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Use numerically stable tree reduction in TensorReduction.

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This commit is contained in:
Rasmus Munk Larsen
2018-09-11 10:08:10 -07:00
parent 43fd42a33b
commit 46f88fc454
4 changed files with 141 additions and 61 deletions
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28
unsupported/test/cxx11_tensor_reduction.cpp
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@@ -386,7 +386,7 @@ static void test_static_dims() {
expected = (std::max)(expected, in(i, k, j, l));
}
}
VERIFY_IS_APPROX(out(i, j), expected);
VERIFY_IS_EQUAL(out(i, j), expected);
}
}
}
@@ -417,7 +417,7 @@ static void test_innermost_last_dims() {
expected = (std::max)(expected, in(l, k, i, j));
}
}
VERIFY_IS_APPROX(out(i, j), expected);
VERIFY_IS_EQUAL(out(i, j), expected);
}
}
}
@@ -448,7 +448,7 @@ static void test_innermost_first_dims() {
expected = (std::max)(expected, in(i, j, k, l));
}
}
VERIFY_IS_APPROX(out(i, j), expected);
VERIFY_IS_EQUAL(out(i, j), expected);
}
}
}
@@ -479,11 +479,30 @@ static void test_reduce_middle_dims() {
expected = (std::max)(expected, in(i, k, l, j));
}
}
VERIFY_IS_APPROX(out(i, j), expected);
VERIFY_IS_EQUAL(out(i, j), expected);
}
}
}
static void test_sum_accuracy() {
Tensor<float, 3> tensor(101, 101, 101);
for (float prescribed_mean : {1.0f, 10.0f, 100.0f, 1000.0f, 10000.0f}) {
tensor.setRandom();
tensor += tensor.constant(prescribed_mean);
Tensor<float, 0> sum = tensor.sum();
double expected_sum = 0.0;
for (int i = 0; i < 101; ++i) {
for (int j = 0; j < 101; ++j) {
for (int k = 0; k < 101; ++k) {
expected_sum += static_cast<double>(tensor(i, j, k));
}
}
}
VERIFY_IS_APPROX(sum(), static_cast<float>(expected_sum));
}
}
EIGEN_DECLARE_TEST(cxx11_tensor_reduction) {
CALL_SUBTEST(test_trivial_reductions<ColMajor>());
CALL_SUBTEST(test_trivial_reductions<RowMajor>());
@@ -506,4 +525,5 @@ EIGEN_DECLARE_TEST(cxx11_tensor_reduction) {
CALL_SUBTEST(test_innermost_first_dims<RowMajor>());
CALL_SUBTEST(test_reduce_middle_dims<ColMajor>());
CALL_SUBTEST(test_reduce_middle_dims<RowMajor>());
CALL_SUBTEST(test_sum_accuracy());
}