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Updated the contraction code to support constant inputs.
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@ -25,7 +25,8 @@ template<typename Dimensions, typename LhsXprType, typename RhsXprType>
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struct traits<TensorContractionOp<Dimensions, LhsXprType, RhsXprType> >
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{
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// Type promotion to handle the case where the types of the lhs and the rhs are different.
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typedef typename gebp_traits<typename LhsXprType::Scalar, typename RhsXprType::Scalar>::ResScalar Scalar;
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typedef typename gebp_traits<typename remove_const<typename LhsXprType::Scalar>::type,
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typename remove_const<typename RhsXprType::Scalar>::type>::ResScalar Scalar;
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typedef typename promote_storage_type<typename traits<LhsXprType>::StorageKind,
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typename traits<RhsXprType>::StorageKind>::ret StorageKind;
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@ -489,6 +489,27 @@ static void test_tensor_product()
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}
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template<int DataLayout>
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static void test_const_inputs()
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{
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Tensor<float, 2, DataLayout> in1(2, 3);
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Tensor<float, 2, DataLayout> in2(3, 2);
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in1.setRandom();
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in2.setRandom();
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TensorMap<Tensor<const float, 2, DataLayout> > mat1(in1.data(), 2, 3);
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TensorMap<Tensor<const float, 2, DataLayout> > mat2(in2.data(), 3, 2);
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Tensor<float, 2, DataLayout> mat3(2,2);
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Eigen::array<DimPair, 1> dims = {{DimPair(1, 0)}};
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mat3 = mat1.contract(mat2, dims);
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VERIFY_IS_APPROX(mat3(0,0), mat1(0,0)*mat2(0,0) + mat1(0,1)*mat2(1,0) + mat1(0,2)*mat2(2,0));
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VERIFY_IS_APPROX(mat3(0,1), mat1(0,0)*mat2(0,1) + mat1(0,1)*mat2(1,1) + mat1(0,2)*mat2(2,1));
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VERIFY_IS_APPROX(mat3(1,0), mat1(1,0)*mat2(0,0) + mat1(1,1)*mat2(1,0) + mat1(1,2)*mat2(2,0));
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VERIFY_IS_APPROX(mat3(1,1), mat1(1,0)*mat2(0,1) + mat1(1,1)*mat2(1,1) + mat1(1,2)*mat2(2,1));
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}
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void test_cxx11_tensor_contraction()
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{
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CALL_SUBTEST(test_evals<ColMajor>());
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@ -519,4 +540,6 @@ void test_cxx11_tensor_contraction()
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CALL_SUBTEST(test_small_blocking_factors<RowMajor>());
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CALL_SUBTEST(test_tensor_product<ColMajor>());
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CALL_SUBTEST(test_tensor_product<RowMajor>());
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CALL_SUBTEST(test_const_inputs<ColMajor>());
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CALL_SUBTEST(test_const_inputs<RowMajor>());
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}
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