return sum / sample_size;
}
+ Dtype sample_mean(const int* const seqs, const size_t sample_size)
+ {
+ Dtype sum = 0;
+ for (int i = 0; i < sample_size; ++i) {
+ sum += Dtype(seqs[i]);
+ }
+ return sum / sample_size;
+ }
+
Dtype mean_bound(const Dtype std, const size_t sample_size)
{
return std/sqrt((double)sample_size);
Caffe::set_random_seed(1701);
TypeParam mu = 0;
TypeParam sigma = 1;
- caffe_vRngGaussian(sample_size, (TypeParam*)data_a.mutable_cpu_data(), mu, sigma);
+ caffe_vRngGaussian(sample_size,
+ (TypeParam*)data_a.mutable_cpu_data(), mu, sigma);
TypeParam true_mean = mu;
TypeParam true_std = sigma;
TypeParam bound = this->mean_bound(true_std, sample_size);
- TypeParam real_mean = this->sample_mean((TypeParam*)data_a.cpu_data(), sample_size);
- EXPECT_NEAR(real_mean, true_mean, bound);
+ TypeParam empirical_mean =
+ this->sample_mean((TypeParam*)data_a.cpu_data(), sample_size);
+ EXPECT_NEAR(empirical_mean, true_mean, bound);
}
+
TYPED_TEST(RandomNumberGeneratorTest, TestRngUniform) {
size_t sample_size = 10000;
SyncedMemory data_a(sample_size * sizeof(TypeParam));
Caffe::set_random_seed(1701);
TypeParam lower = 0;
TypeParam upper = 1;
- caffe_vRngUniform(sample_size, (TypeParam*)data_a.mutable_cpu_data(), lower, upper);
+ caffe_vRngUniform(sample_size,
+ (TypeParam*)data_a.mutable_cpu_data(), lower, upper);
TypeParam true_mean = (lower + upper) / 2;
TypeParam true_std = (upper - lower) / sqrt(12);
TypeParam bound = this->mean_bound(true_std, sample_size);
- TypeParam real_mean = this->sample_mean((TypeParam*)data_a.cpu_data(), sample_size);
- EXPECT_NEAR(real_mean, true_mean, bound);
+ TypeParam empirical_mean =
+ this->sample_mean((TypeParam*)data_a.cpu_data(), sample_size);
+ EXPECT_NEAR(empirical_mean, true_mean, bound);
}
+TYPED_TEST(RandomNumberGeneratorTest, TestRngBernoulli) {
+ size_t sample_size = 10000;
+ SyncedMemory data_a(sample_size * sizeof(int));
+ Caffe::set_random_seed(1701);
+ double p = 0.3;
+ caffe_vRngBernoulli(sample_size, (int*)data_a.mutable_cpu_data(), p);
+ TypeParam true_mean = p;
+ TypeParam true_std = sqrt(p * (1 - p));
+ TypeParam bound = this->mean_bound(true_std, sample_size);
+ TypeParam empirical_mean =
+ this->sample_mean((const int *)data_a.cpu_data(), sample_size);
+ EXPECT_NEAR(empirical_mean, true_mean, bound);
+}
+
} // namespace caffe