arrayfire/test/fftconvolve.cpp at master · arrayfire/arrayfire · GitHub

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/*******************************************************

* This file is distributed under 3-clause BSD license.

* The complete license agreement can be obtained at:

* http://arrayfire.com/licenses/BSD-3-Clause

********************************************************/

#include <arrayfire.h>

#include <gtest/gtest.h>

#include <testHelpers.hpp>

#include <af/dim4.hpp>

#include <af/traits.hpp>

#include <string>

#include <vector>

using af::array;

using af::cdouble;

using af::cfloat;

using af::dim4;

using af::dtype_traits;

using af::randu;

using std::abs;

using std::endl;

using std::string;

using std::vector;

template<typename T>

class FFTConvolve : public ::testing::Test {

public:

virtual void SetUp() {}

};

template<typename T>

class FFTConvolveLarge : public ::testing::Test {

public:

virtual void SetUp() {}

};

// create a list of types to be tested

typedef ::testing::Types<cfloat, cdouble, float, double, int, uint, char, schar,

uchar, intl, uintl>

TestTypes;

typedef ::testing::Types<float, double> TestTypesLarge;

// register the type list

TYPED_TEST_SUITE(FFTConvolve, TestTypes);

TYPED_TEST_SUITE(FFTConvolveLarge, TestTypesLarge);

template<typename T, int baseDim>

void fftconvolveTest(string pTestFile, bool expand) {

SUPPORTED_TYPE_CHECK(T);

vector<dim4> numDims;

vector<vector<T>> in;

vector<vector<T>> tests;

readTests<T, T, int>(pTestFile, numDims, in, tests);

dim4 sDims = numDims[0];

dim4 fDims = numDims[1];

af_array signal = 0;

af_array filter = 0;

af_array outArray = 0;

af_dtype in_type = (af_dtype)dtype_traits<T>::af_type;

ASSERT_SUCCESS(af_create_array(&signal, &(in[0].front()), sDims.ndims(),

sDims.get(), in_type));

ASSERT_SUCCESS(af_create_array(&filter, &(in[1].front()), fDims.ndims(),

fDims.get(), in_type));

af_conv_mode mode = expand ? AF_CONV_EXPAND : AF_CONV_DEFAULT;

switch (baseDim) {

case 1:

ASSERT_SUCCESS(af_fft_convolve1(&outArray, signal, filter, mode));

break;

case 2:

ASSERT_SUCCESS(af_fft_convolve2(&outArray, signal, filter, mode));

break;

case 3:

ASSERT_SUCCESS(af_fft_convolve3(&outArray, signal, filter, mode));

break;

}

vector<T> currGoldBar = tests[0];

size_t nElems = currGoldBar.size();

dim_t out_elems = 0;

ASSERT_SUCCESS(af_get_elements(&out_elems, outArray));

ASSERT_EQ(nElems, (size_t)out_elems);

vector<T> outData(nElems);

ASSERT_SUCCESS(af_get_data_ptr((void*)&outData.front(), outArray));

for (size_t elIter = 0; elIter < nElems; ++elIter) {

ASSERT_NEAR(real(currGoldBar[elIter]), real(outData[elIter]), 1e-2)

<< "at: " << elIter << endl;

}

ASSERT_SUCCESS(af_release_array(outArray));

ASSERT_SUCCESS(af_release_array(signal));

ASSERT_SUCCESS(af_release_array(filter));

}

template<typename T, int baseDim>

void fftconvolveTestLarge(int sDim, int fDim, int sBatch, int fBatch,

bool expand) {

SUPPORTED_TYPE_CHECK(T);

using af::seq;

int outDim = sDim + fDim - 1;

int fftDim = (int)pow(2, ceil(log2(outDim)));

int sd[4], fd[4];

for (int k = 0; k < 4; k++) {

if (k < baseDim) {

sd[k] = sDim;

fd[k] = fDim;

} else if (k == baseDim) {

sd[k] = sBatch;

fd[k] = fBatch;

} else {

sd[k] = 1;

fd[k] = 1;

}

const dim4 signalDims(sd[0], sd[1], sd[2], sd[3]);

const dim4 filterDims(fd[0], fd[1], fd[2], fd[3]);

array signal = randu(signalDims, (af_dtype)dtype_traits<T>::af_type);

array filter = randu(filterDims, (af_dtype)dtype_traits<T>::af_type);

array out =

fftConvolve(signal, filter, expand ? AF_CONV_EXPAND : AF_CONV_DEFAULT);

array gold;

switch (baseDim) {

case 1:

gold = real(ifft(fft(signal, fftDim) * fft(filter, fftDim)));

break;

case 2:

gold = real(ifft2(fft2(signal, fftDim, fftDim) *

fft2(filter, fftDim, fftDim)));

break;

case 3:

gold = real(ifft3(fft3(signal, fftDim, fftDim, fftDim) *

fft3(filter, fftDim, fftDim, fftDim)));

break;

default: ASSERT_LT(baseDim, 4);

}

int cropMin = 0, cropMax = 0;

if (expand) {

cropMin = 0;

cropMax = outDim - 1;

} else {

cropMin = fDim / 2;

cropMax = outDim - fDim / 2 - 1;

}

switch (baseDim) {

case 1: gold = gold(seq(cropMin, cropMax)); break;

case 2:

gold = gold(seq(cropMin, cropMax), seq(cropMin, cropMax));

break;

case 3:

gold = gold(seq(cropMin, cropMax), seq(cropMin, cropMax),

seq(cropMin, cropMax));

break;

}

ASSERT_ARRAYS_NEAR(gold, out, 5e-2);

}

TYPED_TEST(FFTConvolveLarge, VectorLargeSignalSmallFilter) {

fftconvolveTestLarge<TypeParam, 1>(32768, 25, 1, 1, true);

}

TYPED_TEST(FFTConvolveLarge, VectorLargeSignalLargeFilter) {

fftconvolveTestLarge<TypeParam, 1>(32768, 4095, 1, 1, true);

}

TYPED_TEST(FFTConvolveLarge, SameVectorLargeSignalSmallFilter) {

fftconvolveTestLarge<TypeParam, 1>(32768, 25, 1, 1, false);

}

TYPED_TEST(FFTConvolveLarge, SameVectorLargeSignalLargeFilter) {

fftconvolveTestLarge<TypeParam, 1>(32768, 4095, 1, 1, false);

}

TYPED_TEST(FFTConvolveLarge, RectangleLargeSignalSmallFilter) {

fftconvolveTestLarge<TypeParam, 2>(1024, 5, 1, 1, true);

}

TYPED_TEST(FFTConvolveLarge, RectangleLargeSignalLargeFilter) {

fftconvolveTestLarge<TypeParam, 2>(1024, 511, 1, 1, true);

}

TYPED_TEST(FFTConvolveLarge, SameRectangleLargeSignalSmallFilter) {

fftconvolveTestLarge<TypeParam, 2>(1024, 5, 1, 1, false);

}

TYPED_TEST(FFTConvolveLarge, SameRectangleLargeSignalLargeFilter) {

fftconvolveTestLarge<TypeParam, 2>(1024, 511, 1, 1, false);

}

TYPED_TEST(FFTConvolveLarge, CuboidLargeSignalSmallFilter) {

fftconvolveTestLarge<TypeParam, 3>(64, 5, 1, 1, true);

}

TYPED_TEST(FFTConvolveLarge, CuboidLargeSignalLargeFilter) {

fftconvolveTestLarge<TypeParam, 3>(64, 31, 1, 1, true);

}

TYPED_TEST(FFTConvolveLarge, SameCuboidLargeSignalSmallFilter) {

fftconvolveTestLarge<TypeParam, 3>(64, 5, 1, 1, false);

}

TYPED_TEST(FFTConvolveLarge, SameCuboidLargeSignalLargeFilter) {

fftconvolveTestLarge<TypeParam, 2>(64, 31, 1, 1, false);

}

TYPED_TEST(FFTConvolve, Vector) {

fftconvolveTest<TypeParam, 1>(string(TEST_DIR "/convolve/vector.test"),

true);

}

TYPED_TEST(FFTConvolve, Rectangle) {

fftconvolveTest<TypeParam, 2>(string(TEST_DIR "/convolve/rectangle.test"),

true);

}

TYPED_TEST(FFTConvolve, Cuboid) {

fftconvolveTest<TypeParam, 3>(string(TEST_DIR "/convolve/cuboid.test"),

true);

}

TYPED_TEST(FFTConvolve, Vector_Many2One) {

fftconvolveTest<TypeParam, 1>(

string(TEST_DIR "/convolve/vector_many2one.test"), true);

}

TYPED_TEST(FFTConvolve, Rectangle_Many2One) {

fftconvolveTest<TypeParam, 2>(

string(TEST_DIR "/convolve/rectangle_many2one.test"), true);

}

TYPED_TEST(FFTConvolve, Cuboid_Many2One) {

fftconvolveTest<TypeParam, 3>(

string(TEST_DIR "/convolve/cuboid_many2one.test"), true);

}

TYPED_TEST(FFTConvolve, Vector_Many2Many) {

fftconvolveTest<TypeParam, 1>(

string(TEST_DIR "/convolve/vector_many2many.test"), true);

}

TYPED_TEST(FFTConvolve, Rectangle_Many2Many) {

fftconvolveTest<TypeParam, 2>(

string(TEST_DIR "/convolve/rectangle_many2many.test"), true);

}

TYPED_TEST(FFTConvolve, Cuboid_Many2Many) {

fftconvolveTest<TypeParam, 3>(

string(TEST_DIR "/convolve/cuboid_many2many.test"), true);

}

TYPED_TEST(FFTConvolve, Vector_One2Many) {

fftconvolveTest<TypeParam, 1>(

string(TEST_DIR "/convolve/vector_one2many.test"), true);

}

TYPED_TEST(FFTConvolve, Rectangle_One2Many) {

fftconvolveTest<TypeParam, 2>(

string(TEST_DIR "/convolve/rectangle_one2many.test"), true);

}

TYPED_TEST(FFTConvolve, Cuboid_One2Many) {

fftconvolveTest<TypeParam, 3>(

string(TEST_DIR "/convolve/cuboid_one2many.test"), true);

}

TYPED_TEST(FFTConvolve, Same_Vector) {

fftconvolveTest<TypeParam, 1>(string(TEST_DIR "/convolve/vector_same.test"),

false);

}

TYPED_TEST(FFTConvolve, Same_Rectangle) {

fftconvolveTest<TypeParam, 2>(

string(TEST_DIR "/convolve/rectangle_same.test"), false);

}

TYPED_TEST(FFTConvolve, Same_Cuboid) {

fftconvolveTest<TypeParam, 3>(string(TEST_DIR "/convolve/cuboid_same.test"),

false);

}

TYPED_TEST(FFTConvolve, Same_Vector_Many2One) {

fftconvolveTest<TypeParam, 1>(

string(TEST_DIR "/convolve/vector_same_many2one.test"), false);

}

TYPED_TEST(FFTConvolve, Same_Rectangle_Many2One) {

fftconvolveTest<TypeParam, 2>(

string(TEST_DIR "/convolve/rectangle_same_many2one.test"), false);

}

TYPED_TEST(FFTConvolve, Same_Cuboid_Many2One) {

fftconvolveTest<TypeParam, 3>(

string(TEST_DIR "/convolve/cuboid_same_many2one.test"), false);

}

TYPED_TEST(FFTConvolve, Same_Vector_Many2Many) {

fftconvolveTest<TypeParam, 1>(

string(TEST_DIR "/convolve/vector_same_many2many.test"), false);

}

TYPED_TEST(FFTConvolve, Same_Rectangle_Many2Many) {

fftconvolveTest<TypeParam, 2>(

string(TEST_DIR "/convolve/rectangle_same_many2many.test"), false);

}

TYPED_TEST(FFTConvolve, Same_Cuboid_Many2Many) {

fftconvolveTest<TypeParam, 3>(

string(TEST_DIR "/convolve/cuboid_same_many2many.test"), false);

}

TYPED_TEST(FFTConvolve, Same_Vector_One2Many) {

fftconvolveTest<TypeParam, 1>(

string(TEST_DIR "/convolve/vector_same_one2many.test"), false);

}

TYPED_TEST(FFTConvolve, Same_Rectangle_One2Many) {

fftconvolveTest<TypeParam, 2>(

string(TEST_DIR "/convolve/rectangle_same_one2many.test"), false);

}

TYPED_TEST(FFTConvolve, Same_Cuboid_One2Many) {

fftconvolveTest<TypeParam, 3>(

string(TEST_DIR "/convolve/cuboid_same_one2many.test"), false);

}

TEST(FFTConvolve1, CPP) {

vector<dim4> numDims;

vector<vector<float>> in;

vector<vector<float>> tests;

readTests<float, float, int>(string(TEST_DIR "/convolve/vector.test"),

numDims, in, tests);

//![ex_image_convolve1]

// vector<dim4> numDims;

// vector<vector<float> > in;

array signal(numDims[0], &(in[0].front()));

// signal dims = [32 1 1 1]

array filter(numDims[1], &(in[1].front()));

// filter dims = [4 1 1 1]

array output = fftConvolve1(signal, filter, AF_CONV_EXPAND);

// output dims = [32 1 1 1] - same as input since expand(3rd argument is

// false) None of the dimensions > 1 has lenght > 1, so no batch mode is

// activated.

//![ex_image_convolve1]

vector<float> currGoldBar = tests[0];

size_t nElems = output.elements();

vector<float> outData(nElems);

output.host(&outData.front());

for (size_t elIter = 0; elIter < nElems; ++elIter) {

ASSERT_NEAR(currGoldBar[elIter], outData[elIter], 1e-2)

<< "at: " << elIter << endl;

}

TEST(FFTConvolve2, CPP) {

vector<dim4> numDims;

vector<vector<float>> in;

vector<vector<float>> tests;

readTests<float, float, int>(

string(TEST_DIR "/convolve/rectangle_one2many.test"), numDims, in,

tests);

//![ex_image_convolve2]

// vector<dim4> numDims;

// vector<vector<float> > in;

array signal(numDims[0], &(in[0].front()));

// signal dims = [15 17 1 1]

array filter(numDims[1], &(in[1].front()));

// filter dims = [5 5 2 1]

array output = fftConvolve2(signal, filter, AF_CONV_EXPAND);

// output dims = [15 17 1 1] - same as input since expand(3rd argument is

// false) however, notice that the 3rd dimension of filter is > 1. So, one

// to many batch mode will be activated automatically where the 2d input

// signal is convolved with each 2d filter and the result will written

// corresponding slice in the output 3d array

//![ex_image_convolve2]

vector<float> currGoldBar = tests[0];

size_t nElems = output.elements();

vector<float> outData(nElems);

output.host(&outData.front());

for (size_t elIter = 0; elIter < nElems; ++elIter) {

ASSERT_NEAR(currGoldBar[elIter], outData[elIter], 1e-2)

<< "at: " << elIter << endl;

}

TEST(FFTConvolve3, CPP) {

vector<dim4> numDims;

vector<vector<float>> in;

vector<vector<float>> tests;

readTests<float, float, int>(

string(TEST_DIR "/convolve/cuboid_many2many.test"), numDims, in, tests);

//![ex_image_convolve3]

// vector<dim4> numDims;

// vector<vector<float> > in;

array signal(numDims[0], &(in[0].front()));

// signal dims = [10 11 2 2]

array filter(numDims[1], &(in[1].front()));

// filter dims = [4 2 3 2]

array output = fftConvolve3(signal, filter, AF_CONV_EXPAND);

// output dims = [10 11 2 2] - same as input since expand(3rd argument is

// false) however, notice that the 4th dimension is > 1 for both signal and

// the filter, therefore many to many batch mode will be activated where

// each 3d signal is convolved with the corresponding 3d filter

//![ex_image_convolve3]

vector<float> currGoldBar = tests[0];

size_t nElems = output.elements();

vector<float> outData(nElems);

output.host(&outData.front());

for (size_t elIter = 0; elIter < nElems; ++elIter) {

ASSERT_NEAR(currGoldBar[elIter], outData[elIter], 1e-2)

<< "at: " << elIter << endl;

}

TEST(FFTConvolve, Docs_Unified_Wrapper) {

// This unit test doesn't necessarily need to function

// accuracy as convolve is merely a wrapper to

// convolve[1|2|3]

using af::constant;

using af::convolve;

//![ex_image_convolve_1d]

array a = randu(10);

// af_print(a);

// a [10 1 1 1] = 0.0000 0.1315 0.7556 0.4587 0.5328 0.2190 0.0470 0.6789

// 0.6793 0.9347

array b = randu(4);

// af_print(b);

// b [4 1 1 1] = 0.3835 0.5194 0.8310 0.0346

array c = convolve(a, b);

// af_print(c);

// c [10 1 1 1] = 0.3581 0.6777 1.0750 0.7679 0.5903 0.4851 0.6598

// 1.2770 1.0734 0.8002

//![ex_image_convolve_1d]

//![ex_image_convolve_2d]

array d = constant(0.5, 5, 5);

// af_print(d);

// d [5 5 1 1]

// 0.5000 0.5000 0.5000 0.5000 0.5000

array e = constant(1, 2, 2);

// af_print(e);

// e [2 2 1 1]

// 1.0000 1.0000

array f = fftConvolve(d, e);

// af_print(f);

// f [5 5 1 1]

// 2.0000 2.0000 2.0000 2.0000 1.0000

// 1.0000 1.0000 1.0000 1.0000 0.5000

//![ex_image_convolve_2d]

//![ex_image_convolve_3d]

array g = constant(1, 4, 4, 4);

// af_print(g);

// g [4 4 4 1]

// 1.0000 1.0000 1.0000 1.0000

array h = constant(0.5, 2, 2, 2);

// af_print(h);

// h [2 2 2 1]

// 0.5000 0.5000

array i = fftConvolve(g, h);

// af_print(i);

// i [4 4 4 1]

// 4.0000 4.0000 4.0000 2.0000

// 2.0000 2.0000 2.0000 1.0000

// 4.0000 4.0000 4.0000 2.0000

// 2.0000 2.0000 2.0000 1.0000

// 4.0000 4.0000 4.0000 2.0000

// 2.0000 2.0000 2.0000 1.0000

// 1.0000 1.0000 1.0000 0.5000

//![ex_image_convolve_3d]

}

using namespace af;

TEST(GFOR, fftConvolve2_MO) {

array A = randu(5, 5, 3);

array B = randu(5, 5, 3);

array K = randu(3, 3);

gfor(seq ii, 3) { B(span, span, ii) = fftConvolve2(A(span, span, ii), K); }

for (int ii = 0; ii < 3; ii++) {

array c_ii = fftConvolve2(A(span, span, ii), K);

array b_ii = B(span, span, ii);

ASSERT_EQ(max<double>(abs(c_ii - b_ii)) < 1E-5, true);

}

TEST(GFOR, fftConvolve2_OM) {

array A = randu(5, 5);

array B = randu(5, 5, 3);

array K = randu(3, 3, 3);

gfor(seq ii, 3) { B(span, span, ii) = fftConvolve2(A, K(span, span, ii)); }

for (int ii = 0; ii < 3; ii++) {

array c_ii = fftConvolve2(A, K(span, span, ii));

array b_ii = B(span, span, ii);

ASSERT_EQ(max<double>(abs(c_ii - b_ii)) < 1E-5, true);

}

TEST(GFOR, fftConvolve2_MM) {

array A = randu(5, 5, 3);

array B = randu(5, 5, 3);

array K = randu(3, 3, 3);

gfor(seq ii, 3) {

B(span, span, ii) = fftConvolve2(A(span, span, ii), K(span, span, ii));

}

for (int ii = 0; ii < 3; ii++) {

array c_ii = fftConvolve2(A(span, span, ii), K(span, span, ii));

array b_ii = B(span, span, ii);

ASSERT_EQ(max<double>(abs(c_ii - b_ii)) < 1E-5, true);

}

TEST(Padding, fftConvolve2) {

for (int n = 5; n < 32; n++) {

array a = randu(n, n);

array b = randu(5, 5);

array c = fftConvolve2(a, b);

array d = convolve2(a, b, AF_CONV_DEFAULT, AF_CONV_SPATIAL);

ASSERT_EQ(max<double>(abs(c - d)) < 1E-5, true);

}

TEST(FFTConvolve1, Interleaved) {

array a = randu(100, 1, 2);

array b = randu(20, 3);

array c = fftConvolve1(a, b);

for (int ii = 0; ii < 2; ii++) {

array c_ii = c(span, span, ii);

array d = fftConvolve1(a(span, 0, ii), b);

ASSERT_EQ(max<double>(abs(c_ii - d)) < 1E-5, true);

}

TEST(FFTConvolve2, Interleaved) {

array a = randu(100, 100, 2);

array b = randu(5, 5, 1, 3);

array c = fftConvolve2(a, b);

for (int ii = 0; ii < 3; ii++) {

array c_ii = c(span, span, span, ii);

array d = fftConvolve2(a, b(span, span, 0, ii));

ASSERT_EQ(max<double>(abs(c_ii - d)) < 1E-5, true);

}

TEST(FFTConvolve2, Interleaved2) {

array a = randu(100, 100, 2);

array b = randu(5, 5, 2, 3);

array c = fftConvolve2(a, b);

for (int ii = 0; ii < 3; ii++) {

array c_ii = c(span, span, span, ii);

array d = fftConvolve2(a, b(span, span, span, ii));

ASSERT_EQ(max<double>(abs(c_ii - d)) < 1E-5, true);

}

arrayfire/test/fftconvolve.cpp at master · arrayfire/arrayfire · GitHub

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