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81 lines
1.9 KiB
81 lines
1.9 KiB
#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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