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