xautodl/lib/models/shape_searchs/test.py
2019-11-05 23:35:28 +11:00

18 lines
501 B
Python

import torch
import torch.nn as nn
from SoftSelect import ChannelWiseInter
if __name__ == '__main__':
tensors = torch.rand((16, 128, 7, 7))
for oc in range(200, 210):
out_v1 = ChannelWiseInter(tensors, oc, 'v1')
out_v2 = ChannelWiseInter(tensors, oc, 'v2')
assert (out_v1 == out_v2).any().item() == 1
for oc in range(48, 160):
out_v1 = ChannelWiseInter(tensors, oc, 'v1')
out_v2 = ChannelWiseInter(tensors, oc, 'v2')
assert (out_v1 == out_v2).any().item() == 1