NMS_GPU different results from NMS_CPU

I compiled successfully in Ubuntu 14.04 and I use Python 3.6

import numpy as np
detections = torch.from_numpy(np.array([
    (12, 84, 140, 212, 0.1),
	(24, 84, 152, 212, 0.8),
	(36, 84, 164, 212, 0.7),
	(12, 96, 140, 224, 0.6),
	(24, 96, 152, 224, 0.5),
	(24, 108, 152, 236, 0.9)
]))

# print(detections)
print(nms_gpu(detections, 0.1))
print(nms_cpu(detections, 0.1))

## print results below
tensor([], dtype=torch.int32)
tensor([ 5], dtype=torch.int32)

You can see here, the CPU results is correct, whereas the GPU results is not returning anything

[zhenheny]

Hi @sidazhang @jwyang I think it is related to #212 . Line 23 and Line 24 need to be fixed. https://github.com/jwyang/faster-rcnn.pytorch/blob/7079dfbc4e734168e1a123cb1a5a60cdc39f52ed/lib/model/nms/nms_cpu.py#L23

xx2 = np.minimum(x2[i], x2[order[1:]])
yy2 = np.minimum(y2[i], y2[order[1:]])

should generate same results as gpu version code.

[devendraswamy]

when i am kept the training, in few minutes the server was restarted so please tell any suggestion for this . thanking you !