Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

seeding fix for xvalmmd #4784

Open
wants to merge 1 commit into
base: develop
Choose a base branch
from
Open
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
Original file line number Diff line number Diff line change
Expand Up @@ -195,16 +195,11 @@ struct CrossValidationMMD : PermutationMMD
SGVector<int64_t> dummy_labels_x(m_n_x);
SGVector<int64_t> dummy_labels_y(m_n_y);

Copy link
Member Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

@lambday i'm pretty sure that if i would do prng(); prng();
this patch would pass

auto instance_x=new CCrossValidationSplitting(new CBinaryLabels(dummy_labels_x), m_num_folds);
auto instance_y=new CCrossValidationSplitting(new CBinaryLabels(dummy_labels_y), m_num_folds);
random::seed(instance_x, prng);
random::seed(instance_y, prng);

m_kfold_x=unique_ptr<CCrossValidationSplitting>(instance_x);
m_kfold_y=unique_ptr<CCrossValidationSplitting>(instance_y);
m_kfold_x=std::make_unique<CCrossValidationSplitting>(new CBinaryLabels(dummy_labels_x), m_num_folds);
m_kfold_y=std::make_unique<CCrossValidationSplitting>(new CBinaryLabels(dummy_labels_y), m_num_folds);
random::seed(m_kfold_x.get(), prng);
random::seed(m_kfold_y.get(), prng);

m_stack=unique_ptr<CSubsetStack>(new CSubsetStack());

const index_t size=m_n_x+m_n_y;
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -107,6 +107,7 @@ TEST(CrossValidationMMD, biased_full)
kfold_p->put("seed", seed);
kfold_q->put("seed", seed);

std::mt19937_64 permPRNG(seed);
auto permutation_mmd=PermutationMMD();
permutation_mmd.m_stype=stype;
permutation_mmd.m_num_null_samples=num_null_samples;
Expand Down Expand Up @@ -134,7 +135,7 @@ TEST(CrossValidationMMD, biased_full)
(feats_p->create_merged_copy(feats_q));

kernel->init(current_merged_feats, current_merged_feats);
auto p_value=permutation_mmd.p_value(kernel->get_kernel_matrix<float32_t>(), prng);
auto p_value=permutation_mmd.p_value(kernel->get_kernel_matrix<float32_t>(), permPRNG);

EXPECT_EQ(cv.m_rejections(current_run*num_folds+current_fold, k), p_value<alpha);

Expand Down Expand Up @@ -206,6 +207,7 @@ TEST(CrossValidationMMD, unbiased_full)
kfold_p->put("seed", seed);
kfold_q->put("seed", seed);

std::mt19937_64 permPRNG(seed);
auto permutation_mmd=PermutationMMD();
permutation_mmd.m_stype=stype;
permutation_mmd.m_num_null_samples=num_null_samples;
Expand Down Expand Up @@ -233,7 +235,7 @@ TEST(CrossValidationMMD, unbiased_full)
(feats_p->create_merged_copy(feats_q));

kernel->init(current_merged_feats, current_merged_feats);
auto p_value=permutation_mmd.p_value(kernel->get_kernel_matrix<float32_t>(), prng);
auto p_value=permutation_mmd.p_value(kernel->get_kernel_matrix<float32_t>(), permPRNG);

EXPECT_EQ(cv.m_rejections(current_run*num_folds+current_fold, k), p_value<alpha);

Expand Down Expand Up @@ -306,6 +308,7 @@ TEST(CrossValidationMMD, unbiased_incomplete)
kfold_p->put("seed", seed);
kfold_q->put("seed", seed);

std::mt19937_64 permPRNG(seed);
auto permutation_mmd=PermutationMMD();
permutation_mmd.m_stype=stype;
permutation_mmd.m_num_null_samples=num_null_samples;
Expand Down Expand Up @@ -333,7 +336,7 @@ TEST(CrossValidationMMD, unbiased_incomplete)
(feats_p->create_merged_copy(feats_q));

kernel->init(current_merged_feats, current_merged_feats);
auto p_value=permutation_mmd.p_value(kernel->get_kernel_matrix<float32_t>(), prng);
auto p_value=permutation_mmd.p_value(kernel->get_kernel_matrix<float32_t>(), permPRNG);

EXPECT_EQ(cv.m_rejections(current_run*num_folds+current_fold, k), p_value<alpha);

Expand Down