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Add syntactic sugar to Eigen tensors to allow more natural syntax.

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Specifically, this enables expressions involving:

scalar + tensor
scalar * tensor
scalar / tensor
scalar - tensor
This commit is contained in:
Rasmus Munk Larsen 2016-06-02 12:41:28 -07:00
parent 6021c90fdf
commit 811aadbe00
2 changed files with 57 additions and 7 deletions
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30
unsupported/Eigen/CXX11/src/Tensor/TensorBase.h
View File

@ -215,6 +215,13 @@ class TensorBase<Derived, ReadOnlyAccessors>
return unaryExpr(internal::scalar_add_op<Scalar>(rhs)); return unaryExpr(internal::scalar_add_op<Scalar>(rhs));
} }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE friend
const TensorCwiseUnaryOp<internal::scalar_add_op<Scalar>, const Derived>
operator+ (Scalar lhs, const Derived& rhs) {
return rhs + lhs;
}
EIGEN_DEVICE_FUNC EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_sub_op<Scalar>, const Derived> EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_sub_op<Scalar>, const Derived>
operator- (Scalar rhs) const { operator- (Scalar rhs) const {
@ -222,18 +229,41 @@ class TensorBase<Derived, ReadOnlyAccessors>
return unaryExpr(internal::scalar_sub_op<Scalar>(rhs)); return unaryExpr(internal::scalar_sub_op<Scalar>(rhs));
} }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE friend
const TensorCwiseUnaryOp<internal::scalar_add_op<Scalar>,
const TensorCwiseUnaryOp<internal::scalar_opposite_op<Scalar>, const Derived> >
operator- (Scalar lhs, const Derived& rhs) {
return -rhs + lhs;
}
EIGEN_DEVICE_FUNC EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const Derived> EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const Derived>
operator* (Scalar rhs) const { operator* (Scalar rhs) const {
return unaryExpr(internal::scalar_multiple_op<Scalar>(rhs)); return unaryExpr(internal::scalar_multiple_op<Scalar>(rhs));
} }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE friend
const TensorCwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const Derived>
operator* (Scalar lhs, const Derived& rhs) {
return rhs * lhs;
}
EIGEN_DEVICE_FUNC EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_quotient1_op<Scalar>, const Derived> EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_quotient1_op<Scalar>, const Derived>
operator/ (Scalar rhs) const { operator/ (Scalar rhs) const {
return unaryExpr(internal::scalar_quotient1_op<Scalar>(rhs)); return unaryExpr(internal::scalar_quotient1_op<Scalar>(rhs));
} }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE friend
const TensorCwiseUnaryOp<internal::scalar_multiple_op<Scalar>,
const TensorCwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const Derived> >
operator/ (Scalar lhs, const Derived& rhs) {
return rhs.inverse() * lhs;
}
EIGEN_DEVICE_FUNC EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_mod_op<Scalar>, const Derived> EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_mod_op<Scalar>, const Derived>
operator% (Scalar rhs) const { operator% (Scalar rhs) const {

34
unsupported/test/cxx11_tensor_sugar.cpp
View File

@ -33,7 +33,7 @@ static void test_comparison_sugar() {
} }
static void test_scalar_sugar() { static void test_scalar_sugar_add_mul() {
Tensor<float, 3> A(6, 7, 5); Tensor<float, 3> A(6, 7, 5);
Tensor<float, 3> B(6, 7, 5); Tensor<float, 3> B(6, 7, 5);
A.setRandom(); A.setRandom();
@ -41,21 +41,41 @@ static void test_scalar_sugar() {
const float alpha = 0.43f; const float alpha = 0.43f;
const float beta = 0.21f; const float beta = 0.21f;
const float gamma = 0.14f;
Tensor<float, 3> R = A * A.constant(alpha) + B * B.constant(beta); Tensor<float, 3> R = A.constant(gamma) + A * A.constant(alpha) + B * B.constant(beta);
Tensor<float, 3> S = A * alpha + B * beta; Tensor<float, 3> S = A * alpha + B * beta + gamma;
Tensor<float, 3> T = gamma + alpha * A + beta * B;
// TODO: add enough syntactic sugar to support this for (int i = 0; i < 6*7*5; ++i) {
// Tensor<float, 3> T = alpha * A + beta * B; 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) { for (int i = 0; i < 6*7*5; ++i) {
VERIFY_IS_APPROX(R(i), S(i)); VERIFY_IS_APPROX(R(i), S(i));
} }
} }
void test_cxx11_tensor_sugar() void test_cxx11_tensor_sugar()
{ {
CALL_SUBTEST(test_comparison_sugar()); CALL_SUBTEST(test_comparison_sugar());
CALL_SUBTEST(test_scalar_sugar()); CALL_SUBTEST(test_scalar_sugar_add_mul());
CALL_SUBTEST(test_scalar_sugar_sub_div());
} }