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#include "main.h"
#include <Eigen/CXX11/Tensor>
using Eigen::Tensor;
using Eigen::RowMajor;
static void test_comparison_sugar() {
// we already trust comparisons between tensors, we're simply checking that
// the sugared versions are doing the same thing
Tensor<int, 3> t(6, 7, 5);
t.setRandom();
// make sure we have at least one value == 0
t(0,0,0) = 0;
Tensor<bool,0> b;
#define TEST_TENSOR_EQUAL(e1, e2) \
b = ((e1) == (e2)).all(); \
VERIFY(b())
#define TEST_OP(op) TEST_TENSOR_EQUAL(t op 0, t op t.constant(0))
TEST_OP(==);
TEST_OP(!=);
TEST_OP(<=);
TEST_OP(>=);
TEST_OP(<);
TEST_OP(>);
#undef TEST_OP
#undef TEST_TENSOR_EQUAL
}
static void test_scalar_sugar_add_mul() {
Tensor<float, 3> A(6, 7, 5);
Tensor<float, 3> B(6, 7, 5);
A.setRandom();
B.setRandom();
const float alpha = 0.43f;
const float beta = 0.21f;
const float gamma = 0.14f;
Tensor<float, 3> R = A.constant(gamma) + A * A.constant(alpha) + B * B.constant(beta);
Tensor<float, 3> S = A * alpha + B * beta + gamma;
Tensor<float, 3> T = gamma + alpha * A + beta * B;
for (int i = 0; i < 6*7*5; ++i) {
VERIFY_IS_APPROX(R(i), S(i));
VERIFY_IS_APPROX(R(i), T(i));
}
}
static void test_scalar_sugar_sub_div() {
Tensor<float, 3> A(6, 7, 5);
Tensor<float, 3> B(6, 7, 5);
A.setRandom();
B.setRandom();
const float alpha = 0.43f;
const float beta = 0.21f;
const float gamma = 0.14f;
const float delta = 0.32f;
Tensor<float, 3> R = A.constant(gamma) - A / A.constant(alpha)
- B.constant(beta) / B - A.constant(delta);
Tensor<float, 3> S = gamma - A / alpha - beta / B - delta;
for (int i = 0; i < 6*7*5; ++i) {
VERIFY_IS_APPROX(R(i), S(i));
}
}
EIGEN_DECLARE_TEST(cxx11_tensor_sugar)
{
CALL_SUBTEST(test_comparison_sugar());
CALL_SUBTEST(test_scalar_sugar_add_mul());
CALL_SUBTEST(test_scalar_sugar_sub_div());
}
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