Pikaliov
1b3206b6a7
- Add enhanced README with project structure and quick start guide - Initialize repository with DCNv4 CUDA extension (PyTorch module) - Include classification, detection, and segmentation subdirectories - Reference upstream OpenGVLab DCNv4 implementation Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
24 lines
996 B
Python
24 lines
996 B
Python
import os
|
|
|
|
def factors(N):
|
|
res = []
|
|
for i in range(1, N+1):
|
|
if N % i == 0:
|
|
res.append(i)
|
|
return res
|
|
|
|
if __name__ == '__main__':
|
|
BATCH=64
|
|
for group_channel in [16, 32, 64]:
|
|
for group in [4, 5, 6, 7, 8]:
|
|
for N, Hin, Win in [(BATCH, 56, 56), (BATCH, 28, 28), (BATCH, 14, 14), (BATCH, 7, 7),
|
|
(1, 200, 320), (1, 100, 160), (1, 50, 80), (1, 25, 40), (1, 64, 64)]:
|
|
for d_stride in [2, 4, 8, 16]:
|
|
for m in factors(N*Hin*Win):
|
|
if m > 64:
|
|
break
|
|
block_thread = group * (group_channel//d_stride) * m
|
|
if block_thread > 1024:
|
|
break
|
|
cmd = f"python search_dcnv4.py --n {N} --h {Hin} --w {Win} --g {group} --c {group_channel} --dstride {d_stride} --blockthread {block_thread} --multiplier {m}"
|
|
os.system(cmd) |