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Added support for expm1 in Eigen.

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This commit is contained in:
Srinivas Vasudevan
2016-12-02 14:13:01 -08:00
parent 27873008d4
commit 218764ee1f
15 changed files with 171 additions and 13 deletions
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6
unsupported/Eigen/CXX11/src/Tensor/TensorBase.h
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@@ -185,6 +185,12 @@ class TensorBase<Derived, ReadOnlyAccessors>
return unaryExpr(internal::scalar_exp_op<Scalar>());
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_expm1_op<Scalar>, const Derived>
expm1() const {
return unaryExpr(internal::scalar_expm1_op<Scalar>());
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const TensorCwiseUnaryOp<internal::scalar_log_op<Scalar>, const Derived>
log() const {

1
unsupported/Eigen/CXX11/src/Tensor/TensorMeta.h
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@@ -75,6 +75,7 @@ struct PacketType<half, GpuDevice> {
HasSqrt = 1,
HasRsqrt = 1,
HasExp = 1,
HasExpm1 = 0,
HasLog = 1,
HasLog1p = 0,
HasLog10 = 0,

1
unsupported/test/cxx11_tensor_builtins_sycl.cpp
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@@ -91,6 +91,7 @@ template <typename T> T inverse(T x) { return 1 / x; }
TEST_UNARY_BUILTINS_FOR_SCALAR(inverse, SCALAR, OPERATOR) \
TEST_UNARY_BUILTINS_FOR_SCALAR(tanh, SCALAR, OPERATOR) \
TEST_UNARY_BUILTINS_FOR_SCALAR(exp, SCALAR, OPERATOR) \
TEST_UNARY_BUILTINS_FOR_SCALAR(expm1, SCALAR, OPERATOR) \
TEST_UNARY_BUILTINS_FOR_SCALAR(log, SCALAR, OPERATOR) \
TEST_UNARY_BUILTINS_FOR_SCALAR(abs, SCALAR, OPERATOR) \
TEST_UNARY_BUILTINS_FOR_SCALAR(ceil, SCALAR, OPERATOR) \

6
unsupported/test/cxx11_tensor_of_float16_cuda.cu
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@@ -200,6 +200,8 @@ void test_cuda_trancendental() {
Eigen::TensorMap<Eigen::Tensor<Eigen::half, 1>, Eigen::Aligned> gpu_res2_float(d_res2_float, num_elem);
Eigen::TensorMap<Eigen::Tensor<Eigen::half, 1>, Eigen::Aligned> gpu_res3_half(d_res3_half, num_elem);
Eigen::TensorMap<Eigen::Tensor<Eigen::half, 1>, Eigen::Aligned> gpu_res3_float(d_res3_float, num_elem);
Eigen::TensorMap<Eigen::Tensor<Eigen::half, 1>, Eigen::Aligned> gpu_res4_half(d_res3_half, num_elem);
Eigen::TensorMap<Eigen::Tensor<Eigen::half, 1>, Eigen::Aligned> gpu_res4_float(d_res3_float, num_elem);
gpu_float1.device(gpu_device) = gpu_float1.random() - gpu_float1.constant(0.5f);
gpu_float2.device(gpu_device) = gpu_float2.random() + gpu_float1.constant(0.5f);
@@ -207,6 +209,7 @@ void test_cuda_trancendental() {
gpu_res1_float.device(gpu_device) = gpu_float1.exp().cast<Eigen::half>();
gpu_res2_float.device(gpu_device) = gpu_float2.log().cast<Eigen::half>();
gpu_res3_float.device(gpu_device) = gpu_float3.log1p().cast<Eigen::half>();
gpu_res4_float.device(gpu_device) = gpu_float3.expm1().cast<Eigen::half>();
gpu_res1_half.device(gpu_device) = gpu_float1.cast<Eigen::half>();
gpu_res1_half.device(gpu_device) = gpu_res1_half.exp();
@@ -217,6 +220,9 @@ void test_cuda_trancendental() {
gpu_res3_half.device(gpu_device) = gpu_float3.cast<Eigen::half>();
gpu_res3_half.device(gpu_device) = gpu_res3_half.log1p();
gpu_res3_half.device(gpu_device) = gpu_float3.cast<Eigen::half>();
gpu_res3_half.device(gpu_device) = gpu_res3_half.expm1();
Tensor<float, 1> input1(num_elem);
Tensor<Eigen::half, 1> half_prec1(num_elem);
Tensor<Eigen::half, 1> full_prec1(num_elem);