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// See docs in ../ops/math_ops.cc.
#define EIGEN_USE_THREADS
#include "tensorflow/core/kernels/aggregate_ops.h"
#include "tensorflow/core/framework/numeric_op.h"
#include "tensorflow/core/framework/register_types.h"
#include "tensorflow/core/platform/logging.h"
namespace tensorflow {
typedef Eigen::ThreadPoolDevice CPUDevice;
typedef Eigen::GpuDevice GPUDevice;
template <typename Device, typename T>
class AddNOp : public OpKernel {
public:
explicit AddNOp(OpKernelConstruction* context) : OpKernel(context) {}
void Compute(OpKernelContext* ctx) override {
if (!ctx->ValidateInputsAreSameShape(this)) return;
const Tensor& input0 = ctx->input(0);
Tensor* output = nullptr;
OP_REQUIRES_OK(ctx, ctx->allocate_output(0, input0.shape(), &output));
auto To = output->flat<T>();
const int num = ctx->num_inputs();
if (num == 1) {
*output = input0;
return;
}
#define I(IDX) ctx->input(IDX).flat<T>()
#if defined(PLATFORM_POSIX_ANDROID) || defined(PLATFORM_GOOGLE_ANDROID)
// On Android, we only support additions of two arguments, so we
// can reduce the number of template instantiations.
OP_REQUIRES(ctx, num == 2,
errors::InvalidArgument("Only additions of two arguments "
"supported. Num inputs: ",
num));
functor::Add2Functor<Device, T> functor2;
functor2(ctx->template eigen_device<Device>(), To, I(0), I(1));
#else
static const int kWidth = 8;
int r = num % kWidth;
switch (r) {
case 2: {
functor::Add2Functor<Device, T> functor2;
functor2(ctx->template eigen_device<Device>(), To, I(0), I(1));
break;
}
case 3: {
functor::Add3Functor<Device, T> functor3;
functor3(ctx->template eigen_device<Device>(), To, I(0), I(1), I(2));
break;
}
case 4: {
functor::Add4Functor<Device, T> functor4;
functor4(ctx->template eigen_device<Device>(), To, I(0), I(1), I(2),
I(3));
break;
}
case 5: {
functor::Add5Functor<Device, T> functor5;
functor5(ctx->template eigen_device<Device>(), To, I(0), I(1), I(2),
I(3), I(4));
break;
}
case 6: {
functor::Add6Functor<Device, T> functor6;
functor6(ctx->template eigen_device<Device>(), To, I(0), I(1), I(2),
I(3), I(4), I(5));
break;
}
case 7: {
functor::Add7Functor<Device, T> functor7;
functor7(ctx->template eigen_device<Device>(), To, I(0), I(1), I(2),
I(3), I(4), I(5), I(6));
break;
}
case 0: {
functor::Add8Functor<Device, T> functor8;
functor8(ctx->template eigen_device<Device>(), To, I(0), I(1), I(2),
I(3), I(4), I(5), I(6), I(7));
r = 8;
break;
}
case 1: {
functor::Add9Functor<Device, T> functor9;
functor9(ctx->template eigen_device<Device>(), To, I(0), I(1), I(2),
I(3), I(4), I(5), I(6), I(7), I(8));
r = 9;
break;
}
}
for (; r < num; r += kWidth) {
functor::Add8pFunctor<Device, T> functor8p;
functor8p(ctx->template eigen_device<Device>(), To, I(r), I(r + 1),
I(r + 2), I(r + 3), I(r + 4), I(r + 5), I(r + 6), I(r + 7));
}
#endif // defined(PLATFORM_POSIX_ANDROID) || defined(PLATFORM_GOOGLE_ANDROID)
#undef I
}
};
// Partial specializations for a CPUDevice, that uses the Eigen implementation
// from AddNEigenImpl.
namespace functor {
template <typename T>
struct Add2Functor<CPUDevice, T> {
void operator()(const CPUDevice& d, typename TTypes<T>::Flat out,
typename TTypes<T>::ConstFlat in1,
typename TTypes<T>::ConstFlat in2) {
Add2EigenImpl<CPUDevice, T>::Compute(d, out, in1, in2);
}
};
template <typename T>
struct Add3Functor<CPUDevice, T> {
void operator()(const CPUDevice& d, typename TTypes<T>::Flat out,
typename TTypes<T>::ConstFlat in1,
typename TTypes<T>::ConstFlat in2,
typename TTypes<T>::ConstFlat in3) {
Add3EigenImpl<CPUDevice, T>::Compute(d, out, in1, in2, in3);
}
};
template <typename T>
struct Add4Functor<CPUDevice, T> {
void operator()(const CPUDevice& d, typename TTypes<T>::Flat out,
typename TTypes<T>::ConstFlat in1,
typename TTypes<T>::ConstFlat in2,
typename TTypes<T>::ConstFlat in3,
typename TTypes<T>::ConstFlat in4) {
Add4EigenImpl<CPUDevice, T>::Compute(d, out, in1, in2, in3, in4);
}
};
template <typename T>
struct Add5Functor<CPUDevice, T> {
void operator()(const CPUDevice& d, typename TTypes<T>::Flat out,
typename TTypes<T>::ConstFlat in1,
typename TTypes<T>::ConstFlat in2,
typename TTypes<T>::ConstFlat in3,
typename TTypes<T>::ConstFlat in4,
typename TTypes<T>::ConstFlat in5) {
Add5EigenImpl<CPUDevice, T>::Compute(d, out, in1, in2, in3, in4, in5);
}
};
template <typename T>
struct Add6Functor<CPUDevice, T> {
void operator()(const CPUDevice& d, typename TTypes<T>::Flat out,
typename TTypes<T>::ConstFlat in1,
typename TTypes<T>::ConstFlat in2,
typename TTypes<T>::ConstFlat in3,
typename TTypes<T>::ConstFlat in4,
typename TTypes<T>::ConstFlat in5,
typename TTypes<T>::ConstFlat in6) {
Add6EigenImpl<CPUDevice, T>::Compute(d, out, in1, in2, in3, in4, in5, in6);
}
};
template <typename T>
struct Add7Functor<CPUDevice, T> {
void operator()(const CPUDevice& d, typename TTypes<T>::Flat out,
typename TTypes<T>::ConstFlat in1,
typename TTypes<T>::ConstFlat in2,
typename TTypes<T>::ConstFlat in3,
typename TTypes<T>::ConstFlat in4,
typename TTypes<T>::ConstFlat in5,
typename TTypes<T>::ConstFlat in6,
typename TTypes<T>::ConstFlat in7) {
Add7EigenImpl<CPUDevice, T>::Compute(d, out, in1, in2, in3, in4, in5, in6,
in7);
}
};
template <typename T>
struct Add8Functor<CPUDevice, T> {
void operator()(
const CPUDevice& d, typename TTypes<T>::Flat out,
typename TTypes<T>::ConstFlat in1, typename TTypes<T>::ConstFlat in2,
typename TTypes<T>::ConstFlat in3, typename TTypes<T>::ConstFlat in4,
typename TTypes<T>::ConstFlat in5, typename TTypes<T>::ConstFlat in6,
typename TTypes<T>::ConstFlat in7, typename TTypes<T>::ConstFlat in8) {
Add8EigenImpl<CPUDevice, T>::Compute(d, out, in1, in2, in3, in4, in5, in6,
in7, in8);
}
};
template <typename T>
struct Add8pFunctor<CPUDevice, T> {
void operator()(
const CPUDevice& d, typename TTypes<T>::Flat out,
typename TTypes<T>::ConstFlat in1, typename TTypes<T>::ConstFlat in2,
typename TTypes<T>::ConstFlat in3, typename TTypes<T>::ConstFlat in4,
typename TTypes<T>::ConstFlat in5, typename TTypes<T>::ConstFlat in6,
typename TTypes<T>::ConstFlat in7, typename TTypes<T>::ConstFlat in8) {
Add8pEigenImpl<CPUDevice, T>::Compute(d, out, in1, in2, in3, in4, in5, in6,
in7, in8);
}
};
template <typename T>
struct Add9Functor<CPUDevice, T> {
void operator()(
const CPUDevice& d, typename TTypes<T>::Flat out,
typename TTypes<T>::ConstFlat in1, typename TTypes<T>::ConstFlat in2,
typename TTypes<T>::ConstFlat in3, typename TTypes<T>::ConstFlat in4,
typename TTypes<T>::ConstFlat in5, typename TTypes<T>::ConstFlat in6,
typename TTypes<T>::ConstFlat in7, typename TTypes<T>::ConstFlat in8,
typename TTypes<T>::ConstFlat in9) {
Add9EigenImpl<CPUDevice, T>::Compute(d, out, in1, in2, in3, in4, in5, in6,
in7, in8, in9);
}
};
} // namespace functor
#define REGISTER_ADDN(type, dev) \
REGISTER_KERNEL_BUILDER( \
Name("AddN").Device(DEVICE_##dev).TypeConstraint<type>("T"), \
AddNOp<dev##Device, type>)
#define REGISTER_ADDN_CPU(type) REGISTER_ADDN(type, CPU)
TF_CALL_NUMBER_TYPES(REGISTER_ADDN_CPU);
#undef REGISTER_ADDN_CPU
#if GOOGLE_CUDA
REGISTER_ADDN(float, GPU);
#endif // GOOGLE_CUDA
#undef REGISTER_ADDN
} // namespace tensorflow
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