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Merged
9prady9 merged 3 commits into from
May 20, 2020
Merged

Use same Node class for all backends #2891

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df44610
Refactor common::Node and remove cpu::jit::Node
umar456 May 18, 2020
ec42169
More clang-tidy fixes.
umar456 May 19, 2020
7c5ad89
Move Binary and Transform to src/backend/common
umar456 May 19, 2020
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2 changes: 1 addition & 1 deletion src/.clang-tidy
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@@ -1,5 +1,5 @@
---
Checks: 'clang-diagnostic-*,clang-analyzer-*,*,-fuchsia-*,-cppcoreguidelines-*,-misc-misplaced-const,-hicpp-no-array-decay,-readability-implicit-bool-conversion,bugprone-*,performance-*,modernize-*,-llvm-header-guard,-hicpp-use-auto,-modernize-use-trailing-return-type,-hicpp-uppercase-literal-suffix,-hicpp-use-nullptr,-modernize-use-nullptr,-google-runtime-int,-llvm-include-order,-google-runtime-references,-readability-magic-numbers,-readability-isolate-declaration,-hicpp-vararg,-google-readability-todo,-bugprone-macro-parentheses,-misc-unused-using-decls,-readability-else-after-return,-hicpp-avoid-c-arrays,-modernize-avoid-c-arrays'
Checks: 'clang-diagnostic-*,clang-analyzer-*,*,-fuchsia-*,-cppcoreguidelines-*,-misc-misplaced-const,-hicpp-no-array-decay,-readability-implicit-bool-conversion,bugprone-*,performance-*,modernize-*,-llvm-header-guard,-hicpp-use-auto,-modernize-use-trailing-return-type,-hicpp-uppercase-literal-suffix,-hicpp-use-nullptr,-modernize-use-nullptr,-google-runtime-int,-llvm-include-order,-google-runtime-references,-readability-magic-numbers,-readability-isolate-declaration,-hicpp-vararg,-google-readability-todo,-bugprone-macro-parentheses,-misc-unused-using-decls,-readability-else-after-return,-hicpp-avoid-c-arrays,-modernize-avoid-c-arrays,-hicpp-braces-around-statements,-hicpp-noexcept-move'
WarningsAsErrors: ''
HeaderFilterRegex: ''
AnalyzeTemporaryDtors: true
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1 change: 0 additions & 1 deletion src/api/c/CMakeLists.txt
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Expand Up @@ -118,7 +118,6 @@ target_sources(c_api_interface
${CMAKE_CURRENT_SOURCE_DIR}/morph.cpp
${CMAKE_CURRENT_SOURCE_DIR}/nearest_neighbour.cpp
${CMAKE_CURRENT_SOURCE_DIR}/norm.cpp
${CMAKE_CURRENT_SOURCE_DIR}/ops.hpp
${CMAKE_CURRENT_SOURCE_DIR}/optypes.hpp
${CMAKE_CURRENT_SOURCE_DIR}/orb.cpp
${CMAKE_CURRENT_SOURCE_DIR}/pinverse.cpp
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6 changes: 6 additions & 0 deletions src/api/c/anisotropic_diffusion.cpp
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Expand Up @@ -24,6 +24,12 @@
#include <type_traits>

using af::dim4;
using detail::arithOp;
using detail::Array;
using detail::cast;
using detail::createEmptyArray;
using detail::gradient;
using detail::reduce_all;

template<typename T>
af_array diffusion(const Array<float>& in, const float dt, const float K,
Expand Down
2 changes: 1 addition & 1 deletion src/api/c/assign.cpp
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Expand Up @@ -64,7 +64,7 @@ static void assign(Array<Tout>& out, const vector<af_seq> seqs,

isVec &= in.isVector() || in.isScalar();

for (dim_t i = static_cast<dim_t>(ndims); i < in.ndims(); i++) {
for (auto i = static_cast<dim_t>(ndims); i < in.ndims(); i++) {
oDims[i] = 1;
}

Expand Down
83 changes: 51 additions & 32 deletions src/api/c/canny.cpp
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Expand Up @@ -33,49 +33,70 @@
#include <vector>

using af::dim4;
using detail::arithOp;
using detail::Array;
using detail::cast;
using detail::convolve2;
using detail::createEmptyArray;
using detail::createHostDataArray;
using detail::createSubArray;
using detail::createValueArray;
using detail::histogram;
using detail::iota;
using detail::ireduce;
using detail::logicOp;
using detail::reduce;
using detail::reduce_all;
using detail::sobelDerivatives;
using detail::uchar;
using detail::uint;
using detail::unaryOp;
using detail::ushort;
using std::make_pair;
using std::pair;
using std::vector;

Array<float> gradientMagnitude(const Array<float>& gx, const Array<float>& gy,
const bool& isf) {
using detail::abs;
if (isf) {
Array<float> gx2 = detail::abs<float, float>(gx);
Array<float> gy2 = detail::abs<float, float>(gy);
return detail::arithOp<float, af_add_t>(gx2, gy2, gx2.dims());
Array<float> gx2 = abs<float, float>(gx);
Array<float> gy2 = abs<float, float>(gy);
return arithOp<float, af_add_t>(gx2, gy2, gx2.dims());
} else {
Array<float> gx2 = detail::arithOp<float, af_mul_t>(gx, gx, gx.dims());
Array<float> gy2 = detail::arithOp<float, af_mul_t>(gy, gy, gy.dims());
Array<float> sg =
detail::arithOp<float, af_add_t>(gx2, gy2, gx2.dims());
return detail::unaryOp<float, af_sqrt_t>(sg);
Array<float> gx2 = arithOp<float, af_mul_t>(gx, gx, gx.dims());
Array<float> gy2 = arithOp<float, af_mul_t>(gy, gy, gy.dims());
Array<float> sg = arithOp<float, af_add_t>(gx2, gy2, gx2.dims());
return unaryOp<float, af_sqrt_t>(sg);
}
}

Array<float> otsuThreshold(const Array<float>& supEdges,
const unsigned NUM_BINS, const float maxVal) {
Array<uint> hist =
detail::histogram<float, uint, false>(supEdges, NUM_BINS, 0, maxVal);
histogram<float, uint, false>(supEdges, NUM_BINS, 0, maxVal);

const af::dim4& hDims = hist.dims();
const dim4& hDims = hist.dims();

// reduce along histogram dimension i.e. 0th dimension
auto totals = reduce<af_add_t, uint, float>(hist, 0);

// tile histogram total along 0th dimension
auto ttotals = tile(totals, af::dim4(hDims[0]));
auto ttotals = tile(totals, dim4(hDims[0]));

// pixel frequency probabilities
auto probability =
arithOp<float, af_div_t>(cast<float, uint>(hist), ttotals, hDims);

std::vector<af_seq> seqBegin(4, af_span);
std::vector<af_seq> seqRest(4, af_span);
vector<af_seq> seqBegin(4, af_span);
vector<af_seq> seqRest(4, af_span);

seqBegin[0] = af_make_seq(0, static_cast<double>(hDims[0] - 1), 1);
seqRest[0] = af_make_seq(0, static_cast<double>(hDims[0] - 1), 1);

const af::dim4& iDims = supEdges.dims();
const dim4& iDims = supEdges.dims();

Array<float> sigmas = detail::createEmptyArray<float>(hDims);
Array<float> sigmas = createEmptyArray<float>(hDims);

for (unsigned b = 0; b < (NUM_BINS - 1); ++b) {
seqBegin[0].end = static_cast<double>(b);
Expand Down Expand Up @@ -109,7 +130,7 @@ Array<float> otsuThreshold(const Array<float>& supEdges,
auto op2 = arithOp<float, af_mul_t>(qL, qH, tdims);
auto sigma = arithOp<float, af_mul_t>(sqrd, op2, tdims);

std::vector<af_seq> sliceIndex(4, af_span);
vector<af_seq> sliceIndex(4, af_span);
sliceIndex[0] = {double(b), double(b), 1};

auto binRes = createSubArray<float>(sigmas, sliceIndex, false);
Expand All @@ -135,10 +156,11 @@ Array<float> normalize(const Array<float>& supEdges, const float minVal,
return arithOp<float, af_div_t>(diff, denom, supEdges.dims());
}

std::pair<Array<char>, Array<char>> computeCandidates(
const Array<float>& supEdges, const float t1, const af_canny_threshold ct,
const float t2) {
float maxVal = detail::reduce_all<af_max_t, float, float>(supEdges);
pair<Array<char>, Array<char>> computeCandidates(const Array<float>& supEdges,
const float t1,
const af_canny_threshold ct,
const float t2) {
float maxVal = reduce_all<af_max_t, float, float>(supEdges);
auto NUM_BINS = static_cast<unsigned>(maxVal);

auto lowRatio = createValueArray<float>(supEdges.dims(), t1);
Expand All @@ -155,10 +177,10 @@ std::pair<Array<char>, Array<char>> computeCandidates(
logicOp<char, af_and_t>(weak1, weak2, weak1.dims());
Array<char> strong =
logicOp<float, af_ge_t>(supEdges, T2, supEdges.dims());
return std::make_pair(strong, weak);
return make_pair(strong, weak);
};
default: {
float minVal = detail::reduce_all<af_min_t, float, float>(supEdges);
float minVal = reduce_all<af_min_t, float, float>(supEdges);
auto normG = normalize(supEdges, minVal, maxVal);
auto T2 = createValueArray<float>(supEdges.dims(), t2);
auto T1 = createValueArray<float>(supEdges.dims(), t1);
Expand All @@ -181,27 +203,24 @@ af_array cannyHelper(const Array<T>& in, const float t1,
const unsigned sw, const bool isf) {
static const vector<float> v{-0.11021f, -0.23691f, -0.30576f, -0.23691f,
-0.11021f};
Array<float> cFilter =
detail::createHostDataArray<float>(dim4(5, 1), v.data());
Array<float> rFilter =
detail::createHostDataArray<float>(dim4(1, 5), v.data());
Array<float> cFilter = createHostDataArray<float>(dim4(5, 1), v.data());
Array<float> rFilter = createHostDataArray<float>(dim4(1, 5), v.data());

// Run separable convolution to smooth the input image
Array<float> smt = detail::convolve2<float, float, false>(
cast<float, T>(in), cFilter, rFilter);
Array<float> smt =
convolve2<float, float, false>(cast<float, T>(in), cFilter, rFilter);

auto g = detail::sobelDerivatives<float, float>(smt, sw);
auto g = sobelDerivatives<float, float>(smt, sw);
Array<float> gx = g.first;
Array<float> gy = g.second;

Array<float> gmag = gradientMagnitude(gx, gy, isf);

Array<float> supEdges = detail::nonMaximumSuppression(gmag, gx, gy);
Array<float> supEdges = nonMaximumSuppression(gmag, gx, gy);

auto swpair = computeCandidates(supEdges, t1, ct, t2);

return getHandle(
detail::edgeTrackingByHysteresis(swpair.first, swpair.second));
return getHandle(edgeTrackingByHysteresis(swpair.first, swpair.second));
}

af_err af_canny(af_array* out, const af_array in, const af_canny_threshold ct,
Expand Down
22 changes: 15 additions & 7 deletions src/api/c/confidence_connected.cpp
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Expand Up @@ -24,7 +24,15 @@
#include <type_traits>

using af::dim4;
using std::array;
using common::createSpanIndex;
using detail::arithOp;
using detail::Array;
using detail::cast;
using detail::createValueArray;
using detail::reduce_all;
using detail::uchar;
using detail::uint;
using detail::ushort;
using std::conditional;
using std::is_same;
using std::sqrt;
Expand All @@ -34,12 +42,12 @@ using std::swap;
template<typename T>
Array<T> pointList(const Array<T>& in, const Array<uint>& x,
const Array<uint>& y) {
af_array xcoords = getHandle<uint>(x);
af_array ycoords = getHandle<uint>(y);
array<af_index_t, AF_MAX_DIMS> idxrs = {{{{xcoords}, false, false},
{{ycoords}, false, false},
common::createSpanIndex(),
common::createSpanIndex()}};
af_array xcoords = getHandle<uint>(x);
af_array ycoords = getHandle<uint>(y);
std::array<af_index_t, AF_MAX_DIMS> idxrs = {{{{xcoords}, false, false},
{{ycoords}, false, false},
createSpanIndex(),
createSpanIndex()}};

Array<T> retVal = detail::index(in, idxrs.data());

Expand Down
22 changes: 14 additions & 8 deletions src/api/c/corrcoef.cpp
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Expand Up @@ -22,10 +22,16 @@

#include <cmath>

using af::dim4;
using detail::arithOp;
using detail::Array;
using detail::cast;
using detail::intl;
using detail::reduce_all;
using detail::uchar;
using detail::uint;
using detail::uintl;
using detail::ushort;

template<typename Ti, typename To>
static To corrcoef(const af_array& X, const af_array& Y) {
Expand All @@ -35,16 +41,16 @@ static To corrcoef(const af_array& X, const af_array& Y) {
const dim4& dims = xIn.dims();
dim_t n = xIn.elements();

To xSum = detail::reduce_all<af_add_t, To, To>(xIn);
To ySum = detail::reduce_all<af_add_t, To, To>(yIn);
To xSum = reduce_all<af_add_t, To, To>(xIn);
To ySum = reduce_all<af_add_t, To, To>(yIn);

Array<To> xSq = detail::arithOp<To, af_mul_t>(xIn, xIn, dims);
Array<To> ySq = detail::arithOp<To, af_mul_t>(yIn, yIn, dims);
Array<To> xy = detail::arithOp<To, af_mul_t>(xIn, yIn, dims);
Array<To> xSq = arithOp<To, af_mul_t>(xIn, xIn, dims);
Array<To> ySq = arithOp<To, af_mul_t>(yIn, yIn, dims);
Array<To> xy = arithOp<To, af_mul_t>(xIn, yIn, dims);

To xSqSum = detail::reduce_all<af_add_t, To, To>(xSq);
To ySqSum = detail::reduce_all<af_add_t, To, To>(ySq);
To xySum = detail::reduce_all<af_add_t, To, To>(xy);
To xSqSum = reduce_all<af_add_t, To, To>(xSq);
To ySqSum = reduce_all<af_add_t, To, To>(ySq);
To xySum = reduce_all<af_add_t, To, To>(xy);

To result =
(n * xySum - xSum * ySum) / (std::sqrt(n * xSqSum - xSum * xSum) *
Expand Down
21 changes: 16 additions & 5 deletions src/api/c/covariance.cpp
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Expand Up @@ -23,7 +23,18 @@
#include "stats.h"

using af::dim4;
using detail::arithOp;
using detail::Array;
using detail::cast;
using detail::createValueArray;
using detail::intl;
using detail::mean;
using detail::reduce;
using detail::scalar;
using detail::uchar;
using detail::uint;
using detail::uintl;
using detail::ushort;

template<typename T, typename cType>
static af_array cov(const af_array& X, const af_array& Y, bool isbiased) {
Expand All @@ -42,12 +53,12 @@ static af_array cov(const af_array& X, const af_array& Y, bool isbiased) {
createValueArray<cType>(xDims, mean<T, weightType, cType>(_y));
Array<cType> nArr = createValueArray<cType>(xDims, scalar<cType>(N));

Array<cType> diffX = detail::arithOp<cType, af_sub_t>(xArr, xmArr, xDims);
Array<cType> diffY = detail::arithOp<cType, af_sub_t>(yArr, ymArr, xDims);
Array<cType> mulXY = detail::arithOp<cType, af_mul_t>(diffX, diffY, xDims);
Array<cType> redArr = detail::reduce<af_add_t, cType, cType>(mulXY, 0);
Array<cType> diffX = arithOp<cType, af_sub_t>(xArr, xmArr, xDims);
Array<cType> diffY = arithOp<cType, af_sub_t>(yArr, ymArr, xDims);
Array<cType> mulXY = arithOp<cType, af_mul_t>(diffX, diffY, xDims);
Array<cType> redArr = reduce<af_add_t, cType, cType>(mulXY, 0);
xDims[0] = 1;
Array<cType> result = detail::arithOp<cType, af_div_t>(redArr, nArr, xDims);
Array<cType> result = arithOp<cType, af_div_t>(redArr, nArr, xDims);

return getHandle<cType>(result);
}
Expand Down
17 changes: 15 additions & 2 deletions src/api/c/deconvolution.cpp
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Expand Up @@ -32,8 +32,21 @@
#include <vector>

using af::dim4;
using detail::arithOp;
using detail::Array;
using detail::cast;
using detail::cdouble;
using detail::cfloat;
using detail::createSubArray;
using detail::createValueArray;
using detail::logicOp;
using detail::padArrayBorders;
using detail::scalar;
using detail::select_scalar;
using detail::shift;
using detail::uchar;
using detail::uint;
using detail::ushort;
using std::array;
using std::vector;

Expand All @@ -54,7 +67,7 @@ const dim_t GREATEST_PRIME_FACTOR = 7;

template<typename T, typename CT>
Array<T> complexNorm(const Array<CT>& input) {
auto mag = abs<T, CT>(input);
auto mag = detail::abs<T, CT>(input);
auto TWOS = createValueArray(input.dims(), scalar<T>(2));
return arithOp<T, af_pow_t>(mag, TWOS, input.dims());
}
Expand Down Expand Up @@ -276,7 +289,7 @@ af_array invDeconv(const af_array in, const af_array ker, const float gamma,
auto Pc = conj(P);
auto numer = arithOp<CT, af_mul_t>(I, Pc, I.dims());
auto denom = denominator(I, P, gamma, algo);
auto absVal = abs<T, CT>(denom);
auto absVal = detail::abs<T, CT>(denom);
auto THRESH = createValueArray(I.dims(), scalar<T>(gamma));
auto cond = logicOp<T, af_ge_t>(absVal, THRESH, absVal.dims());
auto val = arithOp<CT, af_div_t>(numer, denom, numer.dims());
Expand Down
3 changes: 3 additions & 0 deletions src/api/c/det.cpp
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Expand Up @@ -24,10 +24,13 @@ using detail::Array;
using detail::cdouble;
using detail::cfloat;
using detail::createEmptyArray;
using detail::imag;
using detail::real;
using detail::scalar;

template<typename T>
T det(const af_array a) {
using namespace detail;
const Array<T> A = getArray<T>(a);

const int num = A.dims()[0];
Expand Down
4 changes: 2 additions & 2 deletions src/api/c/device.cpp
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Expand Up @@ -168,7 +168,7 @@ af_err af_get_device_count(int* nDevices) {

af_err af_get_device(int* device) {
try {
*device = getActiveDeviceId();
*device = static_cast<int>(getActiveDeviceId());
}
CATCHALL;
return AF_SUCCESS;
Expand Down Expand Up @@ -202,7 +202,7 @@ af_err af_set_device(const int device) {

af_err af_sync(const int device) {
try {
int dev = device == -1 ? getActiveDeviceId() : device;
int dev = device == -1 ? static_cast<int>(getActiveDeviceId()) : device;
detail::sync(dev);
}
CATCHALL;
Expand Down
1 change: 1 addition & 0 deletions src/api/c/exampleFunction.cpp
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Expand Up @@ -30,6 +30,7 @@
// where your new function declaration
// is written

// NOLINTNEXTLINE(google-build-using-namespace)
using namespace detail; // detail is an alias to appropriate backend
// defined in backend.hpp. You don't need to
// change this
Expand Down
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