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fixed wrong cur_geom_feats address in file of bev_pool_cuda.cu and add QuickCumsumMean function in torch #4

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fixed wrong cur_geom_feats address in file of bev_pool_cuda.cu and add QuickCumsumMean function in torch #4

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30710fd
fixed bev_pool cuda .cu wrong cur_geom_feats address
ZouJiu1 Apr 19, 2026
615e6cd
attach .cu .cpp file to reproduce
ZouJiu1 Apr 19, 2026
817b68a
remove bevpool.zip
ZouJiu1 Apr 19, 2026
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39 changes: 39 additions & 0 deletions models/bevdet/ops/bev_pool/bev_pool.py
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Original file line number Diff line number Diff line change
Expand Up @@ -126,6 +126,45 @@ def backward(ctx, out_grad):

return x_grad, None, None, None, None, None, None

class QuickCumsumMean(torch.autograd.Function):

@staticmethod
def forward(ctx, x, geom_feats, ranks):
x = x.cumsum(0)
kept = torch.ones(x.shape[0], device=x.device, dtype=torch.bool)
kept[:-1] = ranks[1:] != ranks[:-1]

interval_starts = torch.where(kept)[0].int()
interval_lengths = torch.zeros_like(interval_starts)
interval_lengths[1:] = interval_starts[1:] - interval_starts[:-1]
interval_lengths[0] = interval_starts[0] + 1

x, geom_feats = x[kept], geom_feats[kept]
x = torch.cat((x[:1], x[1:] - x[:-1]))

interval_lengths = interval_lengths.unsqueeze(-1)
x = x / interval_lengths

# save kept for backward
ctx.save_for_backward(kept)
ctx.save_for_backward(interval_lengths)

# no gradient for geom_feats
ctx.mark_non_differentiable(geom_feats)

return x, geom_feats

@staticmethod
def backward(ctx, gradx, gradgeom):
(kept, interval_lengths) = ctx.saved_tensors
back = torch.cumsum(kept, 0)
back[kept] -= 1

gradx /= interval_lengths

val = gradx[back]

return val, None, None

def bev_pool(feats, coords, B, D, H, W, mean_pool=False):
assert feats.shape[0] == coords.shape[0]
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8 changes: 4 additions & 4 deletions models/bevdet/ops/bev_pool/src/bev_pool_cuda.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -31,7 +31,7 @@ __global__ void bev_pool_kernel(int b, int d, int h, int w, int n, int c, int n_
return;
int interval_start = interval_starts[index];
int interval_length = interval_lengths[index];
const int *cur_geom_feats = geom_feats + interval_start * 4;
const int *cur_geom_feats = geom_feats + (interval_start + interval_length - 1) * 4;
const float *cur_x = x + interval_start * c + cur_c;
float *cur_out = out + cur_geom_feats[3] * d * h * w * c +
cur_geom_feats[2] * h * w * c + cur_geom_feats[0] * w * c +
Expand Down Expand Up @@ -75,7 +75,7 @@ __global__ void bev_pool_grad_kernel(int b, int d, int h, int w, int n, int c, i
int interval_start = interval_starts[index];
int interval_length = interval_lengths[index];

const int *cur_geom_feats = geom_feats + interval_start * 4;
const int *cur_geom_feats = geom_feats + (interval_start + interval_length - 1) * 4;
float *cur_x_grad = x_grad + interval_start * c + cur_c;

const float *cur_out_grad = out_grad + cur_geom_feats[3] * d * h * w * c +
Expand Down Expand Up @@ -103,7 +103,7 @@ __global__ void bev_mean_pool_kernel(int b, int d, int h, int w, int n, int c, i
return;
int interval_start = interval_starts[index];
int interval_length = interval_lengths[index];
const int *cur_geom_feats = geom_feats + interval_start * 4;
const int *cur_geom_feats = geom_feats + (interval_start + interval_length - 1) * 4;
const float *cur_x = x + interval_start * c + cur_c;
float *cur_out = out + cur_geom_feats[3] * d * h * w * c +
cur_geom_feats[2] * h * w * c + cur_geom_feats[0] * w * c +
Expand Down Expand Up @@ -134,7 +134,7 @@ __global__ void bev_mean_pool_grad_kernel(int b, int d, int h, int w, int n, int
int interval_start = interval_starts[index];
int interval_length = interval_lengths[index];

const int *cur_geom_feats = geom_feats + interval_start * 4;
const int *cur_geom_feats = geom_feats + (interval_start + interval_length - 1) * 4;
float *cur_x_grad = x_grad + interval_start * c + cur_c;

const float *cur_out_grad = out_grad + cur_geom_feats[3] * d * h * w * c +
Expand Down