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fix default settings for point rasterization and update benchmark

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Summary:
Fixes the default setting of `max_points_per_bin` in `rasterize_points.py`. For large batches with large size pointclouds this was a causing the rasterizer to be very slow.

Expanded the pointcloud rendering benchmarks to include larger size pointclouds and fixed cuda synchronization issue in benchmark.

Reviewed By: gkioxari

Differential Revision: D22301185

fbshipit-source-id: 5077c1ba2c43d73efc1c659f0ec75959ceddf893
This commit is contained in:
Nikhila Ravi 2020-06-30 12:39:20 -07:00 committed by Facebook GitHub Bot
parent b636f2950d
commit 88f579389f
2 changed files with 15 additions and 3 deletions
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2
pytorch3d/renderer/points/rasterize_points.py
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@ -98,7 +98,7 @@ def rasterize_points(
)
if max_points_per_bin is None:
max_points_per_bin = int(max(10000, points_packed.shape[0] / 5))
max_points_per_bin = int(max(10000, pointclouds._P / 5))
# Function.apply cannot take keyword args, so we handle defaults in this
# wrapper and call apply with positional args only

16
tests/bm_rasterize_points.py
View File

@ -28,10 +28,17 @@ def _bm_cpu_with_init(N, P, img_size=32, radius=0.1, pts_per_pxl=3):
def _bm_cuda_with_init(N, P, img_size=32, radius=0.1, pts_per_pxl=3):
torch.manual_seed(231)
points = torch.randn(N, P, 3, device=torch.device("cuda"))
device = torch.device("cuda:0")
points = torch.randn(N, P, 3, device=device)
pointclouds = Pointclouds(points=points)
args = (pointclouds, img_size, radius, pts_per_pxl)
return lambda: rasterize_points(*args)
torch.cuda.synchronize(device)
def fn():
rasterize_points(*args)
torch.cuda.synchronize(device)
return fn
def bm_python_vs_cpu() -> None:
@ -46,4 +53,9 @@ def bm_python_vs_cpu() -> None:
{"N": 4, "P": 1024, "img_size": 128, "radius": 0.05, "pts_per_pxl": 5},
]
benchmark(_bm_cpu_with_init, "RASTERIZE_CPU", kwargs_list, warmup_iters=1)
kwargs_list += [
{"N": 32, "P": 10000, "img_size": 128, "radius": 0.01, "pts_per_pxl": 50},
{"N": 32, "P": 100000, "img_size": 128, "radius": 0.01, "pts_per_pxl": 50},
{"N": 8, "P": 200000, "img_size": 512, "radius": 0.01, "pts_per_pxl": 50},
]
benchmark(_bm_cuda_with_init, "RASTERIZE_CUDA", kwargs_list, warmup_iters=1)