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MultiLabelMarginCriterion.cu
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MultiLabelMarginCriterion.cu
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#include <THCUNN/THCUNN.h>
#include <THC/THCTensor.hpp>
#include <THCUNN/common.h>
#include <THC/THCReduceApplyUtils.cuh>
#include <TH/THHalf.h>
#include <THC/THCNumerics.cuh>
#include <c10/macros/Macros.h>
#include <thrust/functional.h>
#define MULTILABELMARGIN_THREADS 1024
template <typename Dtype, typename Acctype>
#if defined(__HIP_PLATFORM_HCC__)
C10_LAUNCH_BOUNDS_1(MULTILABELMARGIN_THREADS)
#endif
__global__ void cunn_MultiLabelMarginCriterion_updateOutput_kernel(Dtype *output,
Dtype *input,
THCIndex_t *target,
Dtype *istarget,
int nframe,
int dim,
int sizeaverage)
{
// Temporary sums (for mapreduce)
__shared__ Acctype sums[MULTILABELMARGIN_THREADS];
// vectors:
int k = blockIdx.x;
Dtype *input_k = input + k*dim;
THCIndex_t *target_k = target + k*dim;
Dtype *output_k = output + k;
Dtype *istarget_k = istarget + k*dim;
// zero istarget
for (int d = threadIdx.x; d < dim; d += blockDim.x) {
istarget_k[d] = ScalarConvert<int, Dtype>::to(0);
}
__syncthreads();
// mark targets in istarget
if (threadIdx.x == 0) {
for (int dt = 0; dt < dim; dt++) {
int target_idx = target_k[dt];
if (target_idx < 0) break;
istarget_k[target_idx] = ScalarConvert<int, Dtype>::to(1);
}
}
__syncthreads();
// iterate over targets
Acctype sum = 0;
for (int dt = 0; dt < dim; dt++) {
// next target:
int target_idx = target_k[dt];
if (target_idx < 0) break;
// current value for target
Dtype input_target_k = input_k[target_idx];
// compare to all inputs (multithreaded):
for (int d = threadIdx.x; d < dim; d += blockDim.x) {
// contribute to loss only if not a target
if (!ScalarConvert<Dtype, int>::to(istarget_k[d])) {
Dtype z = 1 - input_target_k + input_k[d];
if (z > 0)
sum += z;
}
}
}
// reduce
Acctype totalSum = reduceBlock(sums, blockDim.x, sum, thrust::plus<Acctype>(), (Acctype)0);
if (threadIdx.x == 0) {
if (sizeaverage) {
*output_k = ScalarConvert<Acctype, Dtype>::to((totalSum / dim) / nframe);
} else {
*output_k = ScalarConvert<Acctype, Dtype>::to(totalSum / dim);
}
}
}
template <typename Dtype, typename Acctype>
#if defined(__HIP_PLATFORM_HCC__)
C10_LAUNCH_BOUNDS_1(MULTILABELMARGIN_THREADS)
#endif
__global__ void cunn_MultiLabelMarginCriterion_updateGradInput_kernel(Dtype *gradInput,
Dtype *gradOutput,
Dtype *input,
THCIndex_t *target,
Dtype *istarget,
int nframe,
int dim,
int sizeaverage,
int reduce)
{
// Temporary sums (for mapreduce)
__shared__ Acctype sums[MULTILABELMARGIN_THREADS];
// vectors:
int k = blockIdx.x;
Dtype *input_k = input + k*dim;
Dtype *gradInput_k = gradInput + k*dim;
THCIndex_t *target_k = target + k*dim;
Dtype *istarget_k = istarget + k*dim;
Dtype *gradOutput_k = gradOutput;
if (!reduce) {
gradOutput_k += k;
}
// gain:
Dtype g = ScalarConvert<Acctype, Dtype>::to( sizeaverage && reduce ? 1./((Acctype)(nframe*dim)) : 1./((Acctype)dim) );
// zero gradients:
for (int d = threadIdx.x; d < dim; d += blockDim.x) {
gradInput_k[d] = ScalarConvert<int, Dtype>::to(0);
}
__syncthreads();
// iterate over targets
for (int dt = 0; dt < dim; dt++) {
// next target:
int target_idx = (int)target_k[dt];
if (target_idx < 0) break;
// current value for target
Dtype input_target_k = input_k[target_idx];
// compare to all inputs (multithreaded):
Acctype sum = 0;
for (int d = threadIdx.x; d < dim; d += blockDim.x) {
// contribute to loss only if not a target
if (!ScalarConvert<Dtype, int>::to(istarget_k[d])) {
Dtype z = 1 - input_target_k + input_k[d];
if (z > 0) {
sum -= g;
gradInput_k[d] += g;
}
}
}
__syncthreads();
// reduce sum
Acctype totalSum = reduceBlock(sums, blockDim.x, sum, thrust::plus<Acctype>(), (Acctype)0);
if (threadIdx.x == 0) {
gradInput_k[target_idx] += ScalarConvert<Acctype, Dtype>::to(totalSum);
}
}
for (int d = threadIdx.x; d < dim; d += blockDim.x) {
gradInput_k[d] *= *gradOutput_k;
}
}
#include <THCUNN/generic/MultiLabelMarginCriterion.cu>
#include <THC/THCGenerateFloatTypes.h>
#include <THCUNN/generic/MultiLabelMarginCriterion.cu>
#include <THC/THCGenerateBFloat16Type.h>
#undef MULTILABELMARGIN_THREADS