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hardshrink.cu
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#include <algorithm>
#include <cuda_fp16.h>
#include <cuda_runtime.h>
#include <float.h>
#include <stdio.h>
#include <stdlib.h>
#include <torch/extension.h>
#include <torch/types.h>
#include <vector>
#define WARP_SIZE 32
#define INT4(value) (reinterpret_cast<int4 *>(&(value))[0])
#define FLOAT4(value) (reinterpret_cast<float4 *>(&(value))[0])
#define HALF2(value) (reinterpret_cast<half2 *>(&(value))[0])
#define BFLOAT2(value) (reinterpret_cast<__nv_bfloat162 *>(&(value))[0])
#define LDST128BITS(value) (reinterpret_cast<float4 *>(&(value))[0])
// 定义全局 LAMBD 值
#define LAMBD 0.5f
// 定义 CHECK_TORCH_TENSOR_DTYPE 宏
#define CHECK_TORCH_TENSOR_DTYPE(T, th_type) \
if (((T).options().dtype() != (th_type))) { \
std::cout << "Tensor Info:" << (T).options() << std::endl; \
throw std::runtime_error("Tensor dtype must be " #th_type); \
}
// 定义 TORCH_BINDING_COMMON_EXTENSION 宏
#define STRINGFY(str) #str
#define TORCH_BINDING_COMMON_EXTENSION(func) \
m.def(STRINGFY(func), &func, STRINGFY(func));
// HARDSHRINK 计算函数
// -------------------------------------- FP32
// --------------------------------------
__device__ __forceinline__ float hardshrink(float x) {
if (x > LAMBD || x < -LAMBD) {
return x;
} else {
return 0;
}
}
// -------------------------------------- FP16
// --------------------------------------
__device__ __forceinline__ half hardshrink_half(half x) {
if (x > __float2half(LAMBD) || x < __float2half(-LAMBD)) {
return x;
} else {
return __float2half(0.f);
}
}
// CUDA 核函数
// -------------------------------------- FP32
// --------------------------------------
__global__ void hardshrink_f32_kernel(float *x, float *y, int N) {
int idx = blockIdx.x * blockDim.x + threadIdx.x;
if (idx < N)
y[idx] = hardshrink(x[idx]);
}
__global__ void hardshrink_f32x4_kernel(float *x, float *y, int N) {
int idx = (blockIdx.x * blockDim.x + threadIdx.x) * 4;
if (idx < N) {
float4 reg_x = FLOAT4(x[idx]);
float4 reg_y;
reg_y.x = hardshrink(reg_x.x);
reg_y.y = hardshrink(reg_x.y);
reg_y.z = hardshrink(reg_x.z);
reg_y.w = hardshrink(reg_x.w);
FLOAT4(y[idx]) = reg_y;
}
}
// -------------------------------------- FP16
// --------------------------------------
__global__ void hardshrink_f16_kernel(half *x, half *y, int N) {
int idx = blockIdx.x * blockDim.x + threadIdx.x;
if (idx < N)
y[idx] = hardshrink_half(x[idx]);
}
__global__ void hardshrink_f16x2_kernel(half *x, half *y, int N) {
int idx = 2 * (blockIdx.x * blockDim.x + threadIdx.x);
if (idx < N) {
half2 reg_x = HALF2(x[idx]);
half2 reg_y;
reg_y.x = hardshrink_half(reg_x.x);
reg_y.y = hardshrink_half(reg_x.y);
HALF2(y[idx]) = reg_y;
}
}
__global__ void hardshrink_f16x8_kernel(half *x, half *y, int N) {
int idx = 8 * (blockIdx.x * blockDim.x + threadIdx.x);
half2 reg_x_0 = HALF2(x[idx + 0]);
half2 reg_x_1 = HALF2(x[idx + 2]);
half2 reg_x_2 = HALF2(x[idx + 4]);
half2 reg_x_3 = HALF2(x[idx + 6]);
half2 reg_y_0, reg_y_1, reg_y_2, reg_y_3;
reg_y_0.x = hardshrink_half(reg_x_0.x);
reg_y_0.y = hardshrink_half(reg_x_0.y);
reg_y_1.x = hardshrink_half(reg_x_1.x);
reg_y_1.y = hardshrink_half(reg_x_1.y);
reg_y_2.x = hardshrink_half(reg_x_2.x);
reg_y_2.y = hardshrink_half(reg_x_2.y);
reg_y_3.x = hardshrink_half(reg_x_3.x);
reg_y_3.y = hardshrink_half(reg_x_3.y);
if ((idx + 0) < N) {
HALF2(y[idx + 0]) = reg_y_0;
}
if ((idx + 2) < N) {
HALF2(y[idx + 2]) = reg_y_1;
}
if ((idx + 4) < N) {
HALF2(y[idx + 4]) = reg_y_2;
}
if ((idx + 6) < N) {
HALF2(y[idx + 6]) = reg_y_3;
}
}
__global__ void hardshrink_f16x8_pack_kernel(half *x, half *y, int N) {
int idx = 8 * (blockIdx.x * blockDim.x + threadIdx.x);
half pack_x[8], pack_y[8];
LDST128BITS(pack_x[0]) = LDST128BITS(x[idx]);
#pragma unroll
for (int i = 0; i < 8; i++) {
pack_y[i] = hardshrink_half(pack_x[i]);
}
if ((idx + 7) < N) {
LDST128BITS(y[idx]) = LDST128BITS(pack_y[0]);
}
}
// PyTorch 绑定代码
#define TORCH_BINDING_HARDSHRINK(packed_type, th_type, element_type, \
n_elements) \
void hardshrink_##packed_type(torch::Tensor x, torch::Tensor y) { \
CHECK_TORCH_TENSOR_DTYPE(x, (th_type)) \
CHECK_TORCH_TENSOR_DTYPE(y, (th_type)) \
const int ndim = x.dim(); \
if (ndim != 2) { \
int N = 1; \
for (int i = 0; i < ndim; ++i) { \
N *= x.size(i); \
} \
dim3 block(256 / (n_elements)); \
dim3 grid((N + 256 - 1) / 256); \
hardshrink_##packed_type##_kernel<<<grid, block>>>( \
reinterpret_cast<element_type *>(x.data_ptr()), \
reinterpret_cast<element_type *>(y.data_ptr()), N); \
} else { \
const int S = x.size(0); \
const int K = x.size(1); \
const int N = S * K; \
if ((K / (n_elements)) <= 1024) { \
dim3 block(K / (n_elements)); \
dim3 grid(S); \
hardshrink_##packed_type##_kernel<<<grid, block>>>( \
reinterpret_cast<element_type *>(x.data_ptr()), \
reinterpret_cast<element_type *>(y.data_ptr()), N); \
} else { \
int N = 1; \
for (int i = 0; i < ndim; ++i) { \
N *= x.size(i); \
} \
dim3 block(256 / (n_elements)); \
dim3 grid((N + 256 - 1) / 256); \
hardshrink_##packed_type##_kernel<<<grid, block>>>( \
reinterpret_cast<element_type *>(x.data_ptr()), \
reinterpret_cast<element_type *>(y.data_ptr()), N); \
} \
} \
}
TORCH_BINDING_HARDSHRINK(f32, torch::kFloat32, float, 1)
TORCH_BINDING_HARDSHRINK(f32x4, torch::kFloat32, float, 4)
TORCH_BINDING_HARDSHRINK(f16, torch::kHalf, half, 1)
TORCH_BINDING_HARDSHRINK(f16x2, torch::kHalf, half, 2)
TORCH_BINDING_HARDSHRINK(f16x8, torch::kHalf, half, 8)
TORCH_BINDING_HARDSHRINK(f16x8_pack, torch::kHalf, half, 8)
PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
TORCH_BINDING_COMMON_EXTENSION(hardshrink_f32)
TORCH_BINDING_COMMON_EXTENSION(hardshrink_f32x4)
TORCH_BINDING_COMMON_EXTENSION(hardshrink_f16)
TORCH_BINDING_COMMON_EXTENSION(hardshrink_f16x2)
TORCH_BINDING_COMMON_EXTENSION(hardshrink_f16x8)
TORCH_BINDING_COMMON_EXTENSION(hardshrink_f16x8_pack)
}