09804, 16.058825, 17.058825, 18.117647,
19.058825, 20., 21.137257, 22.058825, 22.941177, 23.882355, 25.058825, 26.078432, 26.901962,
@ -2194,16 +2194,19 @@ TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_4) {
45., 50., 70., 45., 50., 70., 45., 50., 70.,
45., 50., 70., 45., 50., 70., 45., 50., 70.,
45., 50., 70.});
NDArray min = NDArrayFactory::create<double>({20., 20., 20.});
NDArray max = NDArrayFactory::create<double>({65., 70., 90.});
NDArray min = NDArrayFactory::create<float>({20., 20., 20.});
NDArray max = NDArrayFactory::create<float>({65., 70., 90.});
x.linspace(1.);
nd4j::ops::fake_quant_with_min_max_vars_per_channel op;
auto results = op.execute({&x, &min, &max}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, results->status());
auto result = results->at(0);
// result->printIndexedBuffer("Quantized2");
result->printBuffer("Quantized per channels 4");
exp.printBuffer("Quantized per channest E");
auto diff = *result - exp;
diff.printIndexedBuffer("Difference");
ASSERT_TRUE(exp.isSameShapeStrict(result));
ASSERT_TRUE(exp.equalsTo(result));