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ActivationLogSigmoidKernel.cu
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ActivationLogSigmoidKernel.cu
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#define TORCH_ASSERT_NO_OPERATORS
#define _USE_MATH_DEFINES
#include <ATen/native/Activation.h>
#include <cmath>
#include <thrust/tuple.h>
#include <ATen/AccumulateType.h>
#include <ATen/Dispatch.h>
#include <ATen/core/TensorBase.h>
#include <c10/core/Scalar.h>
#include <c10/cuda/CUDAMathCompat.h>
#include <ATen/cuda/ApplyGridUtils.cuh>
#include <ATen/cuda/detail/OffsetCalculator.cuh>
#include <ATen/native/cuda/Loops.cuh>
namespace at::native {
// -----------------------------------
// log_sigmoid forward
// -----------------------------------
void launch_log_sigmoid_forward_kernel(TensorIteratorBase& iter) {
AT_DISPATCH_FLOATING_TYPES_AND2(
kHalf, kBFloat16, iter.common_dtype(), "log_sigmoid_forward_cuda", [&] {
using opmath_t = at::opmath_type<scalar_t>;
gpu_kernel(iter, [] GPU_LAMBDA(scalar_t in_) -> scalar_t {
const opmath_t in = in_;
const auto min = std::min(opmath_t(0), in);
const auto z = std::exp(-std::abs(in));
return min - std::log1p(z);
});
});
}
namespace {
// -----------------------------------
// log_sigmoid backward
// -----------------------------------
void log_sigmoid_backward_kernel(TensorIterator& iter) {
AT_DISPATCH_FLOATING_TYPES_AND2(
kHalf, kBFloat16, iter.common_dtype(), "log_sigmoid_backward_cuda", [&] {
using opmath_t = at::opmath_type<scalar_t>;
gpu_kernel(
iter, [] GPU_LAMBDA(scalar_t in_, scalar_t grad_out_) -> scalar_t {
const opmath_t in = in_;
const opmath_t grad_out = grad_out_;
auto in_negative = in < opmath_t(0);
auto max_deriv = in_negative ? opmath_t(1) : opmath_t(0);
auto sign = in_negative ? opmath_t(1) : -opmath_t(1);
const auto z = std::exp(-std::abs(in));
return grad_out * (max_deriv - sign * (z / (opmath_t(1) + z)));
});
});
}
} // namespace
REGISTER_DISPATCH(log_sigmoid_backward_stub, &log_sigmoid_backward_kernel);
} // namespace at::native