Commit 643b46d3 authored by zww's avatar zww
Browse files

Replace #include <torch/extension.h> by #include <torch/types.h> to avoid cuda bug

parent 397a9280
......@@ -7,8 +7,8 @@
#include <assert.h>
#include <math.h>
#include <stdio.h>
#include <torch/extension.h>
#include <torch/serialize/tensor.h>
#include <torch/types.h>
#define THREADS_PER_BLOCK 256
#define DIVUP(m, n) ((m) / (n) + ((m) % (n) > 0))
......
//Modified from
//https://github.com/sshaoshuai/PCDet/blob/master/pcdet/ops/roiaware_pool3d/src/roiaware_pool3d_kernel.cu
//RoI-aware point cloud feature pooling
//Written by Shaoshuai Shi
//All Rights Reserved 2019.
// Modified from
// https://github.com/sshaoshuai/PCDet/blob/master/pcdet/ops/roiaware_pool3d/src/roiaware_pool3d_kernel.cu
// RoI-aware point cloud feature pooling
// Written by Shaoshuai Shi
// All Rights Reserved 2019.
#include <torch/serialize/tensor.h>
#include <torch/extension.h>
#include <assert.h>
#include <math.h>
#include <stdio.h>
#include <torch/serialize/tensor.h>
#include <torch/types.h>
#define THREADS_PER_BLOCK 256
#define DIVUP(m,n) ((m) / (n) + ((m) % (n) > 0))
#define DIVUP(m, n) ((m) / (n) + ((m) % (n) > 0))
// #define DEBUG
__device__ inline void lidar_to_local_coords(float shift_x, float shift_y, float rz, float &local_x, float &local_y){
// should rotate pi/2 + alpha to translate LiDAR to local
float rot_angle = rz + M_PI / 2;
float cosa = cos(rot_angle), sina = sin(rot_angle);
local_x = shift_x * cosa + shift_y * (-sina);
local_y = shift_x * sina + shift_y * cosa;
__device__ inline void lidar_to_local_coords(float shift_x, float shift_y,
float rz, float &local_x,
float &local_y) {
// should rotate pi/2 + alpha to translate LiDAR to local
float rot_angle = rz + M_PI / 2;
float cosa = cos(rot_angle), sina = sin(rot_angle);
local_x = shift_x * cosa + shift_y * (-sina);
local_y = shift_x * sina + shift_y * cosa;
}
__device__ inline int check_pt_in_box3d(const float *pt, const float *box3d, float &local_x, float &local_y){
// param pt: (x, y, z)
// param box3d: (cx, cy, cz, w, l, h, rz) in LiDAR coordinate, cz in the bottom center
float x = pt[0], y = pt[1], z = pt[2];
float cx = box3d[0], cy = box3d[1], cz = box3d[2];
float w = box3d[3], l = box3d[4], h = box3d[5], rz = box3d[6];
cz += h / 2.0; // shift to the center since cz in box3d is the bottom center
if (fabsf(z - cz) > h / 2.0) return 0;
lidar_to_local_coords(x - cx, y - cy, rz, local_x, local_y);
float in_flag = (local_x > -l / 2.0) & (local_x < l / 2.0) & (local_y > -w / 2.0) & (local_y < w / 2.0);
return in_flag;
__device__ inline int check_pt_in_box3d(const float *pt, const float *box3d,
float &local_x, float &local_y) {
// param pt: (x, y, z)
// param box3d: (cx, cy, cz, w, l, h, rz) in LiDAR coordinate, cz in the
// bottom center
float x = pt[0], y = pt[1], z = pt[2];
float cx = box3d[0], cy = box3d[1], cz = box3d[2];
float w = box3d[3], l = box3d[4], h = box3d[5], rz = box3d[6];
cz += h / 2.0; // shift to the center since cz in box3d is the bottom center
if (fabsf(z - cz) > h / 2.0) return 0;
lidar_to_local_coords(x - cx, y - cy, rz, local_x, local_y);
float in_flag = (local_x > -l / 2.0) & (local_x < l / 2.0) &
(local_y > -w / 2.0) & (local_y < w / 2.0);
return in_flag;
}
__global__ void generate_pts_mask_for_box3d(int boxes_num, int pts_num, int out_x, int out_y, int out_z,
const float *rois, const float *pts, int *pts_mask){
// params rois: (N, 7) [x, y, z, w, l, h, rz] in LiDAR coordinate
// params pts: (npoints, 3) [x, y, z]
// params pts_mask: (N, npoints): -1 means point doesnot in this box, otherwise: encode (x_idxs, y_idxs, z_idxs) by binary bit
int pt_idx = blockIdx.x * blockDim.x + threadIdx.x;
int box_idx = blockIdx.y;
if (pt_idx >= pts_num || box_idx >= boxes_num) return;
pts += pt_idx * 3;
rois += box_idx * 7;
pts_mask += box_idx * pts_num + pt_idx;
float local_x = 0, local_y = 0;
int cur_in_flag = check_pt_in_box3d(pts, rois, local_x, local_y);
pts_mask[0] = -1;
if (cur_in_flag > 0){
float local_z = pts[2] - rois[2];
float w = rois[3], l = rois[4], h = rois[5];
float x_res = l / out_x;
float y_res = w / out_y;
float z_res = h / out_z;
unsigned int x_idx = int((local_x + l / 2) / x_res);
unsigned int y_idx = int((local_y + w / 2) / y_res);
unsigned int z_idx = int(local_z / z_res);
x_idx = min(max(x_idx, 0), out_x - 1);
y_idx = min(max(y_idx, 0), out_y - 1);
z_idx = min(max(z_idx, 0), out_z - 1);
unsigned int idx_encoding = (x_idx << 16) + (y_idx << 8) + z_idx;
__global__ void generate_pts_mask_for_box3d(int boxes_num, int pts_num,
int out_x, int out_y, int out_z,
const float *rois, const float *pts,
int *pts_mask) {
// params rois: (N, 7) [x, y, z, w, l, h, rz] in LiDAR coordinate
// params pts: (npoints, 3) [x, y, z]
// params pts_mask: (N, npoints): -1 means point doesnot in this box,
// otherwise: encode (x_idxs, y_idxs, z_idxs) by binary bit
int pt_idx = blockIdx.x * blockDim.x + threadIdx.x;
int box_idx = blockIdx.y;
if (pt_idx >= pts_num || box_idx >= boxes_num) return;
pts += pt_idx * 3;
rois += box_idx * 7;
pts_mask += box_idx * pts_num + pt_idx;
float local_x = 0, local_y = 0;
int cur_in_flag = check_pt_in_box3d(pts, rois, local_x, local_y);
pts_mask[0] = -1;
if (cur_in_flag > 0) {
float local_z = pts[2] - rois[2];
float w = rois[3], l = rois[4], h = rois[5];
float x_res = l / out_x;
float y_res = w / out_y;
float z_res = h / out_z;
unsigned int x_idx = int((local_x + l / 2) / x_res);
unsigned int y_idx = int((local_y + w / 2) / y_res);
unsigned int z_idx = int(local_z / z_res);
x_idx = min(max(x_idx, 0), out_x - 1);
y_idx = min(max(y_idx, 0), out_y - 1);
z_idx = min(max(z_idx, 0), out_z - 1);
unsigned int idx_encoding = (x_idx << 16) + (y_idx << 8) + z_idx;
#ifdef DEBUG
printf("mask: pts_%d(%.3f, %.3f, %.3f), local(%.3f, %.3f, %.3f), idx(%d, %d, %d), res(%.3f, %.3f, %.3f), idx_encoding=%x\n",
pt_idx, pts[0], pts[1], pts[2], local_x, local_y, local_z, x_idx, y_idx, z_idx, x_res, y_res, z_res, idx_encoding);
printf(
"mask: pts_%d(%.3f, %.3f, %.3f), local(%.3f, %.3f, %.3f), idx(%d, %d, "
"%d), res(%.3f, %.3f, %.3f), idx_encoding=%x\n",
pt_idx, pts[0], pts[1], pts[2], local_x, local_y, local_z, x_idx, y_idx,
z_idx, x_res, y_res, z_res, idx_encoding);
#endif
pts_mask[0] = idx_encoding;
}
pts_mask[0] = idx_encoding;
}
}
__global__ void collect_inside_pts_for_box3d(int boxes_num, int pts_num, int max_pts_each_voxel,
int out_x, int out_y, int out_z, const int *pts_mask, int *pts_idx_of_voxels){
// params pts_mask: (N, npoints) 0 or 1
// params pts_idx_of_voxels: (N, out_x, out_y, out_z, max_pts_each_voxel)
int box_idx = blockIdx.x * blockDim.x + threadIdx.x;
if (box_idx >= boxes_num) return;
int max_num_pts = max_pts_each_voxel - 1; // index 0 is the counter
pts_idx_of_voxels += box_idx * out_x * out_y * out_z * max_pts_each_voxel;
for (int k = 0; k < pts_num; k++){
if (pts_mask[box_idx * pts_num + k] != -1){
unsigned int idx_encoding = pts_mask[box_idx * pts_num + k];
unsigned int x_idx = (idx_encoding >> 16) & 0xFF;
unsigned int y_idx = (idx_encoding >> 8) & 0xFF;
unsigned int z_idx = idx_encoding & 0xFF;
unsigned int base_offset = x_idx * out_y * out_z * max_pts_each_voxel + y_idx * out_z * max_pts_each_voxel + z_idx * max_pts_each_voxel;
unsigned int cnt = pts_idx_of_voxels[base_offset];
if (cnt < max_num_pts){
pts_idx_of_voxels[base_offset + cnt + 1] = k;
pts_idx_of_voxels[base_offset]++;
}
__global__ void collect_inside_pts_for_box3d(int boxes_num, int pts_num,
int max_pts_each_voxel, int out_x,
int out_y, int out_z,
const int *pts_mask,
int *pts_idx_of_voxels) {
// params pts_mask: (N, npoints) 0 or 1
// params pts_idx_of_voxels: (N, out_x, out_y, out_z, max_pts_each_voxel)
int box_idx = blockIdx.x * blockDim.x + threadIdx.x;
if (box_idx >= boxes_num) return;
int max_num_pts = max_pts_each_voxel - 1; // index 0 is the counter
pts_idx_of_voxels += box_idx * out_x * out_y * out_z * max_pts_each_voxel;
for (int k = 0; k < pts_num; k++) {
if (pts_mask[box_idx * pts_num + k] != -1) {
unsigned int idx_encoding = pts_mask[box_idx * pts_num + k];
unsigned int x_idx = (idx_encoding >> 16) & 0xFF;
unsigned int y_idx = (idx_encoding >> 8) & 0xFF;
unsigned int z_idx = idx_encoding & 0xFF;
unsigned int base_offset = x_idx * out_y * out_z * max_pts_each_voxel +
y_idx * out_z * max_pts_each_voxel +
z_idx * max_pts_each_voxel;
unsigned int cnt = pts_idx_of_voxels[base_offset];
if (cnt < max_num_pts) {
pts_idx_of_voxels[base_offset + cnt + 1] = k;
pts_idx_of_voxels[base_offset]++;
}
#ifdef DEBUG
printf("collect: pts_%d, idx(%d, %d, %d), idx_encoding=%x\n",
k, x_idx, y_idx, z_idx, idx_encoding);
printf("collect: pts_%d, idx(%d, %d, %d), idx_encoding=%x\n", k, x_idx,
y_idx, z_idx, idx_encoding);
#endif
}
}
}
}
__global__ void roiaware_maxpool3d(int boxes_num, int pts_num, int channels, int max_pts_each_voxel, int out_x,
int out_y, int out_z, const float *pts_feature, const int *pts_idx_of_voxels, float *pooled_features, int *argmax){
// params pts_feature: (npoints, C)
// params pts_idx_of_voxels: (N, out_x, out_y, out_z, max_pts_each_voxel), index 0 is the counter
// params pooled_features: (N, out_x, out_y, out_z, C)
// params argmax: (N, out_x, out_y, out_z, C)
int box_idx = blockIdx.z;
int channel_idx = blockIdx.y;
int voxel_idx_flat = blockIdx.x * blockDim.x + threadIdx.x;
int x_idx = voxel_idx_flat / (out_y * out_z);
int y_idx = (voxel_idx_flat - x_idx * (out_y * out_z)) / out_z;
int z_idx = voxel_idx_flat % out_z;
if (box_idx >= boxes_num || channel_idx >= channels|| x_idx >= out_x || y_idx >= out_y || z_idx >= out_z) return;
__global__ void roiaware_maxpool3d(int boxes_num, int pts_num, int channels,
int max_pts_each_voxel, int out_x, int out_y,
int out_z, const float *pts_feature,
const int *pts_idx_of_voxels,
float *pooled_features, int *argmax) {
// params pts_feature: (npoints, C)
// params pts_idx_of_voxels: (N, out_x, out_y, out_z, max_pts_each_voxel),
// index 0 is the counter params pooled_features: (N, out_x, out_y, out_z, C)
// params argmax: (N, out_x, out_y, out_z, C)
int box_idx = blockIdx.z;
int channel_idx = blockIdx.y;
int voxel_idx_flat = blockIdx.x * blockDim.x + threadIdx.x;
int x_idx = voxel_idx_flat / (out_y * out_z);
int y_idx = (voxel_idx_flat - x_idx * (out_y * out_z)) / out_z;
int z_idx = voxel_idx_flat % out_z;
if (box_idx >= boxes_num || channel_idx >= channels || x_idx >= out_x ||
y_idx >= out_y || z_idx >= out_z)
return;
#ifdef DEBUG
printf("src pts_idx_of_voxels: (%p, ), argmax: %p\n", pts_idx_of_voxels, argmax);
printf("src pts_idx_of_voxels: (%p, ), argmax: %p\n", pts_idx_of_voxels,
argmax);
#endif
int offset_base = x_idx * out_y * out_z + y_idx * out_z + z_idx;
pts_idx_of_voxels += box_idx * out_x * out_y * out_z * max_pts_each_voxel + offset_base * max_pts_each_voxel;
pooled_features += box_idx * out_x * out_y * out_z * channels + offset_base * channels + channel_idx;
argmax += box_idx * out_x * out_y * out_z * channels + offset_base * channels + channel_idx;
int offset_base = x_idx * out_y * out_z + y_idx * out_z + z_idx;
pts_idx_of_voxels += box_idx * out_x * out_y * out_z * max_pts_each_voxel +
offset_base * max_pts_each_voxel;
pooled_features += box_idx * out_x * out_y * out_z * channels +
offset_base * channels + channel_idx;
argmax += box_idx * out_x * out_y * out_z * channels +
offset_base * channels + channel_idx;
int argmax_idx = -1;
float max_val = -1e50;
int argmax_idx = -1;
float max_val = -1e50;
int total_pts = pts_idx_of_voxels[0];
int total_pts = pts_idx_of_voxels[0];
for (int k = 1; k <= total_pts; k++){
if (pts_feature[pts_idx_of_voxels[k] * channels + channel_idx] > max_val){
max_val = pts_feature[pts_idx_of_voxels[k] * channels + channel_idx];
argmax_idx = pts_idx_of_voxels[k];
}
for (int k = 1; k <= total_pts; k++) {
if (pts_feature[pts_idx_of_voxels[k] * channels + channel_idx] > max_val) {
max_val = pts_feature[pts_idx_of_voxels[k] * channels + channel_idx];
argmax_idx = pts_idx_of_voxels[k];
}
}
if (argmax_idx != -1){
pooled_features[0] = max_val;
}
argmax[0] = argmax_idx;
if (argmax_idx != -1) {
pooled_features[0] = max_val;
}
argmax[0] = argmax_idx;
#ifdef DEBUG
printf("channel_%d idx(%d, %d, %d), argmax_idx=(%d, %.3f), total=%d, after pts_idx: %p, argmax: (%p, %d)\n",
channel_idx, x_idx, y_idx, z_idx, argmax_idx, max_val, total_pts, pts_idx_of_voxels, argmax, argmax_idx);
printf(
"channel_%d idx(%d, %d, %d), argmax_idx=(%d, %.3f), total=%d, after "
"pts_idx: %p, argmax: (%p, %d)\n",
channel_idx, x_idx, y_idx, z_idx, argmax_idx, max_val, total_pts,
pts_idx_of_voxels, argmax, argmax_idx);
#endif
}
__global__ void roiaware_avgpool3d(int boxes_num, int pts_num, int channels, int max_pts_each_voxel, int out_x,
int out_y, int out_z, const float *pts_feature, const int *pts_idx_of_voxels, float *pooled_features){
// params pts_feature: (npoints, C)
// params pts_idx_of_voxels: (N, out_x, out_y, out_z, max_pts_each_voxel), index 0 is the counter
// params pooled_features: (N, out_x, out_y, out_z, C)
// params argmax: (N, out_x, out_y, out_z, C)
int box_idx = blockIdx.z;
int channel_idx = blockIdx.y;
int voxel_idx_flat = blockIdx.x * blockDim.x + threadIdx.x;
int x_idx = voxel_idx_flat / (out_y * out_z);
int y_idx = (voxel_idx_flat - x_idx * (out_y * out_z)) / out_z;
int z_idx = voxel_idx_flat % out_z;
if (box_idx >= boxes_num || channel_idx >= channels|| x_idx >= out_x || y_idx >= out_y || z_idx >= out_z) return;
int offset_base = x_idx * out_y * out_z + y_idx * out_z + z_idx;
pts_idx_of_voxels += box_idx * out_x * out_y * out_z * max_pts_each_voxel + offset_base * max_pts_each_voxel;
pooled_features += box_idx * out_x * out_y * out_z * channels + offset_base * channels + channel_idx;
float sum_val = 0;
int total_pts = pts_idx_of_voxels[0];
for (int k = 1; k <= total_pts; k++){
sum_val += pts_feature[pts_idx_of_voxels[k] * channels + channel_idx];
}
if (total_pts > 0){
pooled_features[0] = sum_val / total_pts;
}
__global__ void roiaware_avgpool3d(int boxes_num, int pts_num, int channels,
int max_pts_each_voxel, int out_x, int out_y,
int out_z, const float *pts_feature,
const int *pts_idx_of_voxels,
float *pooled_features) {
// params pts_feature: (npoints, C)
// params pts_idx_of_voxels: (N, out_x, out_y, out_z, max_pts_each_voxel),
// index 0 is the counter params pooled_features: (N, out_x, out_y, out_z, C)
// params argmax: (N, out_x, out_y, out_z, C)
int box_idx = blockIdx.z;
int channel_idx = blockIdx.y;
int voxel_idx_flat = blockIdx.x * blockDim.x + threadIdx.x;
int x_idx = voxel_idx_flat / (out_y * out_z);
int y_idx = (voxel_idx_flat - x_idx * (out_y * out_z)) / out_z;
int z_idx = voxel_idx_flat % out_z;
if (box_idx >= boxes_num || channel_idx >= channels || x_idx >= out_x ||
y_idx >= out_y || z_idx >= out_z)
return;
int offset_base = x_idx * out_y * out_z + y_idx * out_z + z_idx;
pts_idx_of_voxels += box_idx * out_x * out_y * out_z * max_pts_each_voxel +
offset_base * max_pts_each_voxel;
pooled_features += box_idx * out_x * out_y * out_z * channels +
offset_base * channels + channel_idx;
float sum_val = 0;
int total_pts = pts_idx_of_voxels[0];
for (int k = 1; k <= total_pts; k++) {
sum_val += pts_feature[pts_idx_of_voxels[k] * channels + channel_idx];
}
if (total_pts > 0) {
pooled_features[0] = sum_val / total_pts;
}
}
void roiaware_pool3d_launcher(int boxes_num, int pts_num, int channels, int max_pts_each_voxel, int out_x, int out_y, int out_z,
const float *rois, const float *pts, const float *pts_feature, int *argmax, int *pts_idx_of_voxels, float *pooled_features, int pool_method){
// params rois: (N, 7) [x, y, z, w, l, h, rz] in LiDAR coordinate
// params pts: (npoints, 3) [x, y, z] in LiDAR coordinate
// params pts_feature: (npoints, C)
// params argmax: (N, out_x, out_y, out_z, C)
// params pts_idx_of_voxels: (N, out_x, out_y, out_z, max_pts_each_voxel)
// params pooled_features: (N, out_x, out_y, out_z, C)
// params pool_method: 0: max_pool 1: avg_pool
int *pts_mask = NULL;
cudaMalloc(&pts_mask, boxes_num * pts_num * sizeof(int)); // (N, M)
cudaMemset(pts_mask, -1, boxes_num * pts_num * sizeof(int));
dim3 blocks_mask(DIVUP(pts_num, THREADS_PER_BLOCK), boxes_num);
dim3 threads(THREADS_PER_BLOCK);
generate_pts_mask_for_box3d<<<blocks_mask, threads>>>(boxes_num, pts_num, out_x, out_y, out_z, rois, pts, pts_mask);
// TODO: Merge the collect and pool functions, SS
dim3 blocks_collect(DIVUP(boxes_num, THREADS_PER_BLOCK));
collect_inside_pts_for_box3d<<<blocks_collect, threads>>>(boxes_num, pts_num, max_pts_each_voxel,
out_x, out_y, out_z, pts_mask, pts_idx_of_voxels);
dim3 blocks_pool(DIVUP(out_x * out_y * out_z, THREADS_PER_BLOCK), channels, boxes_num);
if (pool_method == 0){
roiaware_maxpool3d<<<blocks_pool, threads>>>(boxes_num, pts_num, channels, max_pts_each_voxel, out_x, out_y, out_z,
pts_feature, pts_idx_of_voxels, pooled_features, argmax);
}
else if (pool_method == 1){
roiaware_avgpool3d<<<blocks_pool, threads>>>(boxes_num, pts_num, channels, max_pts_each_voxel, out_x, out_y, out_z,
pts_feature, pts_idx_of_voxels, pooled_features);
}
cudaFree(pts_mask);
void roiaware_pool3d_launcher(int boxes_num, int pts_num, int channels,
int max_pts_each_voxel, int out_x, int out_y,
int out_z, const float *rois, const float *pts,
const float *pts_feature, int *argmax,
int *pts_idx_of_voxels, float *pooled_features,
int pool_method) {
// params rois: (N, 7) [x, y, z, w, l, h, rz] in LiDAR coordinate
// params pts: (npoints, 3) [x, y, z] in LiDAR coordinate
// params pts_feature: (npoints, C)
// params argmax: (N, out_x, out_y, out_z, C)
// params pts_idx_of_voxels: (N, out_x, out_y, out_z, max_pts_each_voxel)
// params pooled_features: (N, out_x, out_y, out_z, C)
// params pool_method: 0: max_pool 1: avg_pool
int *pts_mask = NULL;
cudaMalloc(&pts_mask, boxes_num * pts_num * sizeof(int)); // (N, M)
cudaMemset(pts_mask, -1, boxes_num * pts_num * sizeof(int));
dim3 blocks_mask(DIVUP(pts_num, THREADS_PER_BLOCK), boxes_num);
dim3 threads(THREADS_PER_BLOCK);
generate_pts_mask_for_box3d<<<blocks_mask, threads>>>(
boxes_num, pts_num, out_x, out_y, out_z, rois, pts, pts_mask);
// TODO: Merge the collect and pool functions, SS
dim3 blocks_collect(DIVUP(boxes_num, THREADS_PER_BLOCK));
collect_inside_pts_for_box3d<<<blocks_collect, threads>>>(
boxes_num, pts_num, max_pts_each_voxel, out_x, out_y, out_z, pts_mask,
pts_idx_of_voxels);
dim3 blocks_pool(DIVUP(out_x * out_y * out_z, THREADS_PER_BLOCK), channels,
boxes_num);
if (pool_method == 0) {
roiaware_maxpool3d<<<blocks_pool, threads>>>(
boxes_num, pts_num, channels, max_pts_each_voxel, out_x, out_y, out_z,
pts_feature, pts_idx_of_voxels, pooled_features, argmax);
} else if (pool_method == 1) {
roiaware_avgpool3d<<<blocks_pool, threads>>>(
boxes_num, pts_num, channels, max_pts_each_voxel, out_x, out_y, out_z,
pts_feature, pts_idx_of_voxels, pooled_features);
}
cudaFree(pts_mask);
#ifdef DEBUG
cudaDeviceSynchronize(); // for using printf in kernel function
cudaDeviceSynchronize(); // for using printf in kernel function
#endif
}
__global__ void roiaware_maxpool3d_backward(int boxes_num, int channels, int out_x, int out_y, int out_z,
const int *argmax, const float *grad_out, float *grad_in){
// params argmax: (N, out_x, out_y, out_z, C)
// params grad_out: (N, out_x, out_y, out_z, C)
// params grad_in: (npoints, C), return value
int box_idx = blockIdx.z;
int channel_idx = blockIdx.y;
int voxel_idx_flat = blockIdx.x * blockDim.x + threadIdx.x;
int x_idx = voxel_idx_flat / (out_y * out_z);
int y_idx = (voxel_idx_flat - x_idx * (out_y * out_z)) / out_z;
int z_idx = voxel_idx_flat % out_z;
if (box_idx >= boxes_num || channel_idx >= channels|| x_idx >= out_x || y_idx >= out_y || z_idx >= out_z) return;
int offset_base = x_idx * out_y * out_z + y_idx * out_z + z_idx;
argmax += box_idx * out_x * out_y * out_z * channels + offset_base * channels + channel_idx;
grad_out += box_idx * out_x * out_y * out_z * channels + offset_base * channels + channel_idx;
if (argmax[0] == -1) return;
atomicAdd(grad_in + argmax[0] * channels + channel_idx, grad_out[0] * 1);
__global__ void roiaware_maxpool3d_backward(int boxes_num, int channels,
int out_x, int out_y, int out_z,
const int *argmax,
const float *grad_out,
float *grad_in) {
// params argmax: (N, out_x, out_y, out_z, C)
// params grad_out: (N, out_x, out_y, out_z, C)
// params grad_in: (npoints, C), return value
int box_idx = blockIdx.z;
int channel_idx = blockIdx.y;
int voxel_idx_flat = blockIdx.x * blockDim.x + threadIdx.x;
int x_idx = voxel_idx_flat / (out_y * out_z);
int y_idx = (voxel_idx_flat - x_idx * (out_y * out_z)) / out_z;
int z_idx = voxel_idx_flat % out_z;
if (box_idx >= boxes_num || channel_idx >= channels || x_idx >= out_x ||
y_idx >= out_y || z_idx >= out_z)
return;
int offset_base = x_idx * out_y * out_z + y_idx * out_z + z_idx;
argmax += box_idx * out_x * out_y * out_z * channels +
offset_base * channels + channel_idx;
grad_out += box_idx * out_x * out_y * out_z * channels +
offset_base * channels + channel_idx;
if (argmax[0] == -1) return;
atomicAdd(grad_in + argmax[0] * channels + channel_idx, grad_out[0] * 1);
}
__global__ void roiaware_avgpool3d_backward(int boxes_num, int channels, int out_x, int out_y, int out_z,
int max_pts_each_voxel, const int *pts_idx_of_voxels, const float *grad_out, float *grad_in){
// params pts_idx_of_voxels: (N, out_x, out_y, out_z, max_pts_each_voxel)
// params grad_out: (N, out_x, out_y, out_z, C)
// params grad_in: (npoints, C), return value
int box_idx = blockIdx.z;
int channel_idx = blockIdx.y;
int voxel_idx_flat = blockIdx.x * blockDim.x + threadIdx.x;
int x_idx = voxel_idx_flat / (out_y * out_z);
int y_idx = (voxel_idx_flat - x_idx * (out_y * out_z)) / out_z;
int z_idx = voxel_idx_flat % out_z;
if (box_idx >= boxes_num || channel_idx >= channels|| x_idx >= out_x || y_idx >= out_y || z_idx >= out_z) return;
int offset_base = x_idx * out_y * out_z + y_idx * out_z + z_idx;
pts_idx_of_voxels += box_idx * out_x * out_y * out_z * max_pts_each_voxel + offset_base * max_pts_each_voxel;
grad_out += box_idx * out_x * out_y * out_z * channels + offset_base * channels + channel_idx;
int total_pts = pts_idx_of_voxels[0];
float cur_grad = 1 / fmaxf(float(total_pts), 1.0);
for (int k = 1; k <= total_pts; k++){
atomicAdd(grad_in + pts_idx_of_voxels[k] * channels + channel_idx, grad_out[0] * cur_grad);
}
__global__ void roiaware_avgpool3d_backward(int boxes_num, int channels,
int out_x, int out_y, int out_z,
int max_pts_each_voxel,
const int *pts_idx_of_voxels,
const float *grad_out,
float *grad_in) {
// params pts_idx_of_voxels: (N, out_x, out_y, out_z, max_pts_each_voxel)
// params grad_out: (N, out_x, out_y, out_z, C)
// params grad_in: (npoints, C), return value
int box_idx = blockIdx.z;
int channel_idx = blockIdx.y;
int voxel_idx_flat = blockIdx.x * blockDim.x + threadIdx.x;
int x_idx = voxel_idx_flat / (out_y * out_z);
int y_idx = (voxel_idx_flat - x_idx * (out_y * out_z)) / out_z;
int z_idx = voxel_idx_flat % out_z;
if (box_idx >= boxes_num || channel_idx >= channels || x_idx >= out_x ||
y_idx >= out_y || z_idx >= out_z)
return;
int offset_base = x_idx * out_y * out_z + y_idx * out_z + z_idx;
pts_idx_of_voxels += box_idx * out_x * out_y * out_z * max_pts_each_voxel +
offset_base * max_pts_each_voxel;
grad_out += box_idx * out_x * out_y * out_z * channels +
offset_base * channels + channel_idx;
int total_pts = pts_idx_of_voxels[0];
float cur_grad = 1 / fmaxf(float(total_pts), 1.0);
for (int k = 1; k <= total_pts; k++) {
atomicAdd(grad_in + pts_idx_of_voxels[k] * channels + channel_idx,
grad_out[0] * cur_grad);
}
}
void roiaware_pool3d_backward_launcher(int boxes_num, int out_x, int out_y, int out_z, int channels, int max_pts_each_voxel,
const int *pts_idx_of_voxels, const int *argmax, const float *grad_out, float *grad_in, int pool_method){
// params pts_idx_of_voxels: (N, out_x, out_y, out_z, max_pts_each_voxel)
// params argmax: (N, out_x, out_y, out_z, C)
// params grad_out: (N, out_x, out_y, out_z, C)
// params grad_in: (npoints, C), return value
// params pool_method: 0: max_pool, 1: avg_pool
dim3 blocks(DIVUP(out_x * out_y * out_z, THREADS_PER_BLOCK), channels, boxes_num);
dim3 threads(THREADS_PER_BLOCK);
if (pool_method == 0){
roiaware_maxpool3d_backward<<<blocks, threads>>>(
boxes_num, channels, out_x, out_y, out_z, argmax, grad_out, grad_in
);
}
else if (pool_method == 1){
roiaware_avgpool3d_backward<<<blocks, threads>>>(
boxes_num, channels, out_x, out_y, out_z, max_pts_each_voxel, pts_idx_of_voxels, grad_out, grad_in
);
}
void roiaware_pool3d_backward_launcher(int boxes_num, int out_x, int out_y,
int out_z, int channels,
int max_pts_each_voxel,
const int *pts_idx_of_voxels,
const int *argmax, const float *grad_out,
float *grad_in, int pool_method) {
// params pts_idx_of_voxels: (N, out_x, out_y, out_z, max_pts_each_voxel)
// params argmax: (N, out_x, out_y, out_z, C)
// params grad_out: (N, out_x, out_y, out_z, C)
// params grad_in: (npoints, C), return value
// params pool_method: 0: max_pool, 1: avg_pool
dim3 blocks(DIVUP(out_x * out_y * out_z, THREADS_PER_BLOCK), channels,
boxes_num);
dim3 threads(THREADS_PER_BLOCK);
if (pool_method == 0) {
roiaware_maxpool3d_backward<<<blocks, threads>>>(
boxes_num, channels, out_x, out_y, out_z, argmax, grad_out, grad_in);
} else if (pool_method == 1) {
roiaware_avgpool3d_backward<<<blocks, threads>>>(
boxes_num, channels, out_x, out_y, out_z, max_pts_each_voxel,
pts_idx_of_voxels, grad_out, grad_in);
}
}
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