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Cleanup PR 4127 #4153

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merged 6 commits into from
Feb 6, 2018
Merged

Cleanup PR 4127 #4153

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f02376c
Cleanup
Feb 5, 2018
c5620ff
Works now
Feb 5, 2018
6b4d881
Formatting, dont expect to pass style checker
Feb 5, 2018
570a8a2
Revert "Formatting, dont expect to pass style checker"
Feb 5, 2018
386a4b0
Revert "Revert "Formatting, dont expect to pass style checker""
Feb 5, 2018
1416cd0
Reverted changed to scripts.
Feb 5, 2018
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6 changes: 3 additions & 3 deletions scripts/check_format.sh
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Original file line number Diff line number Diff line change
Expand Up @@ -41,7 +41,7 @@ function check_shogun_style {
fi
done

RESULT_OUTPUT="$(git clang-format-3.8 --commit $BASE_COMMIT --diff --binary `which clang-format-3.8` $LIST)"
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need to get the Docker image fixed for this on travis

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@dhelekal dhelekal Feb 5, 2018 •
edited

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Yeah, sorry, i didnt want to commit that change.
It's just to make the style checker run locally. Working on reverting this.

RESULT_OUTPUT="$(git clang-format --commit $BASE_COMMIT --diff --binary `which clang-format` $LIST)"

if [ "$RESULT_OUTPUT" == "no modified files to format" ] \
|| [ "$RESULT_OUTPUT" == "clang-format-3.8 did not modify any files" ] \
Expand All @@ -54,10 +54,10 @@ function check_shogun_style {
echo "clang-format failed."
echo "To reproduce it locally please run: "
echo -e "\t1) git checkout ${1:-}"
echo -e "\t2) git clang-format-3.8 --commit $BASE_COMMIT --diff --binary $(which clang-format-3.8)"
echo -e "\t2) git clang-format --commit $BASE_COMMIT --diff --binary $(which clang-format)"
echo "To fix the errors automatically please run: "
echo -e "\t1) git checkout ${1:-}"
echo -e "\t2) git clang-format-3.8 --commit $BASE_COMMIT --binary $(which clang-format-3.8)"
echo -e "\t2) git clang-format --commit $BASE_COMMIT --binary $(which clang-format)"
echo "-----"
echo "Style errors found:"
echo "$RESULT_OUTPUT"
Expand Down
39 changes: 14 additions & 25 deletions src/shogun/kernel/CombinedKernel.cpp
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Expand Up @@ -66,27 +66,20 @@ bool CCombinedKernel::init_with_extracted_subsets(
SGVector<index_t> rhs_subset)
{

auto l_combined = dynamic_cast<CCombinedFeatures*>(l);
auto r_combined = dynamic_cast<CCombinedFeatures*>(r);

if (!l_combined || !r_combined)
SG_ERROR("Cast failed - unsupported features passed")
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imo this will never happen (unless l or r is null) since if the typecasting fails it'll throw a bad_casting exception.


CKernel::init(l, r);
REQUIRE(
l->get_feature_class() == C_COMBINED,
"%s::init(): LHS features are"
" of class %s but need to be combined features!\n",
get_name(), l->get_name());
REQUIRE(
r->get_feature_class() == C_COMBINED,
"%s::init(): RHS features are"
" of class %s but need to be combined features!\n",
get_name(), r->get_name());
ASSERT(l->get_feature_type() == F_UNKNOWN)
ASSERT(r->get_feature_type() == F_UNKNOWN)

CFeatures* lf = NULL;
CFeatures* rf = NULL;
CKernel* k = NULL;

auto l_combined = dynamic_cast<CCombinedFeatures*>(l);
auto r_combined = dynamic_cast<CCombinedFeatures*>(r);

bool result = true;
index_t f_idx = 0;

Expand Down Expand Up @@ -138,6 +131,8 @@ bool CCombinedKernel::init_with_extracted_subsets(
"No kernel matrix was assigned to this Custom kernel\n")

auto k_custom = dynamic_cast<CCustomKernel*>(k);
if (!k_custom)
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same as above, see http://en.cppreference.com/w/cpp/language/dynamic_cast

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As we're casting a pointer type, it should be NULL on fail afaik? From the website:
If the cast fails and new_type is a pointer type, it returns a null pointer of that type.

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/me should really RTFM before saying RTFM

SG_ERROR("Dynamic cast to custom kernel failed")

// clear all previous subsets
k_custom->remove_all_row_subsets();
Expand Down Expand Up @@ -193,21 +188,18 @@ bool CCombinedKernel::init(CFeatures* l, CFeatures* r)
{
init_subkernel_weights();
}
/*
* The two subsets, we will be passing those to init_with_extracted_subsets
*/

if (!l)
SG_ERROR("LHS features are NULL");
if (!r)
SG_ERROR("RHS features are NULL");

SGVector<index_t> lhs_subset;
SGVector<index_t> rhs_subset;

/*
* We will be passing these features to init_with_extracted_subsets
*/
CCombinedFeatures* combined_l;
CCombinedFeatures* combined_r;

/*
* Extract the subsets so that we can pass them on
*/
auto l_subset_stack = l->get_subset_stack();
auto r_subset_stack = r->get_subset_stack();

Expand Down Expand Up @@ -258,9 +250,6 @@ bool CCombinedKernel::init(CFeatures* l, CFeatures* r)
}
else
{
/*
* Otherwise, we just pass l & r straight on
*/
combined_l = (CCombinedFeatures*)l;
combined_r = (CCombinedFeatures*)r;
}
Expand Down
92 changes: 45 additions & 47 deletions tests/unit/kernel/CombinedKernel_unittest.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -45,10 +45,12 @@ TEST(CombinedKernelTest,test_array_operations)
TEST(CombinedKernelTest, test_subset_mixed)
{

CMeanShiftDataGenerator* gen = new CMeanShiftDataGenerator(0, 2);
CFeatures* feats = gen->get_streamed_features(10);
int n_runs = 10;

CCombinedFeatures* cf = new CCombinedFeatures();
auto gen = new CMeanShiftDataGenerator(0, 2);
CFeatures* feats = gen->get_streamed_features(n_runs);

CCombinedFeatures* feats_combined = new CCombinedFeatures();

CCombinedKernel* combined = new CCombinedKernel();

Expand All @@ -64,59 +66,59 @@ TEST(CombinedKernelTest, test_subset_mixed)

combined->append_kernel(custom_1);
combined->append_kernel(gaus_1);
cf->append_feature_obj(feats);
feats_combined->append_feature_obj(feats);

combined->append_kernel(custom_2);
combined->append_kernel(gaus_2);
cf->append_feature_obj(feats);
feats_combined->append_feature_obj(feats);

SGVector<index_t> inds(10);
inds.range_fill();

for (index_t i = 0; i < 10; ++i)
for (index_t i = 0; i < n_runs; ++i)
{
CMath::permute(inds);

cf->add_subset(inds);
combined->init(cf, cf);
feats_combined->add_subset(inds);
combined->init(feats_combined, feats_combined);

CKernel* k_g = combined->get_kernel(1);
CKernel* k_0 = combined->get_kernel(0);
CKernel* k_3 = combined->get_kernel(2);
CKernel* ground_truth_kernel = combined->get_kernel(1);
CKernel* custom_kernel_1 = combined->get_kernel(0);
CKernel* custom_kernel_2 = combined->get_kernel(2);

SGMatrix<float64_t> gauss_matrix = k_g->get_kernel_matrix();
SGMatrix<float64_t> custom_matrix_1 = k_0->get_kernel_matrix();
SGMatrix<float64_t> custom_matrix_2 = k_3->get_kernel_matrix();
SGMatrix<float64_t> gauss_matrix =
ground_truth_kernel->get_kernel_matrix();
SGMatrix<float64_t> custom_matrix_1 =
custom_kernel_1->get_kernel_matrix();
SGMatrix<float64_t> custom_matrix_2 =
custom_kernel_2->get_kernel_matrix();

for (index_t j = 0; j < 10; ++j)
for (index_t j = 0; j < n_runs; ++j)
{
for (index_t k = 0; k < 10; ++k)
for (index_t k = 0; k < n_runs; ++k)
{
EXPECT_LE(
CMath::abs(gauss_matrix(k, j) - custom_matrix_1(k, j)),
1e-6);
EXPECT_LE(
CMath::abs(gauss_matrix(k, j) - custom_matrix_2(k, j)),
1e-6);
EXPECT_NEAR(gauss_matrix(j, k), custom_matrix_1(j, k), 1e-6);
EXPECT_NEAR(gauss_matrix(j, k), custom_matrix_1(j, k), 1e-6);
}
}

cf->remove_subset();
SG_UNREF(k_g);
SG_UNREF(k_0);
SG_UNREF(k_3);
feats_combined->remove_subset();
SG_UNREF(ground_truth_kernel);
SG_UNREF(custom_kernel_1);
SG_UNREF(custom_kernel_2);
}

SG_UNREF(gen);
SG_UNREF(gaus_ck);
SG_UNREF(combined);
}

TEST(CombinedKernelTest, test_subset_combined_only)
{

CMeanShiftDataGenerator* gen = new CMeanShiftDataGenerator(0, 2);
CFeatures* feats = gen->get_streamed_features(10);
int n_runs = 10;

auto gen = new CMeanShiftDataGenerator(0, 2);
CFeatures* feats = gen->get_streamed_features(n_runs);

CCombinedKernel* combined = new CCombinedKernel();

Expand All @@ -125,48 +127,44 @@ TEST(CombinedKernelTest, test_subset_combined_only)

CCustomKernel* custom_1 = new CCustomKernel(gaus_ck);
CCustomKernel* custom_2 = new CCustomKernel(gaus_ck);
;

combined->append_kernel(custom_1);
combined->append_kernel(custom_2);

SGVector<index_t> inds(10);
SGVector<index_t> inds(n_runs);
inds.range_fill();

for (index_t i = 0; i < 10; ++i)
for (index_t i = 0; i < n_runs; ++i)
{
CMath::permute(inds);

feats->add_subset(inds);
combined->init(feats, feats);
gaus_ck->init(feats, feats);

CKernel* k_0 = combined->get_kernel(0);
CKernel* k_1 = combined->get_kernel(1);
CKernel* custom_kernel_1 = combined->get_kernel(0);
CKernel* custom_kernel_2 = combined->get_kernel(1);

SGMatrix<float64_t> gauss_matrix = gaus_ck->get_kernel_matrix();
SGMatrix<float64_t> custom_matrix_1 = k_0->get_kernel_matrix();
SGMatrix<float64_t> custom_matrix_2 = k_1->get_kernel_matrix();
SGMatrix<float64_t> custom_matrix_1 =
custom_kernel_1->get_kernel_matrix();
SGMatrix<float64_t> custom_matrix_2 =
custom_kernel_2->get_kernel_matrix();

for (index_t j = 0; j < 10; ++j)
for (index_t j = 0; j < n_runs; ++j)
{
for (index_t k = 0; k < 10; ++k)
for (index_t k = 0; k < n_runs; ++k)
{
EXPECT_LE(
CMath::abs(gauss_matrix(k, j) - custom_matrix_1(k, j)),
1e-6);
EXPECT_LE(
CMath::abs(gauss_matrix(k, j) - custom_matrix_2(k, j)),
1e-6);
EXPECT_NEAR(gauss_matrix(j, k), custom_matrix_1(j, k), 1e-6);
EXPECT_NEAR(gauss_matrix(j, k), custom_matrix_1(j, k), 1e-6);
}
}

feats->remove_subset();
SG_UNREF(k_0);
SG_UNREF(k_1);
SG_UNREF(custom_kernel_1);
SG_UNREF(custom_kernel_2);
}

SG_UNREF(gen);
SG_UNREF(gaus_ck);
SG_UNREF(combined);
}
Expand Down